Advisor - Software Engineer - SPE
lilly · India, Hyderabad ·
- Category
- Software engineering
- Experience
- 4+ years
- Company size
- 1000+
lilly · India, Hyderabad ·
At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.
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.
Hands-On Full-Stack Engineering
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.
AI-Driven & Agentic Engineering
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.
Cross-Functional Leadership & Influence
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.
What You Should Bring
System Design & Architecture
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.
Software Engineering
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.
AI & Agentic Systems
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.
Leadership & Influence
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.
Basic Qualifications
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.
Additional Skills / Preferences
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 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 () 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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