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AI Engineer - Forward Deployed

Job in New York, New York County, New York, 10261, USA
Listing for: Edison Scientific
Full Time position
Listed on 2026-07-08
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 200000 - 350000 USD Yearly USD 200000.00 350000.00 YEAR
Job Description & How to Apply Below
Location: New York

About

Edison Scientific builds and commercializes AI agents for science. Scientific discovery moves too slowly, and autonomous AI agents are how we intend to fix that. We're assembling a team of top researchers and engineers across AI and biology to build an AI scientist.

Role

As a Forward Deployed AI Engineer, you'll be embedded directly with leading scientific R&D organizations across pharma and biotech – taking full ownership of how Edison's AI agents create value in their environment. You will deeply understand their science, their workflows, and their pain points, then determine where our platform can have the most impact. This isn't remote support or implementation consulting.

You'll be on-site and on the front lines, owning integrations, reliability, relationship cadence, and the product feedback loop end to end. You will build relationships with scientists and research leaders, identify the highest-leverage problems, and ship solutions quickly. You'll operate with a high degree of independence and serve as the bridge between what our platform can do and what the customer needs it to do, feeding insights back to our product and engineering teams to shape the roadmap.

While we don’t require you to have a scientific background, we expect our engineers to be deeply curious about science and to be excited to build and drive value for our partners.

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 Type Script/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…
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