Senior Application Support Engineer – AI Products & Agents

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 Organization

Technology at Lilly builds and maintains capabilities using pioneering technologies like 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. Job Title: Senior Application Support Engineer – Operations Job Level: R2 Role Summary

Senior Application Support Engineer – Operations, Reliability & AI Platforms

About the Role

As a Senior Application Support Engineer – Operations, Reliability & AI Platforms , you will provide advanced technical support for a suite of products, acting as the escalation point for L2 support and customer queries. You will troubleshoot, diagnose, and resolve incidents related to application functionality, integrations, performance, and security, collaborating closely with development and cross-functional teams to deliver timely fixes and ensure product quality.

What You'll Be Doing

• Provide advanced technical support for a suite of products, acting as the escalation point for L2 support and customer queries.

• Troubleshoot, diagnose, and resolve incidents related to application functionality, integrations, performance, and security.

• Collaborate with development teams (frontend, backend, full stack) to analyse root causes, reproduce issues, and deliver timely fixes or workarounds.

• Monitor application health, logs, and alerts using tools such as AWS CloudWatch, Winston, or similar.

• Maintain and update knowledge base articles, FAQs, and runbooks for recurring issues and resolutions.

• Support deployment activities, including post-release validation and rollback procedures.

• Participate in incident management, including RCA (Root Cause Analysis), documentation, and communication with stakeholders.

• Ensure compliance with internal standards and external regulations (e.g., GDPR, HIPAA, as relevant).

• Contribute to continuous improvement of support processes.

• Collaborate cross-functionally with Product, QA, Engineering, Platform, and Operations teams to drive product quality and customer satisfaction.

• Support cloud-native and distributed application environments across AWS, Azure, and GCP platforms.

• Drive operational excellence through automation, monitoring, observability, and reliability engineering practices.

• Support AI-powered applications, Generative AI solutions, chatbots, copilots, and agent-based systems running in production environments.

• Troubleshoot and resolve incidents related to AI platforms, LLM integrations, MCP servers, vector databases, retrieval services, and AI orchestration workflows.

• Support deployment, monitoring, performance tuning, and operational stability of AI-enabled applications and services.

• Participate in operational readiness reviews, disaster recovery planning, capacity management, and production support activities for AI workloads.

How You Will Succeed

• Demonstrate strong analytical and problem-solving skills, with hands-on experience in debugging web applications (frontend and backend).

• Utilise monitoring, logging, and alerting tools (e.g., AWS CloudWatch, Winston, Datadog, ELK, Splunk, Grafana, Prometheus).

• Work effectively with ticketing systems (e.g., Jira, ServiceNow) and incident management workflows.

• Apply good understanding of RESTful APIs, databases (PostgreSQL, Redis), and cloud platforms (AWS, Azure, GCP).

• Support CI/CD pipelines and deployment processes.

• Use scripting skills (e.g., Bash, Python, JavaScript, PowerShell) for automation and troubleshooting.

• Communicate and collaborate effectively across teams.

• Apply DevOps and Site Reliability Engineering (SRE) practices to improve application reliability, scalability, and operational efficiency.

• Demonstrate understanding of AI application operational support, including monitoring, troubleshooting, observability, and incident management.

• Troubleshoot issues involving Large Language Models (LLMs), AI agents, MCP integrations, AI APIs, prompt orchestration, and retrieval pipelines.

• Support AI application deployments through CI/CD pipelines and automation frameworks.

• Monitor AI service reliability, latency, throughput, failure rates, token consumption, and operational health metrics.

• Implement automation to improve incident response, operational efficiency, and platform reliability.

What You Should Bring

• 4-6 years of experience in application support, technical troubleshooting, DevOps, Site Reliability Engineering (SRE), or software engineering.

• Experience supporting products in regulated industries (Life Sciences, Healthcare, Financial Services, etc.).

• Familiarity with frontend frameworks (React, Material-UI) and backend technologies (Node.js, Express.js).

• Knowledge of security best practices and compliance requirements.

• Exposure to Agile methodologies and SDLC.

• Experience with knowledge base management and documentation.

• Interest in continuous learning and process improvement.

• Bachelor's degree in Computer Science, Engineering, or related field (or equivalent practical experience).

DevOps & Operations Skills

• Strong understanding of CI/CD pipelines and deployment automation tools such as GitHub Actions, Azure DevOps, Jenkins, GitLab CI/CD, or similar.

• Experience with Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or Bicep.

• Understanding of containerization and orchestration technologies such as Docker and Kubernetes.

• Knowledge of application monitoring, observability, alerting, logging, and troubleshooting methodologies.

• Experience supporting production systems in cloud environments.

• Familiarity with release management, change management, incident management, and problem management processes.

• Knowledge of high availability, disaster recovery, backup, failover, and resilience engineering concepts.

AI & Emerging Technology Skills

• Working knowledge of Generative AI and Large Language Model (LLM) ecosystems.

• Understanding of AI architecture patterns, including:

• LLM-based Applications

• Retrieval-Augmented Generation (RAG)

• AI Agents and Multi-Agent Systems

• Prompt Engineering

• Vector Databases and Semantic Search

• AI Service Integration Patterns

• Agentic Workflows and Orchestration Frameworks

• Familiarity with Model Context Protocol (MCP), MCP Server architecture, MCP Clients, Tool Calling, and Enterprise AI integrations.

• Understanding of AI observability, monitoring, tracing, evaluation, and operational support practices.

• Exposure to Azure OpenAI, AWS Bedrock, Google Vertex AI, Azure AI Serv