Lead Software Engineer - Applied AI ML Lead

As a Lead Software Engineer at JPMorganChase within the Enterprise Technology, Infrastructure Platforms team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives., * Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problem.

• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
• Own infrastructure capacity optimization solutions and build predictive/prescriptive models to identify capacity risk, performance bottlenecks, and right-sizing opportunities.
• Design, develop, and productionize GenAI/agentic AI solutions for automation, decision support, and operational workflows, including LLM/SLM apps such as RAG and summarization/extraction.
• Engineer production-grade backend services in Python/Java (REST APIs, microservices, reusable libraries) and own cloud-native data ingestion/processing pipelines for capacity analytics and AI use cases.
• Build prompt engineering assets, routing strategies, and guardrails, and implement automated plus human-in-the-loop evaluation to improve quality.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Apply MLOps best practices across experimentation, versioning, CI/CD, deployment, monitoring, and lifecycle management; implement testing/benchmarking and observability; define success metrics/governance with stakeholders; and mentor engineers to uphold high standards.
• Own and govern the end-to-end AI/ML optimization strategy-from architecture and engineering standards (quality, lifecycle, observability, secure SDLC) through cross-functional execution with SRE/platform/business-to deliver scalable automation, risk reduction, and measurable enterprise outcomes.
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming language(s)
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
• Proficient in all aspects of the Software Development Life Cycle
• Strong hands-on data engineering stack: Apache Spark (batch optimization, partitioning, shuffle tuning, reliability), Apache Airflow (DAG design, backfills, alerting, operational reliability, CI patterns), and Apache Iceberg (schema evolution, partition specs, snapshots, compaction).
• Proven applied AI/ML and GenAI delivery with measurable impact (RAG, extraction, summarization, ranking/classification, copilots, evaluation) and demonstrated ability to lead across teams and influence technical standards and execution.
• Deep distributed systems + production engineering expertise across APIs/microservices, CI/CD, observability, containers/Kubernetes, security, and reliability., * Experience with MCP (Model Context Protocol), Agent Skills, and structured agentic architectures.
• Strong practical usage of AI engineering productivity tooling (for example, GitHub Copilot, Claude Code) in enterprise SDLC environments.
• Familiarity with VSI and Cloud Foundry contexts.
• Advanced Java engineering proficiency in addition to Python.
• Expert-level Python for production systems (packaging, dependency management, performance); strong Java proficiency is a plus.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChase's review of criminal conviction history, including pretrial diversions or program entries. JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.