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AI Engineer

$80k – $160k • 0.0% – 0.4%

We’re building Reflow, a workforce and workflow intelligence platform that helps teams understand and improve how work gets done. A key part of that vision is Reflow AI, agentic, automation-focused intelligence that adapts to how people actually work. We’re looking for an AI developer who can experiment fast, optimize intelligently, and help us push the boundaries of AI-assisted performance.

What you’ll do

• Develop, optimize, and maintain agentic AI pipelines for automation and workflow intelligence.
• Experiment with prompt engineering, context tuning, and model orchestration to improve performance and adaptability.
• Work with vector databases, RAG (retrieval-augmented generation), and related frameworks for contextual intelligence.
• Collaborate with engineers and product teams to integrate AI systems into real-world workflows.
• Continuously refine and improve models through experimentation, data feedback, and iterative development.

Who you are

• Strong foundation in Python, LLMs, and agentic architectures.
• Experienced in prompt engineering, context optimization, and AI pipeline design.
• Comfortable building fast prototypes and testing model behavior in varied, complex contexts.
• Curious, pragmatic, and unafraid to experiment, you turn uncertainty into working systems.

Bonus points

• Experience integrating AI into desktop or web apps.
• Familiarity with LangChain, OpenAI API, or similar frameworks.
• Background in automation systems, workflow optimization, or enterprise AI tools.

Why join

You’ll help shape the intelligence core of Reflow, the layer that learns from work patterns and turns data into action. You’ll work across experiments, prototypes, and production systems, collaborating directly with founders and engineers. Ideal for someone who loves to push AI beyond the theoretical into the real.

We’re flexible on structure (part or full-time). What matters is iteration speed, creativity, and a bias for working code.

Job Overview:

The AI Data Engineer is responsible for building and operating high‑quality, governed, and AI‑ready data pipelines that power enterprise GenAI and agent‑based use cases. This role focuses on preparing data for retrieval‑augmented generation (RAG), managing embeddings and vector indexes, and ensuring data quality, lineage, and compliance across the AI platform. As part of the AI CoE Technology pod, the AI Data Engineer enables rapid, responsible AI development by delivering reusable, scalable data foundations. This is a hands‑on individual contributor role within the AI CoE – Technology pod, working closely with AI Platform Engineers and AI Engineers to support both shared platform capabilities and priority AI use cases. The role is intentionally centralized to avoid fragmented data pipelines and to ensure consistent governance, quality, and reuse across the enterprise.

Major Responsibilities:

• Design, build, and maintain data pipelines that ingest, transform, and curate structured and unstructured data for AI use cases.
• Prepare RAG‑ready datasets by applying metadata enrichment, chunking, normalization, and document parsing patterns aligned to platform standards.
• Partner with source system teams and domain SMEs to understand data semantics and ensure accurate representation for AI consumption.

• Create and maintain embedding pipelines, including generation, refresh, and lifecycle management.
• Own vector index maintenance, including re‑indexing strategies, performance tuning, and cleanup of stale or unused embeddings.
• Support knowledge grounding for AI agents by ensuring source attribution, consistency, and traceability.

• Implement data quality checks, validation rules, and monitoring to ensure accuracy, completeness, and reliability of AI datasets.
• Ensure all AI data pipelines comply with enterprise data governance, privacy, and information management policies, including support for regulated and sensitive data use cases.
• Collaborate with Architecture, Security, and Information Governance partners to align data handling with approved AI patterns and risk controls.

• Support AI Engineers during onboarding and troubleshooting by diagnosing data issues that affect agent behavior or retrieval accuracy.
• Contribute reusable data patterns, templates, and documentation to accelerate future AI use cases.
• Participate in platform support activities defined in the AI CoE RACI, particularly those related to data grounding and vector maintenance.

• Optimize data and embedding pipelines for performance, scalability, and cost efficiency, in partnership with Platform Engineers.
• Monitor data freshness and usage trends to recommend retirement, refresh, or enhancement of datasets supporting AI agents.

Qualifications:

• Bachelor’s degree in computer science, Engineering, Data Science, or a related technical discipline OR equivalent combination of education and relevant experience.
• Demonstrated experience designing and operating production-grade data pipelines in an enterprise environment.
• Experience working with unstructured data (documents, text, PDFs) and preparing data for analytics, ML, or AI use cases.
• Working knowledge of embeddings, vector databases, and retrieval patterns used in modern AI and GenAI solutions.
• Strong understanding of data quality, lineage, and governance concepts.

Additional Licensing, Certifications, Registrations:

• Professional certification(s) in area of expertise a plus

-AWS Machine Learning Specialty, Azure AI Engineer Associate, or equivalent cloud certifications.

-Databricks and/or Snowflake certifications

Knowledge, Skills, and Abilities:

• Strong hands-on experience designing and operating data pipelines for analytics, ML, or AI workloads.
• Experience working with unstructured data (documents, PDFs, text) and preparing it for downstream AI or search use cases.
• Knowledge of embeddings, vector databases, and retrieval patterns used in RAG or knowledge-based AI systems.
• Strong understanding of data quality, lineage, and governance concepts in enterprise environments.
• Experience supporting GenAI or agentic AI platforms in a regulated enterprise environment (e.g., healthcare, financial services).
• Familiarity with cloud-native data services and AI platforms commonly used for enterprise AI enablement.
• Experience partnering with platform and application teams in a federated or hub-and-spoke operating model.
• Understanding of healthcare compliance standards (HIPAA, HITRUST) and ethical AI practices (bias, explainability,data privacy).
• Ability to collaborate effectively with cross-functional teams and translate business requirements into technical solutions.
• Strong problem-solving and innovation mindset, with the ability to adapt generative AI to real-world challenges in healthcare and ability to adapt to and adapt to evolving priorities and technologies
• Familiarity with governance and compliance frameworks relevant to healthcare (HIPAA, SOC 2, HITRUST) preferred

Job Overview:

The AI Platform Engineer builds, hardens, and helps operate the enterprise GenAI/agentic platform that enables teams to safely develop and run AI agents at scale. This role owns the platform “foundations”—including LLM gateway & model routing, vector/knowledge base infrastructure, CI/CD and IaC automation, observability, and cost/usage management across use cases —so Dev teams can deliver agents quickly under consistent governance and controls. This role focuses on shared platform capabilities (as distinct from use-case AI engineering) and partners closely with CoE product/ops enablement and governance stakeholders to keep the platform scalable, compliant, and easy to onboard new agents and tools.

Key Responsibilities:

• Engineer and maintain the platform’s foundational capabilities: LLM gateway, model routing, shared compute/infrastructure, and platform governance controls.
• Onboard and support new platform capabilities and tools used by agents (e.g., adding/maintaining supported models and agent tooling standards).
• Provision and manage platform resources needed to scale agent development (e.g., provisioning Bedrock Knowledge Bases/vector-backed retrieval components where applicable).
• Build and maintain Terraform (or equivalent) IaC to create/update platform resources and dashboards; keep deployments repeatable across environments.
• Own and operate platform pipelines: executing Terraform + backend/frontend pipelines, troubleshooting failed deployments, and improving delivery reliability.
• Provide “platform support” for agent teams by diagnosing platform-related issues (e.g., deployment/update failures, agent creation problems, missing/incorrect results, conversation memory issues).
• Implement and maintain monitoring for performance/quality and agent behavior over time (including benchmark testing and evaluation monitoring such as “Bedrock Eval” where applicable).
• Own platform cost & usage management practices (budget signals, usage metrics, reporting, optimization recommendations).
• Collaborate with Security/Architecture/Governance partners to ensure platform controls align to enterprise policies and approved operating patterns (e.g., access controls, safe enablement of who can create what kinds of agents).

Required Qualifications:

• Bachelor’s degree in computer science, Engineering, Information Systems, or related technical discipline, or equivalent experience.
• Demonstrated experience designing and operating shared application or platform services in an enterprise environment.
• Experience with CI/CD pipelines, automation, and infrastructure provisioning.
• Working knowledge of modern AI/ML or GenAI platforms and cloud-based services.
• Strong understanding of operational reliability, monitoring, and support practices.
• Experience supporting AI, ML, or GenAI platforms in regulated industries (e.g., healthcare, insurance, financial services).
• Familiarity with agent-based architectures, LLM model integration, and AI platform patterns.
• Experience with cloud cost management, usage monitoring, or FinOps practices.
• Professional cloud or AI-related certifications (AWS, Azure, or equivalent).

Benefits:

• Flexible remote work environment.
• Comprehensive health benefits and wellness programs.
• Opportunities for professional development and career growth.

Company Culture:

At Cinteot, we foster an inclusive and collaborative environment where innovation thrives. We believe in empowering our employees to take ownership of their work and contribute to meaningful projects that impact our community and industry.

AI Engineer

$80k – $160k • 0.0% – 0.4%

We’re building Reflow, a workforce and workflow intelligence platform that helps teams understand and improve how work gets done. A key part of that vision is Reflow AI, agentic, automation-focused intelligence that adapts to how people actually work. We’re looking for an AI developer who can experiment fast, optimize intelligently, and help us push the boundaries of AI-assisted performance.

What you’ll do

• Develop, optimize, and maintain agentic AI pipelines for automation and workflow intelligence.
• Experiment with prompt engineering, context tuning, and model orchestration to improve performance and adaptability.
• Work with vector databases, RAG (retrieval-augmented generation), and related frameworks for contextual intelligence.
• Collaborate with engineers and product teams to integrate AI systems into real-world workflows.
• Continuously refine and improve models through experimentation, data feedback, and iterative development.

Who you are

• Strong foundation in Python, LLMs, and agentic architectures.
• Experienced in prompt engineering, context optimization, and AI pipeline design.
• Comfortable building fast prototypes and testing model behavior in varied, complex contexts.
• Curious, pragmatic, and unafraid to experiment, you turn uncertainty into working systems.

Bonus points

• Experience integrating AI into desktop or web apps.
• Familiarity with LangChain, OpenAI API, or similar frameworks.
• Background in automation systems, workflow optimization, or enterprise AI tools.

Why join

You’ll help shape the intelligence core of Reflow, the layer that learns from work patterns and turns data into action. You’ll work across experiments, prototypes, and production systems, collaborating directly with founders and engineers. Ideal for someone who loves to push AI beyond the theoretical into the real.

We’re flexible on structure (part or full-time). What matters is iteration speed, creativity, and a bias for working code.

Automation Engineer — AI Agent Systems
Remote, Latin America | 3–4+ years of actually shipping things
Reports to: Senior Operational Leader

About Bold Business
We build multi-agent AI systems that do real Sales and Recruiting work, not demo-day theater. If it cannot survive a Tuesday with real users, it does not count.

The job
You will build and run agent systems: routing, workers, tools, memory, retries, and the part where we find out it broke at 11pm. You work with a Lead Architect and with Sales and Recruiting humans who will tell you if it is useful. You will not disappear into a cave and emerge with a framework rewrite.

You will also sit with the developers building our CRM, ATS, and ERP. You represent this team in those rooms so those systems can talk to our agents, and our agents can talk back. You are the integration. You are not the CRM owner.

Ask questions. Show the work. If something is on fire, say so the same day. We have already lived the other version.

What you will actually do

• Build Python agents that behave as a system, not as 14 clever prompts in a trench coat
• Wire them to real platforms: APIs, webhooks, data in, data out, no duplicate rows because the webhook got excited
• Work with the teams building our CRM, ATS, and ERP. Show up in their design conversations. Do not leave until the APIs and events actually work for automation
• Debug production like an adult. Trace the bad run to the tool call, the payload, or the prompt
• Log decisions, tool calls, and cost. Alert us before finance does
• Sit with users, watch them use it, then change it

Must have (we will test these, not just admire them on a resume)

Hard

• 3–4+ years of backend, automation, or AI that ran in production. Walk us through something you shipped. “I contributed” is not a walkthrough.
• Production LLM APIs (OpenAI, Anthropic, Groq, or similar). Tool calls, rate limits, token burn, and what a failure looks like when it is not a blog post
• Python someone else can maintain. Tests and CI you actually run
• REST and webhooks: idempotency, retries, timeouts. Pop quiz: it fires twice. What happens.
• SQL past SELECT *. Joins, indexes. Postgres is a plus
• You can read logs and find the root cause. You assume failure is the default and you designed for it

Soft

• Clear English, written and spoken, with a US team. Your application is the first test. Use it.
• You surface problems the same day, not in the postmortem
• You will start without a 40-page spec
• You care if Sales or Recruiting actually used the thing, not just that it compiled
• You can sit with another engineering team, explain what we need in plain English, and not leave until the API and events actually work for automation. Salesforce / HubSpot / Greenhouse / ERP experience is a plus, not a must. Surviving someone else’s system is the must.

Nice to have (we can teach this)
LangChain, LangGraph, LlamaIndex, or whichever library is fashionable this quarter. Vector DBs. AWS/GCP, Docker. Datadog. Prompt evals. If you have them, great. If you don’t, and you have shipped systems, we will live.

Why Join Bold Business?

• Build on your Python and integration skills while learning AI systems alongside our senior team.
• Build solutions used directly by Sales and Recruiting teams.
• Work with real APIs, databases, automation, and AI integrations.
• Work remotely with a US-based team with clear collaboration hours and competitive compensation.

Details
Remote, Latin America. Overlap live US hours or this does not work.
Pay is competitive and tied to what you have shipped, not how many libraries you can name. Equipment provided. Health insurance included.

Shipped systems. Clear communication. Curiosity. That is the whole interview.

About Bold Business

Bold Business is an AI-first U.S. based global workforce solutions company rebuilding how businesses operate in the AI era. We build AI-Amplified Talent™, custom AI agents, and automation systems for clients like AT&T, JP Morgan, and Verizon — and we back every engagement. If you want to build things that ship and matter, you'll fit right in.

The Role 

You are the technical standard-setter and primary builder for how AI systems are designed, built, and shipped at Bold.

You will:

• Architect systems
• Build them yourself
• Set the bar for everyone else

If you haven’t personally shipped production AI systems end-to-end, this role will not be a fit.

What You’ll Do

Build Real Systems

• Design and ship production RAG pipelines (end-to-end)
• Build multi-agent systems used by real clients
• Integrate LLMs into production workflows (not prototypes)
• Own backend systems (FastAPI, multi-tenant, secure)
• Deploy with Docker + CI/CD + cloud
• Measure and improve output quality before anything ships

Set the Standard

• Define how AI systems are built at Bold
• Establish architecture patterns, prompting standards, and data flows
• Own code quality and reviews — nothing ships without your approval
• Choose tools, frameworks, and infrastructure
• Mentor engineers and raise the performance bar across the team

Non-Negotiable Requirements

English communication — non-negotiable

• Advanced to fluent English — written and spoken
• Ability to explain technical concepts clearly to non-technical stakeholders: clients, founders, business owners
• Professional written communication across emails, Slack, documentation, and status updates
• Comfortable on video calls and async communication with a U.S.-based team

RAG (This Defines the Role)

• You have shipped 2+ production RAG systems (not demos)
• You can explain every decision (chunking, embeddings, retrieval, re-ranking)
• You’ve worked with vector databases in production
• You’ve debugged real issues (hallucination, low recall, bad retrieval)
• You’ve built multi-tenant systems with clean data separation
• You know how to measure and improve output quality

Core Engineering

• 5+ years Python in production
• 3+ years building AI/LLM systems used by real users
• LangChain / LangGraph in production (not tutorials)
• Experience designing multi-agent systems
• Strong backend experience (FastAPI or equivalent)
• Docker, CI/CD, cloud deployment
• Security fundamentals (auth, secrets, isolation)
• Strong written English (clear, direct, professional)
• Proven ability to set and enforce engineering standards

Strong Signals (Highly Valued)

• LlamaIndex, hybrid search, or re-ranking models
• RAG over complex data (PDFs, tables, images)
• Open-source LLMs (Ollama, vLLM)
• MLOps, evaluation, monitoring
• Voice AI pipelines
• Experience leading technical direction for a team
• Client-facing delivery experience

Who You Are

• You build and think in systems, not just features
• You don’t wait to be unblocked — you solve it
• You care about clean, scalable systems in production
• You can explain complex systems simply
• You push standards higher, even when it’s uncomfortable

Experience: 5–8 years
Proof: Live systems with real users (required)

How We Evaluate You

We will ask you to:

• Walk through a system you built in detail
• Explain your architectural decisions
• Build a working RAG pipeline
• Show how you think, not just what you know

Bold Business

AI-First. Standards-First. Delivery-First.
We build systems that ship, scale, and earn trust.

Location: Fully Remote but must have UK/EU work authorization
Type: Full-time contractor, with a path to conversion to salaried role + equity

Reports to: Chief Scientific Officer (until Head of Engineering is hired)

Compensation: $8,000 USD/month contractor rate 

Background Screening: Required per client + legal obligations

Website: www.anadyr-horizon.com

The Mission

Anadyr Horizon builds Strategic Warning AI — technology designed to help governments and institutions see crises before they happen and prevent escalation.

This isn’t “yet another stack.”

You’ll be engineering the backbone of a system used by analysts, operators, and real-world decision-makers navigating high-pressure environments.

We’re assembling a founding engineering team — just three people — to take research prototypes and turn them into production systems that actually shape global outcomes.

If you’ve ever wanted to say “I built the infrastructure behind a new category of intelligence software”, this is that moment.

What You’ll Do

• Build and maintain FastAPI services that power agentic simulations and data pipelines.
• Design PostgreSQL schemas, optimize queries, and manage migrations (SQL proficiency required).
• Deploy and monitor workloads on AWS with CI/CD and infrastructure-as-code practices.
• Set up and maintain observability (metrics, logs, traces, error handling) with SLO/SLA thinking and privacy-safe product analytics/UX telemetry (e.g., PostHog/OpenReplay or Hotjar with strict field masking, consent, and data-residency controls).
• Collaborate on system design with research and product leads — from concept → prototype → production.
• Contribute to engineering standards: code review, testing, linting, typed Python, and rollback plans.

What You’ll Bring

• Proficient in Python and SQL; strong back-end engineering fundamentals.
• Experience with Linux and building/consuming APIs.
• Ability to pick up new technologies quickly (e.g., AWS cloud services).
• Docker experience for local development and deployment.
• Strong communication skills and ability to explain technical concepts clearly.
• Familiarity with React and Next.js is a bonus (not a strict requirement).
• Emphasis on strong coding skills and back-end depth over front-end specialization.

Must-Have Experience

• 3–5+ years shipping production web applications with clear ownership of features from design to deploy (preferably in small, high-velocity teams).
• Backend depth in Python: FastAPI (preferred) or Flask, strong async fundamentals, Pydantic/typing, and SQL/PostgreSQL mastery (schema design, indexing, query plans, migrations).
• Frontend capability, not dependency: comfortable building and maintaining React + TypeScript views and UI flows; deep front-end specialization is not required.
• DevOps proficiency: hands-on with Docker, CI/CD (e.g., GitHub Actions), and practical AWS (EC2, S3, VPC, IAM basics); able to stand up and monitor services.
• Observability + reliability: metrics, logs, traces (OpenTelemetry/Prometheus/Grafana) and SLO/SLA thinking;
• privacy-safe product analytics/UX telemetry (e.g., PostHog/OpenReplay or Hotjar with strict field masking, consent, and data-residency controls).
• Security-minded habits: least-privilege IAM, secrets management, auditability, and rollback plans.
• Communication & collaboration: clear written English (PRs/design notes/runbooks), effective remote collaboration during EU time zones, and a bias to ship.

Nice-to-Have

• Infrastructure-as-Code (Terraform/CloudFormation), Docker.
• Observability tools (OpenTelemetry, Prometheus, Grafana) and SLO/SLA thinking.
• ML serving experience (FastAPI inference endpoints, vector databases, model registries).
• Experience with simulation-heavy or data-intensive applications.
• Security & compliance: least-privilege IAM, secrets management, audit trails, and exposure to SOC-2/GDPR/data-residency practices.

Why You’ll Love It Here

You’re joining at the moment before the engineering culture solidifies — which means:

• Early influence: Help shape the engineering stack and team culture from the ground up, we’re moving from prototype to scalable, and your decisions will set the standards we grow on.
• Mission with consequence: Your code helps analysts and policymakers prevent crises, not react to them.
• Serious craft: We write typed Python, measure twice before shipping, and build systems meant to last.
• Autonomy & trust: Minimal bureaucracy, direct access to founders, rapid iteration.

Weekly Cadence (What a typical week looks like)

• Periodic stand-up (≈15 minutes, late afternoon/evening CET): crisp sync across engineering, data, product, and design.
• Deep work blocks: uninterrupted time for building, testing, and writing design notes.
• Weekly engineering planning (60–90 minutes): refine priorities, confirm acceptance criteria, and set measurable outcomes (e.g., p95 targets, migration milestones).
• Release/retro touchpoints: check what shipped, what moved metrics, and capture learnings into runbooks and tech-debt tickets.

Hiring Process

1. 20 min intro call (fit + mission)
2. Short take-home or working session (real task, no algorithm puzzles)
3. 60 min technical conversation (Python, SQL, architecture)
4. Founder conversation
5. Offer

Why Join Now

• You’ll be helping build the decision engine we wish existed during the Cuban Missile Crisis — software designed to surface escalation pathways before they become headlines.
• You’ll join the team that anticipated Ukraine’s conflict dynamics early and now partners with organizations operating in the world’s highest-stakes environments.
• You’ll ship quickly, learn relentlessly, and make an outsized impact on a deep-tech system built for analysts and policymakers who cannot afford to be surprised.

Anadyr Culture

We move fast. We operate as one aligned team.

If you’re looking for low stakes or a 9–5 buffer — this isn’t it.

If you thrive on responsibility, clarity, trust, and momentum, you’ll do the best work of your career here.

You’ll help shape the engineering culture, product experience, and norms of a deep-tech company rooted in our values:

• Integrity — we do what we say.
• Amity — we win through trust and collaboration.
• Excellence — we build with precision and purpose.

Job Overview:

The AI Product Owner is responsible for defining, prioritizing, and delivering the enterprise AI platform vision, roadmap, and capabilities that enable Agentic AI, machine learning, and generative AI solutions across the organization. This role serves as the bridge between business stakeholders, AI architects, platform engineers, data engineers, data scientists, and governance teams to ensure the AI platform delivers measurable business value, scalability, security, and operational excellence.

Key Responsibilities:

• Own and prioritize the Agile Team backlog for AI platform initiatives.
• Create and refine user stories, acceptance criteria, and feature decompositions.
• Define and maintain the product vision, strategy, and roadmap for enterprise AI platform capabilities.
• Translate business needs into clear user stories, acceptance criteria, and product requirements.
• Serve as the primary liaison between business stakeholders and AI platform delivery teams.
• Ensure platform capabilities align with organizational security, compliance, and AI governance requirements.
• Drive automation, standardization, and self-service capabilities to improve developer productivity.

Required Qualifications:

• High School Diploma/GED required. Bachelor’s degree in computer science, Engineering, Information Systems, Business, Data Science, or related field strongly preferred.
• 7+ years of experience in product management, technology delivery, platform management, AI/ML programs, or related disciplines.
• 3+ years of experience supporting AI, machine learning, data platforms, analytics platforms, or cloud-based technology products.
• Experience working in Agile/Scrum product delivery environments.
• Strong understanding of AI/ML lifecycles, cloud platforms, and enterprise technology ecosystems.

Benefits:

• Flexible remote work arrangements to support work-life balance.
• Comprehensive health and wellness benefits.
• Opportunities for professional development and career growth.

Company Culture:

At Cinteot, we believe in fostering an inclusive environment where diverse perspectives are valued. We are committed to innovation, collaboration, and continuous improvement, empowering our employees to thrive in their careers and contribute to our mission of delivering cutting-edge AI solutions.

About the job

About IMPACTER Pathway

IMPACTER Pathway is a Human Skills Analytics company building the measurement infrastructure schools have always needed and never had — the ability to see student growth in the human competencies that actually predict long-term success: purpose, grit, curiosity, perspective-taking, compassion. Our platform turns authentic student voice into rubric-aligned, decision-grade insight for districts, county offices, and state systems. We're one of the fastest-growing EdTech companies in the country, serving 200K+ monthly active students across 236+ school sites, with state, county, and district contracts coast to coast.

The role

You're design-minded and you know code. You live in Figma and you're just as comfortable in a terminal — you know your way around Git, the command line, and how software actually fits together, and you can take an idea from sketch to a working, clickable thing in an afternoon using Claude Code, Codex, and the modern AI building stack.

You'll build solutions that communicate and demonstrate our data, like these:

• https://bh.impacterpathway.com/
• https://nc.impacterpathway.com/
• https://smfcsd.portrait.impacterpathway.com/
• https://sd.impacterpathway.com/

And statewide accountability systems that bring transparency to taxpayer-funded initiatives, like these:

• https://bh.impacterpathway.com/accountability
• https://bh.impacterpathway.com/portal

You're not a career software engineer, and that's fine — you're the person who turns "what if we could" into something people can actually click. (We have a 20-person engineering team that owns and ships our production code. This isn't a seat on that team, and it isn't a heads-down back-end or infrastructure role.)

What you'll do

• Take real customer problems from districts, county offices, and school site teams, and turn them into working product in days, not months
• Design and ship beautifully crafted UX/UI surfaces using Claude Code, Codex, Figma, and the modern AI building stack
• Prototype new features, internal tools, customer-facing dashboards, and district reports — the stuff that lives between "what if we could" and "here, try this"
• Partner with our ML and engineering team on anything that touches production systems or our scoring pipeline — they own production, you build the thing that proves it's worth building
• Move fast, document well, ship constantly

Who you are

• You have a real technical foundation. CS coursework, a CS degree, or equivalent hands-on experience. You're comfortable with Git, the command line, and the basic mechanics of how software gets built and shipped.
• You can code, even if you're not a "developer." You don't identify as a software engineer, and that's fine. But you can read, write, and debug real code, not just prompt your way around it. When an AI tool hands you something broken, you can figure out why.
• You're AI-native. You've shipped real things with Claude Code, Codex, Cursor, Lovable, Replit, or the equivalent, and you can show us a live link.
• You have strong design sensibility. You know Figma, you know what good product looks like, and you can build to that bar.
• You're a tinkerer. Curious, willing, restless. The kind of person who breaks things to learn them.
• You write well. We run on async writing.
• K-12, education, or classroom background is a plus — domain empathy helps — but it is not a requirement for this role.

Not for you if:

• You want a heads-down back-end or infrastructure engineering job (we have that team, this isn't that seat)
• You've only ever prompted — you've never actually touched Git, a terminal, or real code
• You want a VA / executive assistant / general operations role
• You can't show us a working thing you've shipped with AI building tools

Logistics

• Compensation: $30–$40/hr (commensurate with experience), with a contract-to-full-time conversion path
• Location: Remote (Pacific Time overlap). SoCal preferred for periodic in-person sprint days
• Must be authorized to work in the United States and physically based in the US. Due to FERPA, COPPA, and state-level student data privacy requirements, all work, devices, and data handling must occur within the United States. This role is not eligible for offshore contracting or remote work outside the US.

How to apply (required, in this order)

1. Your LinkedIn or resume (apply to this post, link at the top) or send Steve a direct email at jobs@impacterpathway.com
2. A live link to something you've built or shipped using Claude Code, Codex, Cursor, Lovable, or Replit. This is required, not optional.

-          If you don't have one, this isn't the role for you yet.

3. A 90-second voice note: the three words people would use to describe you, and why you'd thrive in this role. (We'll send you a link for this separately.)

-          Steve will send the VideoAsk, after receiving your application and/or resume via: email

We screen on what you've built, not what you've claimed. That's the most important part of your application.

Location:

New York, NY (5 days per week)

Experience:

7–10+ Years (Investment Banking VP+ / Credit Investor)

The Mission:

Our client’s product is a competitive advantage for the world’s leading financial institutions. As the AI Strategy Lead, you are embedded within Tier 1 private equity firms, credit funds, and banks to transform complex workflows, including diligence, underwriting, and portfolio monitoring.

The Role: A Hybrid Powerhouse:

This is a high-ownership role that sits at the intersection of GTM Strategy, Product Development, and Senior Relationship Management. You will bridge the gap between cutting-edge LLM capabilities and the high-stakes reality of institutional finance.

Key Responsibilities:

• Strategic Deployment & Advisory: Serve as the primary AI Advisor to senior stakeholders, leading the "land-and-expand" strategy and ensuring our client’s solution becomes essential to their investment teams.
• Workflow Re-Engineering: Become a deep SME in our client’s platform to deconstruct and automate document-heavy workflows (e.g., credit agreements, lease abstractions, waterfall analyses, and complex Diligence Q&A).
• Commercial Edge: Drive measurable value creation that translates into account expansion. You will own the post-sale lifecycle, transforming initial pilots into enterprise-wide deployments through revenue-backed growth initiatives.
• Product Interlock: Serve as the "voice of the industry" for our engineering team. You will translate the nuanced needs of a Credit Investor or VP Banker into actionable product roadmaps, ensuring our LLMs (GPT, Gemini) are optimized for financial accuracy and transparency.
• Scaling the Craft: Define and enhance the internal playbooks for the AI Strategy team. As a Lead, you will help build the systems and processes that enable our client to scale from supporting $10T in AUM to the entire global market.

Who You Are:

• The Industry Veteran: You have 7–10 years of experience as a VP+ in Investment Banking or a Credit Investor at a top-tier fund. You have "lived" the manual drain of document-heavy workflows and are obsessed with fixing them.
• Technical Polymath: You don’t just use AI; you understand it. You’ve tested, built, or researched LLM applications and can move seamlessly between talking "yield" with a PM and "context windows" with an engineer.
• Executive Polish: You possess a credible presence with senior financial stakeholders. You can command a room of Partners, but aren't afraid to roll up your sleeves to map out a messy workflow in the weeds.
• Unstructured Operator: You thrive in high-intensity, "unstructured" environments. You don't need a manual; you write the manual. You move with speed, conviction, and a high degree of autonomy.

Qualifications:

• Education: Bachelor’s degree from a top-tier institution (Finance, Economics, Engineering, or Law).
• Experience: Proven track record of outperformance in high-pressure, client-facing roles (PE, IB, Private Credit, or Consulting).
• Tooling: Comfort with leading LLM models and a desire to become an expert in applied AI.
• Bonus: Technical startup or founder experience; history of building scalable systems from scratch.