Leads the design, development, deployment, and operation of production agentic AI applications. Builds Graph RAG, agent memory, organizational context management, multi-agent workflows, evaluation systems, guardrails, and secure cloud infrastructure. Partners with business and product stakeholders to deliver scalable agents across financial services while contributing technical leadership and software development lifecycle best practices.
Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Senior Lead Software Engineer at JPMorganChase within the Commercial and Investment bank Digital & Platform Services, Data Analytics, 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Job responsibilities
As a Senior Lead Software Engineer at JPMorganChase within the Commercial and Investment bank Digital & Platform Services, Data Analytics, 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Job responsibilities
- Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
- Design and ship production agents on NEO across the federated portfolio, owning them from prototype through production.
- Build retrieval that holds up in production: Graph RAG combining knowledge-graph traversal with vector search, plus chunking, ranking, and grounding strategies that keep answers accurate and auditable.
- Design agent memory: episodic and semantic memory organized as memory nodes, with recall, summarization, and decay policies tuned per use case.
- Own organizational context management — assembling entitlement-, lineage-, and tenant-aware context so each agent reasons over only what it’s allowed to see.
- Compose multi-agent workflows using A2A, and integrate tools and data through MCP servers (Bitbucket, Confluence, Databricks, Kubernetes, Snowflake, Splunk).
- Build and run evals: task-level and end-to-end agent evaluations, regression suites, LLM-as-judge, and quality safety gating before release.
- Deploy and operate solutions on public cloud (AWS and, or Azure) with strong SDLC, security, resiliency, and observability practices.
- Partner with product and business partners across CIB and Payments to turn use cases into shipped, supported agents.
- Serves as a function-wide subject matter expert in one or more areas of focus
- Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience with at least 4 years working on AI/ML solutions.
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced in one or more programming language(s) - Strong programming skills in Python, with deep knowledge of data structures, algorithms, machine learning, data mining, information retrieval, and statistics.
- Hands-on experience building LLM-powered or agentic applications in production, including tracing, evaluations, and guardrails.
- Deep proficiency with Kubernetes and Amazon EKS, micro-VM isolation (e.g., Firecracker, Kata Containers, gVisor), and sidecar architectures, with proven experience designing defense in depth across the stack: network and mTLS, workload identity, fine-grained authorization, runtime isolation for untrusted or adversarial workloads, and application-level guardrails
- Practical RAG experience — retrieval quality, embeddings, and vector stores; Expert knowledge of at least one of: AWS, Azure, Kubernetes.
Knowledge of data management and data model design; real-time processing using
both SQL (e.g., Postgres) and NoSQL stores (e.g., OpenSearch, Redis). - Excellent communication skills with the ability to partner effectively with senior technical and business stakeholders.
- Proficient in all aspects of the Software Development Life Cycle
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
In-depth knowledge of the financial services industry and their IT systems
Preferred qualifications, capabilities, and skills
- MS in Computer Science, Statistics, Mathematics, Machine Learning, or related field (or equivalent experience).
- Experience with agent frameworks or runtimes, A2A, or MCP. Agent memory design (memory nodes, episodic/semantic memory) and organizational context management.
- Knowledge graphs and graph databases used for retrieval. Graph RAG a strong plus.
- Understanding of LLM fine-tuning and small language model inference.
- Ability to develop full-stack products using modern JavaScript/TypeScript frameworks (e.g., Next.js, Svelte) for agent UIs (AG-UI , NEO UI SDK).
- Experience working in the financial or payments domain at a large institution (Investment Banking, Markets, Securities Services, or adjacent).
- Knowledge of high-performance languages such as Go or Rust
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
JPMorganChase San Francisco, California, USA Office
San Francisco, CA, United States
Similar Jobs
Financial Services
Leads architecture and production engineering for agentic pricing and AI/ML platforms. Designs multi-agent systems, secure authorization, deterministic pricing controls, MLOps pipelines, model serving, monitoring, governance, and auditability. Develops and reviews high-quality software, establishes AI safety and validation standards, troubleshoots complex systems, mentors engineers, and partners with product, pricing, finance, risk, and platform teams.
Top Skills:
Ag-UiAgent-To-Agent (A2A) CommunicationAi AgentsAmazon EksCi/CdCloud-Native TechnologiesDatabricksEnvoyFirecrackerGoogle AdkGvisorIstioKata ContainersKubernetesLanggraphLlmsMlflowMlopsModel Context Protocol (Mcp)MtlsMulti-Agent SystemsOpa/RegoOpenfgaPython
Fintech • Software
Leads DFIN’s government affairs and public policy strategy, monitoring regulatory developments, influencing policy outcomes, and advising executive leadership. Builds relationships with regulators, policymakers, trade associations, and industry stakeholders; coordinates consultations and advocacy efforts; manages subject-matter experts; and translates regulatory changes into business opportunities, risk mitigation, product strategy, and executive communications.
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Own readiness and enablement programs for SDR teams, including onboarding, sales training, prospecting, qualification, product knowledge, tool adoption, AI workflows, and manager coaching. Facilitate workshops and role-plays, develop learning content and playbooks, partner with sales, marketing, operations, and systems teams, and measure impact through ramp time, conversion, pipeline, proficiency, and adoption metrics.
Top Skills:
Artificial IntelligenceConversation Intelligence ToolsCRMGongLinkedin Sales NavigatorOutreachSales Engagement ToolsSalesforceSalesloftZoominfo
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
