Atrix
Forward Deployed Engineer (AI Solutions) - Atrix
7mo ago
USARemoteaimachine learningsoftware developmentpython
Work with pharma and biotech teams to implement AI-powered systems accelerating evidence generation and medical strategy.
Responsibilities
- 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.
Requirements
- 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 have
- 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
Conditions
- 🚀 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
Other
- 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.
- We exist to support the mission of those who dedicate their lives to creating and delivering innovations that impact global health.
- 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
- 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.