1 month ago
Washington, DC, USA or New York, NY, USASenior
Base Salary
$120k - $180k/yr
Responsibilities
- Perform the customer’s operational role for two to four weeks to understand its constraints from the inside.
- Reach working fluency in unfamiliar business domains and redesign functions from first principles with operators and executives.
- Build and ship production GenAI systems, including LLM applications, agentic workflows, retrieval and structured-extraction pipelines, backend services, data pipelines, and AI-layer components.
- Create evaluation harnesses and define measurable success criteria for non-deterministic systems before building features.
- Write production code across the stack using tools suited to each customer’s needs.
- Deploy containerized, observable, and maintainable systems on AWS or other cloud platforms as required.
- Feed field learnings back into the company’s industry blueprints.
- Drive customer adoption, shape commitments before delivery, and own outcomes tied to business-unit KPIs.
Requirements
- At least 8 years of software-building experience, including substantial production coding accountability.
- Willingness to spend weeks performing a customer’s job before writing code.
- Demonstrated ability to learn unfamiliar business domains quickly.
- Production experience shipping GenAI or LLM systems and handling post-prototype operational challenges.
- Experience building or owning evaluation suites for non-deterministic systems.
- Strong engineering fundamentals and proficiency in Python and/or TypeScript.
- Cloud-native AWS delivery experience with containers, Kubernetes or ECS, infrastructure as code, and operational ownership.
- Ability to communicate credibly with business-unit leaders, CTOs, customer engineers, operators, and executives.
- Solid AI/ML foundations and understanding of model failure modes.
- Strong hands-on production experience with Claude Code and Cowork.
- Fluent written and spoken English.
- Preferred experience includes founding, CTO, or engineering leadership experience; depth in financial services, insurance, healthcare, or asset management; consulting or embedded delivery; data platforms; MLOps and classical ML; model fine-tuning or inference optimization; graph databases; infrastructure as code; and open-source contributions or public writing on applied AI.
Benefits
- Remote-friendly culture.
- B2B contract or full-time employment model.
- Performance-based bonuses and strong earning potential.
- Unlimited vacation policy.
- Health, vision, and dental insurance.
- 401(k) matching plan.
- Opportunity to work on frontier AI delivery and help shape enterprise AI adoption.
- Direct visibility to leadership and the opportunity to build AI delivery tooling and frameworks.
Tech Stack
Categories
Forward Deployed
