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

JPMorganChase

Full time On-site
Experience
9+ years
Location
Mumbai
Work mode
On-site
Salary
₹11L – ₹24L a year estimatetypical for IT Jobs in India, 848 posts
Posted 4 days ago

Role at a glance

You will
  • 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.
Experience
9+ years
Must-have skills
CI/CDEvent-Driven ArchitectureJavaKafkaMLOpsMicroservices

Job description

Description
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.
  • 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.


Key skills

Required

CI/CDEvent-Driven ArchitectureJavaKafkaMLOpsMicroservicesMongoDBPythonRedisSpring Boot

Preferred

Kubernetes

Soft skills

Communication

Tags

Software DevelopmentAIIT JobsSoftware Engineer

Job market insights

52active CI/CD jobs in Mumbai
6active Event-Driven Architecture jobs in Mumbai
60active Java jobs in Mumbai
₹11L – ₹24L advertised yearly salary for IT Jobs in India (middle half of 848 posts that show a salary; median ₹17L)
120 more open jobs at JPMorganChase

Jobs asking for CI/CD in Mumbai also ask for

  • Python54%
  • Java48%
  • AWS48%
  • Microsoft Azure35%
  • Agile33%

From live job posts on CoreHRx, updated 21 Oct 2026. Skill figures count posts that list their skills; salary figures only posts that show a salary.

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