Lead Software Engineer-Python , Java ,Gen AI, Architect
JPMorgan Chase · Posted Oct 15
Global banking, investment, credit card, mortgage, and asset management services
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About the role
JPMorgan Chase's Corporate Technology organization builds and delivers trusted, market-leading technology products in a secure, stable, and scalable way, with agile teams supporting the firm's business objectives across applications, APIs, data, and integrations. The team works on distributed, event-driven and cloud-native systems as well as AI/ML production patterns, including inference, feature pipelines, evaluation, and monitoring. This Lead Software Engineer role owns end-to-end solution architecture, provides hands-on Java/Spring Boot and Python technical leadership, partners with Data Science teams to productionize models, and drives NFRs, operational excellence, and responsible AI controls.
What you will do
- Own end-to-end solution architecture across applications, APIs, data, integrations, and environments (development through production).
- Convert business requirements into target-state architecture, HLD, and LLD with clear trade-offs and documented decisions.
- Define integration patterns and cross-service contracts (REST/gRPC, event-driven), including versioning, compatibility, and SLAs.
- Provide hands-on technical leadership by contributing Java/Spring Boot and Python code for reference implementations, critical paths, and POCs through to production.
- Leads team adoption of enterprise-authorized AI-assisted engineering practices and SDLC/TLM automation to improve delivery speed, quality, and operational outcomes, while setting expectations for human validation, secure handling of inputs/outputs, and consistent use of reusable patterns across teams.
- 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 and support capacity unlock initiatives.
- Lead design spikes and performance investigations to validate approaches and resolve complex technical risks.
- Drive complex production issue triage and root cause analysis, ensuring sustainable fixes and operational learning.
- Design and deliver production patterns for AI/ML capabilities (batch and real-time inference, feature pipelines, evaluation, monitoring).
- Partner with Data Science teams to move models from experimentation to reliable, scalable, and observable services.
- Implement responsible AI controls (traceability, testing/evaluation, approvals, and appropriate human oversight where required).
- Define and deliver NFRs and operational excellence (availability, latency, throughput, scalability, resiliency, RTO/RPO, capacity planning, observability/SLOs/runbooks) with secure-by-design and SDLC/audit compliance
Skills used in this role
What the employer is looking for
- Formal training or certification on software engineering concepts and 9+ years applied experience.
- Strong hands-on experience designing and delivering enterprise solutions end-to-end.
- Demonstrated solution architecture capability (target-state architecture, HLD/LLD, trade-offs, and architecture decision documentation) across services, data, and integrations.
- Java 11/17+ expertise, including Spring Boot microservices, API design, and testing practices.
- Python 3.x expertise for services, automation, and data/ML integration.
- Proven distributed systems experience: microservices, event-driven architecture, and messaging/streaming (Kafka or equivalent).
- Strong data architecture fundamentals: relational/NoSQL patterns (including MongoDB), caching (e.g., Redis), data consistency, and schema evolution.
- Practical experience productionizing AI/ML: inference patterns, model packaging/serving, and monitoring/drift fundamentals.
- Working knowledge of MLOps concepts and operational model lifecycle management.
- DevOps delivery mindset: CI/CD, automated testing (unit/integration/contract), and release/rollback strategies; strong security and resiliency mindset suitable for regulated environments with excellent communication and influence skills to align stakeholders.
Preferred qualifications
- Kubernetes/container platforms and cloud-native patterns (autoscaling, config/secrets, service-to-service security).
- GenAI experience (LLMs, RAG, vector search, evaluation frameworks, prompt/model governance) where applicable.
- Modernization experience (monolith decomposition, strangler patterns, incremental migration).
- Advanced production readiness and observability practices, including readiness reviews, monitoring, and operational rigor.
Benefits and support
- Compensation and benefits are detailed in the job posting
About JPMorgan Chase
JPMorgan Chase & Co. is one of the oldest, largest, and most diversified financial services institutions in the world. Operating globally through the J.P. Morgan and Chase brands, the firm provides a comprehensive range of financial solutions including investment banking, consumer and commercial banking, transaction processing, and asset management. Serving millions of consumers and many of the world's most prominent corporate, institutional, and government clients, the company combines deep market expertise with extensive technological investments.
- Industry
- Banking
- Company size
- 320000+ employees
- Founded
- 1799
- Location
- New York, New York, USA
- Funding stage
- Public Company
Leadership
Chairman and Chief Executive Officer
Chief Financial Officer
Chief Operating Officer
Global Chief Information Officer
CEO, Asset & Wealth Management
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