15 days ago
Responsibilities
- Perform the customer’s operational job 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 Forward Deployed Executives.
- Build and ship production GenAI systems, including LLM applications, agentic workflows, retrieval and structured-extraction pipelines, backend services, data pipelines, and AI layers.
- Build evaluation harnesses, define success metrics, instrument systems, and use evaluations to guide product and engineering decisions.
- Write production code across the stack, primarily using Python and TypeScript.
- Deploy maintainable, observable, containerized systems to AWS or other customer-required cloud environments.
- Feed lessons from customer engagements back into Provectus blueprints and delivery tooling.
- Drive customer adoption, challenge assumptions with stakeholders, and own work measured against business-unit KPIs.
Requirements
- 8+ years building software, including substantial production-code ownership and current hands-on engineering.
- Willingness to spend weeks performing an operator’s job before writing code.
- Ability to quickly learn unfamiliar business domains and communicate credibly with senior stakeholders.
- Experience shipping GenAI or LLM systems to production 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, CI/CD, and production operations.
- Solid AI/ML foundations and the ability to reason about model failure modes.
- Strong hands-on production experience with Claude Code and Cowork.
- Fluent written and spoken English.
- Preferred experience includes founding or leading engineering organizations before returning to individual contribution, financial services or healthcare domain depth, consulting or embedded delivery, data platforms, MLOps, classical ML, fine-tuning, inference optimization, graph databases, infrastructure as code, open-source contributions, or public applied-AI writing.
Benefits
- Remote-friendly culture.
- B2B contract or full-time 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 across Financial Services and Healthcare with direct leadership visibility.
- Hiring process includes an introductory conversation, two live engineering sessions, a redesign session, and a team and practice conversation.
Tech Stack
Categories
Forward Deployed
