Senior Forward Deployed AI Engineer, GenAI, AWS

🕒 July 27

🗽 New York, Massachusetts, +2 more states – Remote

🗽 New York – Remote 🍂 Massachusetts – Remote 🔔 Pennsylvania – Remote ☕ Washington – Remote

💵 $120k - $180k / year

⏰ Full Time

🟠 Senior

🤖 AI Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 16%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

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

• Do the operator’s job for two to four weeks at the start of an engagement. Learn the function from inside, not from a requirements doc. • Reach working fluency in a new domain — insurance underwriting, healthcare revenue cycle, asset flow — in weeks, not quarters. • Sit with the operator and the Forward Deployed Executive and redesign the function from first principles. Discovery, user research, and PRD-writing collapse into one team that re-imagines its own job. You are all three roles. • Ship production GenAI systems into the customer’s environment — LLM applications, agentic workflows, retrieval and structured-extraction pipelines, and the services around them. Running software, not recommendations. • Build the evaluation harness before you build the feature. When the engagement is bound to a business KPI, “it looked good in testing” is not an answer. Define what working means, instrument it, and let the evals drive the design. • Write production code across the stack — backend services, data pipelines, and the AI layer. Python and TypeScript are our centre of gravity; we choose tools to fit the customer, not the résumé. • Take systems to production on AWS (GCP/Azure where the customer requires it): containerized, observable, and maintainable after we leave. • Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from. • Work in a pair with a Forward Deployed Executive who carries the Business Unit’s KPIs. Your work is measured against the same number. • Drive adoption. A system the BU routes around has not shipped. Change management is part of the engineering job here, not a phase after it. • Be credible with the customer’s engineers, their operators, and their executives — and be willing to disagree with all three. • Shape what we commit to before we commit to it. You’ll have the standing to do it, because you’re the one who will build it.

🎯 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.

🏖️ 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

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume