AI Engineer - Sr Lead Software Engineer

JPMorganChase is hiring a Senior Lead Software Engineer within the AI/ML Data Platforms organization to help design and deliver agentic AI platforms and LLM-enabled, cloud-native services. This role is hands-on and leadership-focused, with ownership of architecture decisions, production delivery, and improvements to engineering standards across teams.

Based in Jersey City, NJ (onsite), you will partner with engineering and business stakeholders to align priorities, unblock delivery, and bring production-grade rigor to AI application development on AWS.

What you’ll do

• Provide technical guidance and direction by partnering with external teams to align on priorities, unblock delivery, and drive successful engineering outcomes.
• Develop secure, high-quality production code and lead code reviews, including reviewing, debugging, and improving others’ code to raise engineering quality.
• Drive architecture and design decisions affecting product design, application functionality, and technical operations, including SDLC practices.
• Act as a subject matter expert in one or more focus areas, helping teams make sound technical trade-offs and resolve complex problems.
• Evaluate and introduce leading-edge technologies when appropriate, providing clear rationale along with risk and benefit analysis for decision-makers.
• Build and operate production-grade LLM applications, including agentic patterns and tool integrations for enterprise use cases.
• Design and deliver cloud-native services on AWS using containers and serverless architectures, with emphasis on scalability and operational resilience.
• Implement retrieval-augmented generation (RAG) solutions, including embeddings, semantic search, and practical context engineering to improve answer quality and control.
• Build reliable service APIs and integrations with a focus on security, performance, and maintainability.
• Drive adoption and governance of approved AI-assisted engineering practices across teams, including AI-assisted code review and refactoring, test acceleration, release readiness, and incident or root-cause analysis, supported by measurable validation standards (secure coding, peer review, automated testing) and reusable patterns and automation in the SDLC/TLM toolchain.
• Apply knowledge of Software Development Life Cycle toolchain capabilities, including approved AI-assisted development and automation, to increase automation value at scale.

Qualifications

• 5+ years of applied experience, supported by formal training or certification in software engineering concepts.
• Strong Python engineering skills, with experience in PyTorch or TensorFlow.
• Expertise working with vector storage systems and designing memory for agents.
• Experience developing long running agents that run autonomously using tools, skills, and human-in-the-loop workflows.
• Proven production experience deploying LLM-backed services (APIs, microservices).
• Deep MLOps experience including CI/CD, monitoring, incident response, and model governance.
• Cloud-native AI deployment experience on AWS or Azure, including cost and performance optimization.
• Commitment to responsible AI practices and operational excellence.
• Strong communication and collaboration skills working across product, risk, legal, and compliance teams.
• Experience designing and leading adoption of agentic AI-enabled development practices using enterprise-authorized tools, including standards for human-in-the-loop validation, auditability or traceability of changes, and secure handling of sensitive data.
• Strong understanding of responsible AI use and control expectations in engineering workflows, including security and resiliency implications, data sensitivity, and risk-based governance, with influence over senior technical leaders on safe scaling patterns and reuse.

Technologies

• Python, PyTorch, TensorFlow
• Vector storage systems
• LLM-backed services, APIs, microservices
• CI/CD
• AWS, Azure
• Containers, serverless architectures
• Retrieval-augmented generation (RAG), embeddings, semantic search
• SDLC, TLM, model governance

Preferred qualifications

• Experience with fine-tuning, adapters, or custom evaluation frameworks.
• Background operating AI systems in regulated environments (finance, healthcare, etc.).
• Experience with prompt engineering and LLM orchestration.
• Knowledge of safety filters, audit logging, and explainability in production systems.
• Experience mentoring senior engineers and leading architecture discussions.
• Demonstrated ability to influence technical roadmaps and priorities.

Compensation: USD 175,750 - 260,000 per year.