Leads end-to-end solution architecture and hands-on development across Java, Spring Boot, Python, APIs, distributed systems, data platforms, and AI/ML services. Defines high- and low-level designs, integration patterns, nonfunctional requirements, and production-readiness standards. Guides AI-assisted engineering practices, model productionization, MLOps, observability, security, resiliency, and responsible AI controls. Investigates performance and production issues while partnering with data science teams to deliver scalable, reliable services.
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
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.
- 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, capabilities, and skills
- 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.
Similar Jobs
Financial Services
Leads a cross-functional Java and React engineering team building secure, scalable, high-performance market technology. Owns technical vision, architecture, reliability, observability, incident response, security, and production readiness. Partners with Product and Delivery on roadmaps and releases, mentors engineers, and promotes responsible AI-assisted development. Remains hands-on designing and implementing Java services, tuning performance, and supporting microservices deployed on Kubernetes.
Top Skills:
Ai-Assisted Software Development ToolsComputer NetworksContinuous DeliveryContinuous IntegrationFixGitJava 17+KubernetesLinuxMessaging TechnologiesMicroservicesPythonReactRest ApisSolaceSpringSpring BootTest-Driven Development
Fintech • Professional Services • Consulting • Energy • Financial Services • Cybersecurity • Generative AI
Lead end-to-end architecture for agentic AI solutions, including multi-agent workflows, tool calling, memory, retrieval, human-in-the-loop controls, and cloud deployment. Define security, resilience, scalability, latency, cost, observability, and governance standards. Select models, cloud services, vector search technologies, and frameworks while evaluating build-versus-buy decisions. Establish AIDLC stages, architecture decision records, evaluation criteria, release gates, and AI safety controls for banking-critical systems.
Top Skills:
Agentic AiAidlcAPIsAutogenCloud ArchitectureData IntegrationDistributed SystemsEnterprise SearchEvent-Driven SystemsIdentity IntegrationLanggraphLlmLlm ObservabilityMicroservicesRagSemantic KernelVector Databases
Cloud • Information Technology • Security • Software • Cybersecurity
Lead customer architecture discovery and workshops for complex Zscaler Professional Services engagements. Advise sales teams, design multi-product Statements of Work, estimate level of effort, validate technical feasibility, mitigate risks, and support customer zero-trust deployments. Facilitate handoffs to implementation teams, govern scoping, and enable sales through product workshops and deal triage. The role requires deep cybersecurity and network infrastructure expertise, strong technical communication, and 7+ years in customer-facing technical roles.
Top Skills:
Ai ToolsAi-Powered Sales Intelligence PlatformsCloud ProtectionFirewallsIdentity And Access Management (Iam)RoutingSaseSecure Web Gateway (Swg)SseWorkload ProtectionZdxZero Trust ArchitectureZero Trust Network Access (Ztna)ZiaZpaZscaler Zero Trust Exchange
What you need to know about the Pune Tech Scene
Once a far-out concept, AI is now a tangible force reshaping industries and economies worldwide. While its adoption will automate some roles, AI has created more jobs than it has displaced, with an expected 97 million new roles to be created in the coming years. This is especially true in cities like Pune, which is emerging as a hub for companies eager to leverage this technology to develop solutions that simplify and improve lives in sectors such as education, healthcare, finance, e-commerce and more.
