Senior Forward Deployed AI Engineer (GenAI, AWS)

Provectus • New York, NY

22h • Remote

About The Position

Provectus is hiring a hands-on senior engineer to embed with client teams and build production AI systems that improve measurable business outcomes. The company partners with enterprises in Financial Services & Insurance and Healthcare & Life Sciences, using bespoke applications, managed services, advisory engagements, and pre-built AI Blueprints. The role begins by spending two to four weeks performing the customer’s work—such as underwriting, claims processing, or revenue-cycle operations—to understand operational constraints firsthand. Working with the operator and a Forward Deployed Executive, the engineer then redesigns the function and builds the solution.

The engineer is expected to own delivery from domain learning and evaluation design through production deployment and adoption. Work includes building GenAI applications, agentic workflows, retrieval and structured-extraction pipelines, supporting services, data pipelines, and evaluation harnesses. Systems are deployed primarily on AWS and must be observable, maintainable, and suited to the customer’s environment. The engineer also contributes lessons from engagements back to Provectus’s industry Blueprints and shares accountability for the Business Unit’s KPIs. This is an autonomous, customer-embedded role for an experienced technical leader who wants to remain hands-on in production code.

Requirements

• At least 8 years of software-building experience, with a substantial portion spent writing production code for which the candidate was accountable.
• Currently hands-on and committed to remaining hands-on in production engineering.
• Willingness to spend weeks performing an operator’s work before beginning software development.
• Ability to learn unfamiliar business functions quickly and engage substantively with domain practitioners.
• Experience shipping GenAI/LLM systems to production, including addressing challenges beyond the prototype stage.
• Experience building or owning an evaluation suite for a non-deterministic system and explaining what was measured and why.
• Strong engineering fundamentals and ability to become productive in unfamiliar codebases or languages.
• Proficiency in Python and/or TypeScript.
• Cloud-native delivery experience on AWS, including containers, Kubernetes or ECS, infrastructure as code, CI/CD, and operational handover; GCP or Azure experience is also relevant.
• Credibility in conversations with senior business stakeholders and CTOs.
• Comfort with ambiguity, autonomy, and ownership in engagements that begin underspecified.
• Solid AI/ML foundations and ability to reason about model capabilities and failure modes.
• Strong hands-on production experience with Claude Code/Cowork.
• Fluent written and spoken English.

Nice To Haves

• Prior experience as a founder, CTO, or engineering leader who has returned to individual-contributor work.
• Deep experience in financial services, insurance, healthcare, or asset management.
• Consulting, professional services, or other embedded customer-facing delivery experience.
• Data platform experience with data lakes, warehouses, streaming and real-time analytics, data mesh, data contracts, governance, or data quality.
• MLOps or classical ML experience, including PyTorch, SageMaker, or MLflow.
• Experience with fine-tuning, distillation, or inference and serving optimization.
• Graph database experience, such as Neo4j or AWS Neptune.
• Infrastructure-as-code depth with AWS CDK, CloudFormation, or Terraform.
• Open-source contributions or public writing about applied AI.

Responsibilities

• Spend two to four weeks at the start of an engagement performing the customer’s operational work and learning the function from the inside.
• Reach working fluency in unfamiliar business domains quickly, including insurance underwriting, healthcare revenue cycle, and asset-flow processes.
• Work with operators and a Forward Deployed Executive to redesign business functions from first principles.
• Build and ship production GenAI systems, including LLM applications, agentic workflows, retrieval and structured-extraction pipelines, and supporting services.
• Build evaluation harnesses, define success measures, instrument systems, and use evaluation results to guide design.
• Write production code across backend services, data pipelines, and AI systems, primarily using Python and TypeScript.
• Deploy systems to AWS, or to GCP/Azure where required by the customer, using containerized, observable, and maintainable approaches.
• Contribute field learnings to Provectus’s industry Blueprints so future engagements can build on them.
• Work alongside a Forward Deployed Executive and share accountability for Business Unit KPIs.
• Drive system adoption and treat change management as part of the engineering work.
• Communicate credibly with customer engineers, operators, and executives, and challenge assumptions when needed.
• Help shape engagement commitments and solutions before work is committed.

Benefits

• Base salary up to USD 200,000 and OTE up to USD 250,000.
• Unlimited PTO policy.
• 401(k) profit-sharing plan after a three-month probation period.
• Frontier delivery work across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare.
• Opportunity to shape how leading enterprises adopt AI, from strategy through first deployment.
• Work in small, senior forward-deployed teams alongside Principal Architects and Forward Deployed Engineers.
• Opportunity to help build tooling and frameworks in a growing AI delivery practice.
• Remote-friendly culture.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed