Senior Forward Deployed AI Architect (GenAI, AWS)

Provectus•New York, NY

2d•$150,000 - $180,000•Remote

About The Position

Provectus is a Premier AWS partner and an Anthropic Strategic Partner focused on applied AI, helping enterprises leverage technologies like Claude and agentic systems to achieve measurable business outcomes. We work with clients globally, specializing in Financial Services & Insurance and Healthcare & Life Sciences. Our approach involves deploying pre-built AI Blueprints that rebuild critical business processes. As a Forward Deployed Architect (FDA), you will embed within client operations to understand their work firsthand, ship bespoke AI systems, and own the outcomes. This role emphasizes deep immersion in the client's operational reality, moving beyond traditional requirements gathering to hands-on problem-solving and system building. You will be responsible for delivering tangible business results, measured by the impact on the client's business unit metrics.

Requirements

8+ years of software building experience, with a significant portion in writing production code for which you were accountable.
Hands-on current coding ability and intent to remain so.
Willingness to spend weeks performing an operator's job (e.g., claims processing, underwriting, revenue-cycle work) before writing code.
Demonstrated ability to quickly learn and become conversant in unfamiliar business functions.
Experience shipping GenAI/LLM systems to production, including handling post-prototype challenges.
Experience building or owning an evaluation suite for non-deterministic systems.
Strong engineering fundamentals, enabling productivity in unfamiliar codebases or languages.
Proficiency in Python and/or TypeScript.
Cloud-native delivery experience on AWS (GCP/Azure is a plus), including containers, Kubernetes/ECS, IaC, CI/CD, and operational realities.
Credibility with senior stakeholders, capable of holding technical and scoping conversations.
Comfort with ambiguity and a strong sense of ownership.
Solid AI/ML foundations, understanding model capabilities and failure modes.
Strong hands-on production experience with Claude Code/Cowork.
Fluent English, written and spoken.

Nice To Haves

Prior experience as a founder, CTO, or engineering leader who has returned to individual contribution.
Deep expertise in financial services, insurance, healthcare, or asset management.
Experience in consulting, professional services, or other embedded customer-facing delivery roles.
Data platform expertise: data lakes, warehouses, streaming analytics, data mesh, data contracts, governance, and data quality.
MLOps and classical ML experience: PyTorch, SageMaker, MLflow.
Experience with fine-tuning, distillation, or inference/serving optimization.
Experience with graph databases (Neo4j, AWS Neptune).
IaC depth: AWS CDK, CloudFormation, Terraform.
Open-source contributions or public writing on applied AI.

Responsibilities

Embed within client operations to understand and perform the operator's job for several weeks at the start of an engagement.
Gain working fluency in new business domains such as insurance underwriting or healthcare revenue cycle management.
Collaborate with operators and Forward Deployed Executives to redesign functions from first principles.
Build and ship production GenAI systems, including LLM applications, agentic workflows, and retrieval/extraction pipelines, into customer environments.
Develop and implement evaluation harnesses to measure system performance against business KPIs.
Write production code across the full stack, including backend services, data pipelines, and AI layers, using Python and TypeScript.
Deploy containerized, observable, and maintainable systems on AWS (or GCP/Azure as required).
Contribute learnings from field engagements back into Provectus's industry blueprints.
Own the outcome of engagements, working with a Forward Deployed Executive to drive adoption and achieve business KPIs.
Manage change within the client organization as part of the engineering job.
Engage credibly with customer engineers, operators, and executives, and be willing to challenge assumptions.
Shape and influence client commitments based on build feasibility and impact.