Advisor - Software Engineer
Indexed description
Job Description
About the Technology Organisation
Technology at Lilly builds and maintains capabilities using pioneering technologies like the most prominent tech companies. What differentiates Technology at Lilly is that we create new possibilities through tech to advance our purpose – creating medicines that make life better for people around the world, like data-driven drug discovery and connected clinical trials. We hire the best technology professionals from a variety of backgrounds, so they can bring an assortment of knowledge, skills, and diverse thinking to deliver solutions in every area of our business.
About The Business Function
The Software Product Engineering (SPE) team is a specialised engineering group that delivers strategic solutions and differentiated capabilities. We take a forward-thinking approach, focusing on an enterprise platform and product mindset, ensuring that the solutions we build can be leveraged across Technology teams for broader impact and efficiency.
Role Summary
As a Advisor Software Engineer (R5), you are a recognised technical authority who shapes the engineering direction of the SPE organisation. You combine deep, hands-on expertise in system design and distributed architecture with a forward-looking AI-first mindset – designing and building agentic AI systems, intelligent automation pipelines, and next-generation software platforms. You are the go-to person when teams face their hardest technical challenges, and you translate that expertise into scalable, production-grade solutions that drive measurable business outcomes across multiple functions.
This is a high-impact, hands-on technical leadership role. You will architect end-to-end systems, write production code, champion AI-driven development practices, and influence engineering culture across teams – all while mentoring and coaching engineers to raise the overall technical bar.
What You’ll Be Doing
System Design & Architecture
- Own end-to-end system design of large-scale, distributed, cloud-native platforms – from API contracts and data models to deployment topology and observability.
- Define and enforce architectural standards and patterns (microservices, event-driven, serverless, CQRS) and lead architecture reviews, ADRs, and technical blueprints.
- Design for resilience, scalability, security, and cost-efficiency on cloud platforms (AWS preferred; GCP/Azure acceptable).
- Drive decomposition of monolithic and COTS systems into modern, maintainable, in-house services and platform capabilities.
- Write production-quality code across the stack using modern languages and frameworks (e.g., Python, JavaScript/TypeScript, Go, Java, Rust, or equivalent) on both frontend and backend.
- Build and optimise APIs (RESTful, GraphQL), real-time communication layers, and high-throughput data pipelines with appropriate database technologies (relational, NoSQL, or columnar).
- Champion code quality through rigorous reviews, test-driven development, and CI/CD automation. Apply DevSecOps principles end-to-end.
- Architect and build agentic AI systems that autonomously execute multi-step workflows – leveraging LLM orchestration frameworks (LangChain, LangGraph, CrewAI, or equivalent), tool-use patterns, and retrieval-augmented generation (RAG).
- Design AI-native architectures that embed intelligence into products: context-aware assistants, automated decision support, and self-healing infrastructure.
- Demonstrate mastery of prompt engineering, model evaluation, and responsible AI practices. Leverage AI-assisted development tools (GitHub Copilot, Claude, Cursor) and set the standard for the team.
- Evaluate emerging AI technologies (foundation models, multi-modal AI, MCP, A2A protocols) and drive adoption where they create measurable value.
- Act as the technical conscience across multiple teams and functions – challenging the status quo and providing recommendations to improve processes, tooling, and practices.
- Coach engineers at all levels, sharing specialised knowledge in architecture, AI, and software craftsmanship. Represent SPE in architecture guilds and technology leadership forums.
- Proven track record designing and delivering large-scale distributed systems in production (microservices, event-driven, serverless architectures).
- Deep expertise in at least one cloud platform (AWS preferred) with infrastructure-as-code (CloudFormation, CDK, Terraform) and containerisation (Docker, Kubernetes). Cloud certifications are a plus.
- Strong knowledge of domain-driven design (DDD), CQRS, API gateway patterns, and system decomposition strategies.
- Strong proficiency in one or more modern programming languages (e.g., Python, JavaScript/TypeScript, Go, Java, Rust) with the ability to work across the full stack.
- Experience building frontend applications with modern frameworks (e.g., React, Angular, Vue) with focus on performance, accessibility, and component-driven design.
- Proficient in backend development with appropriate frameworks and database technologies (relational and/or NoSQL). Strong testing discipline and CI/CD experience.
- Hands-on experience building AI-powered applications: agentic workflows, RAG pipelines, LLM integrations, and prompt engineering at production scale.
- Familiarity with AI orchestration frameworks and foundation model capabilities, limitations, evaluation, and responsible AI principles.
- Demonstrated ability to influence technical direction across multiple teams without direct authority. Excellent communication for architecture documents, ADRs, and standards.
- Strong track record of coaching engineers. A challenger mindset: you question assumptions, propose better alternatives, and drive innovation.
- Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related technical field.
- 16+ years of hands-on software development experience across frontend and backend systems, with at least 4 years in a senior/lead architecture role.
- Strong foundation in computer science fundamentals, data structures, algorithms, and software architecture.
- Effective communication skills with the ability to influence at a cross-functional level. High intellectual curiosity and commitment to continuous learning.
- Experience in regulated industries (e.g., Life Sciences, Healthcare) or familiarity with compliance frameworks (GxP, HIPAA, SOX).
- Contributions to open-source projects, technical publications, or a visible engineering community presence.
- Experience with platform engineering, developer experience (DX) tooling, or multi-modal AI in enterprise contexts.
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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