Lead Software Engineer - AI Application

JPMorganChase; Jersey City (NJ); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorganChase is seeking a Lead Software Engineer in Corporate Technology to architect and implement scalable GenAI applications and agentic AI platforms for finance use cases. You will design cloud-native AWS services, establish observability and security standards, and drive technical decisions across teams to improve reliability, cost, and velocity.

The role requires advanced Python, proven delivery of LLM/agentic systems, and strong leadership to mentor engineers in a regulated enterprise

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Experience architecting and shipping production large language model applications, including agentic workflows and tool integration patterns
• Leading effective use of approved AI-assisted software development tools with the ability to validate AI outputs for correctness, performance, and security
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity and security expectations
• Familiarity with agentic workflows and frameworks (e.g., LangChain, LangGraph, Autogen, CrewAI and A2A)
• Experience building retrieval-augmented generation solutions (embeddings, semantic search, grounding)
• Strong software engineering fundamentals with cloud-native services on AWS
• Advanced python programming skills
• Build systems using frontier models from OpenAI, Anthropic or others on platforms like AWS Bedrock / Vertex AI
• Proven technical leadership skills, mentoring and cross-functional influence
• Hands-on experience with enterprise AI-assisted software development tools and validating AI outputs

Responsibilities

• Lead the architecture and hands-on delivery of scalable, reliable agentic AI platforms for enterprise workflows
• Drives team adoption of enterprise AI practices to improve code quality, delivery speed, and operational outcomes
• Applies knowledge of SDLC tools to improve automation and value
• Design and build production-grade AI systems including agents, skills, memory patterns, guardrails, and tool-use orchestration
• Architect retrieval and context-engineering approaches including embeddings, semantic search and prompt management
• Engineer cloud-native AI services on AWS using containers and serverless designs
• Optimize platform performance across latency, throughput, scalability, caching, context, and cost
• Build APIs and integrations connecting AI to enterprise platforms
• Establish evaluation, experimentation, regression testing, observability frameworks
• Mentor senior engineers and influence engineering direction
• Leverage AI coding assist tools with peer review, automated testing, and secure coding standards

Tools

LangChain

LangGraph

Autogen

CrewAI

A2A

Job description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer at JPMorganChase within Corporate Technology, you will lead the architecture and hands‑on implementation of scalable GenAI Applications and agentic AI platforms for Finance use cases leveraging Firmwide AI tools & platforms. You will design cloud-native solutions, establish evaluation and observability standards, and drive technical decisions across teams to improve reliability, cost, and developer velocity. The candidate will design cloud‑native AWS services and reusable platform capabilities (agents, retrieval/RAG, guardrails, tool orchestration, APIs), while establishing strong evaluation, observability, reliability, security, and cost controls. Ideal candidates have extensive experience, advanced Python, proven delivery of LLM/agentic systems, and technical leadership skills to mentor engineers and drive cross‑team architecture standards in a regulated enterprise environment.

Job Responsibilities

• Lead the architecture and hands‑on delivery of scalable, reliable agentic AI platforms for enterprise workflows
• 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.
• Design and build production‑grade AI systems including agents, skills, memory patterns, guardrails, and tool‑use orchestration
• Architect retrieval and context‑engineering approaches including embeddings, semantic search, grounding, summarization, and prompt/version management
• Engineer cloud‑native AI services on AWS using containers and serverless patterns, event‑driven messaging, and distributed data stores
• Optimize platform performance across latency, throughput, scalability, caching, context efficiency, and cost controls
• Build well‑governed APIs and integrations that connect AI capabilities to enterprise platforms, tools, and business processes
• Establish evaluation, experimentation, regression testing, and observability frameworks to continuously improve quality and agent behavior
• Mentor senior engineers and influence engineering direction through code reviews, architecture forums, and cross‑team technical leadership
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.

Required Qualifications, Capabilities And Skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Experience architecting and shipping production large language model applications, including agentic workflows and tool integration patterns
• 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
• Familiarity with agentic workflows and frameworks (e.g., LangChain, LangGraph, Autogen, CrewAI and A2A etc)
• Experience building retrieval‑augmented generation solutions (embeddings, semantic search, grounding) using Vector databases and managing prompt lifecycle/versioning
• Strong software engineering fundamentals with ability to deliver cloud‑native services using containers and serverless designs on AWS
• Advanced python programming skills with experience writing production quality code
• Build systems using frontier models from OpenAI, Anthropic or others leveraging platforms such as AWS Bedrock / Google Vertex AI or other similar platforms
• Proven technical leadership skills, including mentoring, driving architecture decisions, and influencing cross‑functional stakeholders
• Hands‑on experience using enterprise-authorized AI‑assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI‑generated outputs for correctness, performance, and security.

Preferred Qualifications, Capabilities And Skills

• Experience building standardized evaluation harnesses, automated regression suites, and experimentation platforms for large language model systems
• Hands‑on experience with Kubernetes‑based deployment patterns and operational excellence practices for high‑availability services
• Experience applying privacy, data minimization, and safe AI guardrail patterns in regulated or high‑risk environments
• Familiarity with context‑efficiency optimization techniques and cost governance for large language model workloads
• Experience building reusable developer platforms, reference architectures, and technical standards across multiple teams

ABOUT US

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.

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.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

About The Team

Our Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You'll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda.