Join us in Dublin as part of JPMorganChase’s Employee Platforms technology organization, where you’ll help shape the future of work for over 300,000 employees. You’ll have the opportunity to build impactful AI solutions, collaborate with talented teams, and grow your career in a dynamic engineering hub. We value creativity, reliability, and a passion for delivering measurable results. Your expertise will help us integrate advanced AI capabilities into enterprise platforms, improving productivity and employee experience. Discover a place where your skills and ideas can make a real difference.
Job Summary: As an Applied AI / ML Lead Software Engineer in the Employee Platforms Data Team, you will design, build, and operate agentic AI and LLM-powered workflows that drive operational excellence. You will work closely with end-user services, ensuring solutions are reliable, secure, and aligned with firm standards. Your role will focus on integrating AI safely into enterprise platforms, collaborating across disciplines, and contributing to platform standards. You will help foster a culture of innovation and continuous improvement within the team.
Job Responsibilities:
- Design and deliver LLM-powered applications that support employee platforms and operational use cases
- Build and maintain agentic AI workflows, including tool use, planning, structured outputs, and safety controls
- Create and operationalize MCP servers/tools for secure agent interactions with internal services and data sources
- Develop evaluation strategies for LLM systems and drive performance improvements through experimentation
- Productionize models and AI services, including packaging, deployment, scaling, and observability
- Implement monitoring for model and system health, and define operational SLOs/SLAs
- Build CI/CD pipelines and automated testing for data, ML, and LLM systems
- Ensure solutions meet governance requirements, including documentation, controls, and compliance
- Build and maintain data pipelines and feature/retrieval layers to support AI use cases
- Partner with product owners, platform engineering, SRE, security, and data stakeholders to integrate AI capabilities
- Contribute to platform standards, reusable components, and best practices for AI engineering
Required Qualifications, Capabilities, and Skills:
- Demonstrate strong Python engineering skills for production-grade code, testing, and performance tuning
- Deliver LLM-enabled applications and apply agentic AI patterns, including tool use, orchestration, and guardrails
- Build and operate MCP integrations reliably
- Apply solid software engineering fundamentals, including version control, code review, CI/CD, and secure development
- Utilize at least one ML/AI ecosystem such as PyTorch, TensorFlow, scikit-learn, or MLflow
- Deploy and operate workloads on AWS, including compute, storage, IAM, and networking fundamentals
Preferred Qualifications, Capabilities, and Skills:
- Model and optimize data with PostgreSQL
- Use Infrastructure as Code with Terraform for repeatable environments
- Apply strong CI/CD experience with tools like GitHub Actions or Jenkins
- Work with distributed data processing and lakehouse patterns, such as Apache Spark or Databricks
- Leverage developer productivity tools like Claude Code and GitHub Copilot responsibly
- Collaborate on end-user services, including VDI, application delivery, and enterprise tooling
- Consider operational constraints and user experience in solution design
Why Join Us? You will be part of a collaborative, innovative team that values secure-by-design and reliable engineering. Your work will directly impact employee productivity and operational efficiency, offering opportunities for growth and meaningful contributions.