What You’ll Be Doing
Design and build AI-powered applications using Large Language Models, agentic AI workflows, and Retrieval-Augmented Generation (RAG) solutions built on enterprise knowledge sources.
Integrate AI services with business applications and external systems, and continuously evaluate, optimize, and monitor AI application performance and quality.
Build responsive, modern frontend applications and scalable backend services and APIs, using reusable components and clean, maintainable code.
Deploy and manage applications on cloud platforms (preferably AWS), building CI/CD pipelines, containerizing with Docker, and orchestrating workloads with Kubernetes.
Design and manage SQL and NoSQL databases, integrate enterprise systems and third-party services, and ensure secure, compliant handling of data.
Collaborate closely with product teams to translate business requirements into technical solutions, and implement monitoring, logging, and observability best practices.
What You Will Bring
Strong understanding of LLMs, Prompt Engineering, RAG, and Agentic AI concepts, with hands-on experience using frameworks such as LangGraph, LangChain, or LlamaIndex.
Experience integrating AI models through OpenAI, Anthropic, Bedrock, Azure OpenAI, or equivalent services, along with working knowledge of vector databases and semantic search.
Strong proficiency in Python, with experience building APIs using FastAPI, Flask, or similar frameworks, and a solid understanding of microservices architecture and API design.
Practical experience with React and TypeScript, building modern, responsive user interfaces with strong attention to frontend performance and usability.
Hands-on experience with AWS, Docker, and Kubernetes, and CI/CD implementation using GitHub Actions, Jenkins, GitLab, or similar tools, along with infrastructure deployment and environment management experience.
Strong knowledge of relational databases such as PostgreSQL, MySQL, or SQL Server, with experience in NoSQL and vector databases preferred.
How You Will Succeed
Delivers production-ready AI applications with high quality and reliability.
Independently drives features from design through deployment.
Builds reusable and scalable solutions that can support multiple business teams.
Improves developer productivity through automation and engineering best practices.
Continuously explores and adopts emerging AI capabilities to solve business problems.
Basic Qualifications
6-8 years of software engineering experience.
At least 1-2 years of practical Generative AI experience.
Strong Python + React + Cloud background. Proven deployments to production.
Ability to work across the full technology stack independently.
Preferred Skills
Experience building enterprise AI copilots or intelligent assistants.
Experience with Model Context Protocol (MCP) and AI tool integrations.
Experience integrating with collaboration platforms such as Microsoft Teams, Jira, ServiceNow, or similar enterprise tools.
Familiarity with AI observability, evaluations, and monitoring frameworks.
Will this position support sponsorship
No
Travel percentage for this position
0%-10%
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.
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