Forward Deployed Engineer (AI Solutions) - Atrix

At Atrix, our journey began with a simple belief:
Breakthrough medicines and technologies change lives, and the people making them deserve better tools.

We often celebrate the final moment: a patient receiving a life-saving therapy or a groundbreaking treatment becoming standard of care.
But behind that moment is a complex, coordinated effort that begins years earlier.

Pharmaceutical and med device companies shoulder this responsibility every day:

• Advancing science from lab to clinic

• Navigating regulatory and access barriers

• Ensuring safe, evidence-based adoption in the real world

They’re not just bringing products to market; they’re shaping the future of care.

Yet these organizations are often held back by outdated workflows and siloed data, unable to fully harness the knowledge that already exists across their teams.

Atrix was built to change that.

We exist to support the mission of those who dedicate their lives to creating and delivering innovations that impact global health.

As a Forward Deployed Engineer, you will sit at the intersection of engineering, implementation, and customer value. You’ll partner directly with enterprise pharma and biotech teams to turn complex scientific workflows into reliable, AI-powered systems that accelerate evidence generation, medical strategy, commercial insights, and patient impact.

You will become the technical owner of several key customer accounts, embedding deeply into their workflows, translating their needs into structured requirements, configuring Atrix’s AI-native platform, and ensuring accuracy, trust, and real-world reliability.

This is one of the most impactful roles at Atrix.
You’ll see your work used daily by medical, clinical, and commercial teams making high-stakes decisions.

You’ll work closely with our Engineering Team and CEO, and collaborate as a peer to product, design, and GTM leadership. As one of our earliest FDEs, you’ll help define technical architecture, influence product strategy, and set the tone for future engineering hires.

💡 This is an hybrid role based in NYC (ability to be in office is required), with flexibility for remote work on some days as needed.

This role is perfect for someone who is customer-obsessed, technically fluent, and thrives in fast-moving startup environments. If you love the challenge of translating AI workflows into intuitive product experiences in a high-stakes industry, we want to talk to you.

• Configure Atrix templates, pipelines, and AI workflows to match complex scientific and medical processes

• Set up and validate customer-approved data sources

• Ensure accuracy, reliability, and trust in AI-generated outputs

• Drive the full implementation lifecycle: onboarding → configuration → validation → go-live → iteration

• Lead weekly customer calls and serve as the primary technical point of contact

• Build quick prototypes and workflow experiments for GTM initiatives

• Translate customer needs into clear product requirements

• Triage bugs, uncover feature gaps, and partner with engineering to implement fixes or enhancements

• Shape product roadmap with insights drawn from real-world usage

• Own business-sense QA and accuracy validation for customer deployments

• Identify risk, propose guardrails, and define scalable validation processes

• Enable AI evals to ensure high trust and quality of all workflows

• Create internal SOPs for deployment, QA, template configuration, and customer onboarding

• Own 3–5 enterprise accounts end-to-end within 6 months

• Identify patterns across accounts and surface scalable templates or product opportunities

• Become a trusted technical advisor to medical, clinical, and commercial stakeholders

Must haves

• 2–5 years in forward deployed engineering, software engineering, solutions engineering, technical consulting, ML implementation, data engineering, or adjacent roles

• CS degree is required if non-software engineering role held in past.

• Strong Python experience; comfortable doing light FE work in React/TS

• Ability to write evals and optimize Ai-driven workflows.

• Ability to translate complex technical ideas to a smart, non-technical scientific audience

• Experience working with LLMs, prompt engineering, or AI-native tools (e.g., Claude code, Cursor)

• Obsession with accuracy, reliability, and the details that matter in high-stakes workflows

• Thrives in customer-facing environments and enjoys owning outcomes, not just tasks

• Startup experience strongly preferred

Nice to haves

• Background in life sciences, healthcare, or real-world data

• Data science experience

• Work experience at healthcare AI startups or technical consulting firms

• Experience deploying AI in regulated or enterprise settings

🚀 Mission-Driven Impact
Your work will help life sciences teams deliver the right treatment to the right patient—faster. Real-world clinical outcomes start with better tools, and you’ll be building them.

👨‍⚕️ Customer-Centric & High-Stakes
You won’t be building in a vacuum. You'll work directly with top-10 pharma companies to understand how AI can transform medical workflows—this is high-impact, high-visibility work.

🧱 End-to-End Ownership
Own major parts of the stack, shape technical architecture, and influence product direction from day one.

🌱 Early Stage, High Growth
We're small and moving fast. You’ll help shape both the technology and the culture as we scale.

🧠 Tech Meets Trust
Design AI-native workflows that scientific and medical teams trust and depend on daily.

📈 Clear Growth Path
Opportunity to grow into a Lead Frontend or Fullstack Tech Lead role as we expand the engineering team.

💪 Health & wellness support – Stipend + medical (vision, dental, health) insurance coverage
🌴 Unlimited PTO – Recharge when you need to

Instead of a traditional cover letter and resume, we’d like you to complete a short task to show how you work:

Use an AI tool (ChatGPT, Claude, Gemini, etc.) to generate 3–5 short, fake customer interaction notes.
These should look like quick snippets from a customer support chat (e.g., a frustrated user, a neutral inquiry, a positive message).

Using the same AI tool, create:

This should include:

• The sentiment categories you choose (e.g., Positive, Neutral, Negative).

• Short definitions for each category.

• 1–2 criteria the evaluator/model should look for.

• How you used the AI tool.

• What prompts you wrote.

• Any challenges you encountered (e.g., model over-explaining, unclear sentiment boundaries).

Send us your:

• Customer interaction notes

• Sentiment rubric (checklist)

• LLM usage notes

These can be in a Google Doc, Word Doc, or PDF.