Senior Forward Deployed AI Engineer, GenAI, AWS

🕒 July 27

🏖️ New Jersey, North Carolina, +1 more states – Remote

🏖️ New Jersey – Remote 🌲 North Carolina – Remote ⚔️ Virginia – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

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Provectus

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2012

💼 Consulting

🏥 Healthcare

🏭 Manufacturing

Consulting • Healthcare • Manufacturing

Provectus is an artificial intelligence consultancy and solutions provider that helps businesses transform through AI. Offering both a use case and a platform approach, Provectus integrates AI into organizations to achieve unique business objectives and technical capabilities. Their solutions are cloud-native, vendor-agnostic, and open, allowing for deployment in customer's cloud without restrictive licenses. With applications in industries like retail, manufacturing, and healthcare, Provectus delivers AI-powered use cases and turnkey solutions to drive innovation and efficiency. They also offer consulting, customization, and managed AI services.

📋 Description

• Provectus is a Premier AWS partner and an Anthropic Strategic Partner at the forefront of applied AI, helping enterprises turn Claude, agentic systems, and their own data into measurable business outcomes through bespoke applications, managed services, and advisory engagements. • Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. • We embed engineers and leaders inside client operations as Forward Deployed Engineers (FDE) and Forward Deployed Executives (FDX) — people who learn the work, ship the system, and own the outcome. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Bluprints. • You will do the customer’s job before you automate it. • Most AI engagements fail the same way: someone gathers requirements, someone writes a PRD, and a team ships a workflow nobody uses. We think the requirements-gathering step is the bug. So we remove it. • A Forward Deployed AI Engineer at Provectus spends the first weeks of an engagement in the operator’s seat — as the underwriter, the analyst, the RCM specialist, the claims clinician, whoever actually does the work we’ve been asked to change. You do the job. You learn the constraints from the inside, the ones nobody writes down. Then you sit at a table with that operator and a Forward Deployed Executive and rebuild the function from first principles — and you are the one who builds it. • Three things define how you work: • - Embedded, not engaged. You are part of the customer’s team and inside their process — not a vendor running a project alongside it. • - Real tasks, not scope. You are not fenced into a siloed deliverable. You go where the operating problem is. • - Autonomous. Embedded is not staff-augmented. You own the method; nobody hands you a ticket. • You won’t start from zero. Provectus builds industry blueprints — working systems that have already shipped for a customer in your industry. Your engagement starts from that baseline, and what you learn in the field goes back into it. That loop is the difference between an outcome and an invoice. • You’ll be measured on whether the Business Unit’s number moved — not on hours, not on scope delivered. • This is a role for engineers who have led before — as a founder, a CTO, a staff engineer — and who want to stay in the code while owning the outcome. On most days you’ll be the most senior technical person in the room, and you’ll still be the one shipping.

🎯 Requirements

• 8+ years building software, a substantial share of it writing production code you were accountable for. You are hands-on today and intend to stay that way. • You will take the operator’s seat. You are genuinely willing to spend weeks doing someone else’s job — claims processing, underwriting, revenue-cycle work — before you write a line of code. Engineers who need to stay in the IDE should not apply. • You learn domains fast. Demonstrated ability to become conversant in an unfamiliar business function quickly enough to argue with the people who do it for a living. • Shipped GenAI/LLM systems to production — not demos, not notebooks. You’ve handled the parts that get hard after the prototype works. • You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured and why. • Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack. • Cloud-native delivery on AWS (GCP/Azure a plus): containers, Kubernetes/ECS, IaC, CI/CD, and the operational reality of a system someone else inherits. • Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO without losing either room. • Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job. • Solid AI/ML foundations — you understand what the models do well enough to reason about failure modes, not just call the API. • Strong hands-on production experience with Claude Code/Cowork. • Fluent English, written and spoken. • Nice to have: • Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution. • Real depth in one of our blueprint industries: financial services, insurance, healthcare, asset management. • Consulting, professional services, or other embedded customer-facing delivery. • Data platform depth: data lakes, warehouses, streaming and real-time analytics, data mesh and data contracts, governance and data quality. • MLOps and classical ML: PyTorch, SageMaker, MLflow. • Fine-tuning, distillation, or inference/serving optimization. • Graph databases (Neo4j, AWS Neptune). • IaC depth: AWS CDK, CloudFormation, Terraform. • Open-source contributions or public writing on applied AI.

🏖️ Benefits

• Frontier delivery work across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare • The chance to shape how leading enterprises adopt AI, from strategy through first deployment • A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers • A growing AI delivery practice where you help build the tooling and frameworks, not just use them • Remote-friendly culture