Forward Deployed AI Architect (GenAI, AWS)

About the Role

We are representing a confidential AI consulting organization that embeds senior engineers inside client operations to rebuild critical business processes using applied AI and agentic systems. This is not a traditional consulting engagement—you will join client teams as an owner, learn their work from the inside, and ship production systems that move measurable business outcomes.

As a Forward Deployed AI Architect, you'll spend your first weeks in each engagement doing the operator's job—underwriting policies, processing claims, managing revenue cycles—before writing a single line of code. You'll then sit with that operator and leadership to redesign the function from first principles, and you'll be the engineer who builds it.

This role is for experienced engineers who have led teams or companies but want to stay hands-on while owning real outcomes. You'll work primarily in Financial Services and Healthcare verticals, delivering production GenAI systems on AWS that are measured against business KPIs, not scope documents.

Responsibilities

• Take the operator's seat for 2-4 weeks at engagement start—do their job to learn constraints that never make it into requirements docs
• Reach working fluency in unfamiliar business functions (insurance underwriting, healthcare revenue cycle, asset management) in weeks
• Redesign business processes collaboratively with operators and executives, collapsing discovery and solution design into one conversation
• Ship production GenAI systems—LLM applications, agentic workflows, retrieval pipelines, structured extraction—into client AWS environments
• Build evaluation harnesses before features; instrument systems against business KPIs and let evals drive design decisions
• Write production code across the stack in Python and TypeScript; deliver containerized, observable systems on AWS (GCP/Azure when required)
• Own adoption and change management as part of the engineering role—systems the business routes around have not shipped
• Work paired with an executive who carries the Business Unit's metrics; your work is measured against the same number
• Shape engagement scope before commitments are made; you have the standing because you're accountable for delivery

What We're Looking For

Required:

• 8+ years building software with substantial time writing production code you were accountable for—you are hands-on today
• Genuine willingness to spend weeks doing unfamiliar operational work (claims, underwriting, clinical workflows) before engineering—if you need to stay in the IDE, this isn't the role
• Demonstrated ability to become conversant in new business domains fast enough to credibly challenge domain experts
• Shipped GenAI/LLM systems to production—not demos or notebooks—and handled the parts that get hard after prototypes work
• Built or owned evaluation suites for non-deterministic systems; can explain what you measured and why
• Strong engineering fundamentals—productive when dropped into unfamiliar codebases or languages; proficiency in Python and/or TypeScript
• Cloud-native delivery on AWS: containers, Kubernetes/ECS, infrastructure-as-code, CI/CD, operational handoff to other teams
• Credible with senior stakeholders—can hold redesign conversations with business leaders and technical scoping with CTOs without losing the room
• Comfort with ambiguity and ownership—engagements start underspecified by design; closing that gap is the job
• Solid AI/ML foundations—understand model capabilities and failure modes well enough to reason about system design, not just API calls
• Strong hands-on production experience with Claude Code or similar agentic coding tools
• Fluent English, written and spoken

Preferred:

• Prior experience as founder, CTO, or engineering leader who has chosen to return to individual contribution
• Real depth in Financial Services, Insurance, Healthcare, or Asset Management
• Consulting, professional services, or embedded customer-facing delivery experience
• Data platform depth: data lakes, warehouses, streaming analytics, data mesh, governance
• MLOps and classical ML: PyTorch, SageMaker, MLflow
• Fine-tuning, distillation, or inference optimization experience
• Graph databases (Neo4j, AWS Neptune)
• IaC depth: AWS CDK, CloudFormation, Terraform
• Open-source contributions or public writing on applied AI

How We Work with You

Candidates apply through Get A Job.ai. Our recruiting team will conduct an initial screening to understand your background and what you're looking for. If there's a strong match, we'll coordinate interviews with our client, which include live engineering sessions using real problems in your own editor, plus a redesign exercise where you'll work through an unfamiliar business function.

Once you're selected, we handle placement, onboarding coordination, and ongoing support. Do not contact the client directly—all communication flows through Get A Job.ai to protect both your candidacy and our client relationship.

Pay

The client's published range for this role is $150,000-$180,000 base with performance-based bonuses. This is a full-time or B2B contract role with unlimited vacation, health/vision/dental insurance, and 401(K) matching. Final compensation is determined through interviews and evaluation of your experience, skills, and market alignment.

Get A Job.ai is an equal opportunity recruiter. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.