Senior Forward Deployed Engineer

Overview

Senior individual-contributor role embedded with Digital Engagement Tech@Lilly business, medical and marketing teams to discover problems and build AI-enabled software end to end, from vague problem to live product, then turn learnings into reusable patterns.

What you'll do

• Embed with business, medical and marketing teams to understand their workflows, pain points and constraints first-hand.
• Frame ambiguous problems, decide what is worth building, and be direct about what is not feasible.
• Prototype quickly, put working software in front of users early, and iterate on their feedback.
• Design and build full-stack solutions: responsive front ends, API integrations, Node.js services and the data layer behind them.
• Integrate LLMs, RAG, agents and AI services into products, with evaluation, guardrails and monitoring for quality, latency and cost.
• Own the delivery lifecycle: scoping and estimation, development, automated testing, CI/CD, deployment, monitoring and support handover.
• Work with the technical lead and system custodian to keep what you ship maintainable, observable, and secure.
• Make architectural decisions that improve efficiency and maintain compliance in a regulated space.
• Turn what you learn in the field into reusable components, templates, and reference implementations for cross-functional teams.
• Set and uphold coding standards, review practices and engineering patterns across teams.
• Apply secure-by-design and privacy-by-design principles, and build in traceability, grounding, auditability and human oversight.
• Work with quality, compliance and risk partners so solutions meet regulatory and enterprise requirements, including content review processes.
• Maintain clear architecture, design, and support documentation for everything put into production.
• Provide hands-on technical guidance to developers and engineers, review designs and code, and raise the bar through practical examples.
• Communicate trade-offs, risks and recommendations clearly to both technical and non-technical stakeholders, including senior leaders.
• Bring practical feasibility, scalability, and value considerations into roadmap planning.

What you'll need

• 10+ years of software engineering experience, with a track record of building and shipping production systems end to end.
• 4+ years building customer-facing or business-facing solutions in close partnership with stakeholders, such as forward deployed, solutions engineering, consulting engineering or embedded product engineering roles.
• Expert in HTML5, CSS3, JavaScript/TypeScript and React; strong in responsive design and web standards.
• Strong back-end experience with Node.js (Express, Koa or Hapi) and API design and integration (REST, GraphQL).
• 2+ years of hands-on generative AI delivery: LLMs, prompt and context engineering, RAG, embeddings, agentic workflows, and evaluation of model outputs.
• Working proficiency in Python and SQL, and experience with frameworks such as LangChain, DSPy or Hugging Face.
• Strong experience with unit and integration testing frameworks such as Jest, Mocha, Chai or Jasmine.
• Experience designing, deploying and operating services on a major cloud (AWS preferred), with CI/CD, containers and monitoring.
• Strong system design and architecture fundamentals: version control (GitHub), code reviews, and secure, maintainable, observable code.
• Experience working in Agile teams, including scoping, estimation and backlog ownership.
• Proven ability to turn ambiguous business problems into scalable solutions with measurable value, and to communicate clearly with technical and non-technical audiences.
• Bachelor's degree in computer science, Engineering or a related technical field; equivalent practical experience is considered.
• Demonstrated leadership, teamwork, and collaboration in a professional setting.

Nice to have

• Vue or Nuxt experience.
• Pharmaceutical, healthcare or other regulated-industry experience, including working within content review, privacy and compliance processes.
• Experience with multi-agent systems, tool use, Text2SQL, semantic search, hybrid retrieval, reranking, and LLM evaluation.
• Experience with vector databases, lakehouse platforms (such as Databricks), and enterprise AI platforms (such as SageMaker or Azure ML).
• Experience fine-tuning or adapting models, and optimizing AI systems for quality, latency, throughput and cost.
• Experience with Kubernetes, Docker, GitHub Actions and MLflow, or equivalent LLMOps tooling.
• Experience working across multiple concurrent projects and with stakeholders in different countries and time zones.
• Experience building developer tooling, internal platforms or accelerators that other teams adopt.
• Familiarity with web experience platforms, CMS and content operations.
• A master's degree.

Details

• Location: Bangalore, India.