AI Engineer - Forward Deployed

Responsibilities

• Translate complex scientific and operational requirements into a clear delivery roadmap, from initial discovery through scaled production deployment.
• Be embedded with R&D teams, understand their research workflows deeply, and drive & own the value creation that Edison delivers to our partners.
• Map the customer's scientific and operational landscape to identify where AI agents can have the most impact – not just where they ask for help, but where the real leverage is.
• Design, implement, and iterate on production-ready integrations in fast cycles, often owning features end-to-end from architecture to rollout.
• Troubleshoot and debug issues in real time, ensure reliability and adoption, and be the go-to technical contact for AI within the client organization.
• Capture pain points, unmet needs, and product gaps and work with our internal Applied AI and engineering teams to shape future capabilities.
• Partner with GTM and account executives to scope engagements, define success metrics, and support pre-sales technical evaluation.

Requirements

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