Forward Deployed AI Engineer

Edison Scientific is looking for a forward-deployed AI engineer to embed on-site with pharma and biotech R&D teams and help translate AI agent work into measurable value end to end. You will drive integration ownership, reliability, and relationship cadence, then feed what you learn back into Edison’s product and roadmap through close collaboration with Applied AI and engineering teams.

This is a full-time Applied AI role based on-site in Boston, NY (onsite). Compensation is USD 200,000 - 350,000 per year with offers equity, plus a benefits package designed to support you and your family.

What you’ll do

• Translate complex scientific and operational requirements into a delivery roadmap, from discovery through scaled production deployment.
• Embed with R&D teams, understand their workflows deeply, and drive value creation for Edison partners by owning delivery outcomes.
• Map the customer’s scientific and operational landscape to identify the highest-leverage opportunities for AI agents, beyond simple “help” requests.
• Design, implement, and iterate on production-ready integrations in fast cycles, sometimes owning features end to end from architecture through rollout.
• Troubleshoot and debug issues in real time, ensuring reliability, adoption, and technical confidence as the primary AI contact for the client organization.
• Capture pain points, unmet needs, and product gaps, then partner with Edison’s internal Applied AI and engineering teams to shape future capabilities.
• Work with GTM and account executives to scope engagements, define success metrics, and support pre-sales technical evaluation.

What you bring

• 2+ years of professional software engineering experience with a track record shipping production-grade software in fast-paced or ambiguous environments.
• Strong proficiency in Python and/or TypeScript/JavaScript, with deep fundamentals.
• Hands-on production experience building and deploying LLM-powered or agentic AI systems, including prompt engineering, RAG pipelines, model evaluation, and orchestration frameworks.
• AI fluency: ability to reason through systems architecture, debug at the infrastructure level, and write clean production code independently without reliance on AI-assisted coding tools.
• Comfortable operating with 20-40% travel (at peak times), making decisions with incomplete information, and driving outcomes without close oversight.
• Proven problem-solving skills: navigate complex systems, debug in real time, and own features end to end.
• Strong communication and relationship-building skills to earn trust with scientists, executives, and engineering teams.
• Deep curiosity and willingness to learn new scientific domains quickly and adapt to shifting priorities.
• Degree in Computer Science, Software Engineering, Mathematics, Physics, or a related technical field, or equivalent demonstrated depth through professional experience.

Relevant technologies

Python, TypeScript, JavaScript, LLM-powered, agentic AI systems, prompt engineering, RAG pipelines, model evaluation, orchestration frameworks.

Compensation and benefits

• Competitive salary and equity (Offers Equity)
• Full healthcare coverage: Edison pays 100% of premiums for you and your dependents
• Yearly new parent stipend and fertility coverage through Carrot
• Mental health support through Rula (in-network therapist and psychiatrist network with fast availability)
• 12 weeks of paid parental leave for maternity, paternity, and adoption
• Pet care support with a yearly employer-funded stipend
• Commuter benefits so you can use pre-tax dollars for transit and parking
• 401(k) company matching
• $300 health and wellness benefit quarterly
• Lunch provided on office days, and dinner provided when working late
• Regular team off-sites and company events

Locations and schedule

• On-site in Boston, NY
• Also available in: San Francisco, Boston, New York; Remote available (U.S. Only)

Bonus points

• Experience in life sciences, pharma, biotech, or scientific R&D (researcher, consultant, or engineer)
• Familiarity with regulated data environments (GxP, HIPAA, 21 CFR Part 11, or equivalent compliance frameworks)
• Background as a technical founder, forward-deployed engineer, or management consultant
• A science degree or research experience alongside engineering skills