Lead Software Engineer-Python , Java ,Gen AI, Architect

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 JP Morgan Chase within the Corporate Technology 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.

Job responsibilities

• 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

Required qualifications, capabilities, and skills

• 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.