Software Engineer III - AI/ML, Java/Python, REACT

JPMorganChase · Mumbai · 3+ yrs experience · Posted 2026-07-01

Tech stack: Java, Python, React

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About the role

We are seeking a highly motivated and innovative technologist passionate about solving business problems using modern software engineering and applied AI techniques at enterprise scale. Our team is focused on improving end-to-end risk and control posture for the Line of Business by building resilient platforms, reliable services, and prompt-enabled workflow automation. We embrace a culture of experimentation, continuous learning, and disciplined engineering execution.
Responsibilities:
- Build and operate resilient backend services and APIs that power enterprise workflows and AI-enabled capabilities.
- Integrate LLM/prompt capabilities into production services with guardrails, fallback paths, response validation, and clear auditability.
- Design service interfaces with strong API contract management, versioning, and integration patterns.
- Implement retrieval patterns (e.g., RAG) and orchestration workflows using LangChain or similar frameworks, connecting models to approved enterprise data sources and APIs (subject to firm-approved tooling).
- Implement and optimize vector search/embedding solutions (e.g., pgvector or equivalent) including indexing strategy, metadata filtering, hybrid search, and production scaling (subject to firm-approved tooling).
- Build intuitive user experiences for AI-powered applications and dashboards using modern front-end frameworks (React preferred).
- Design and manage persistence layers using relational and/or NoSQL databases; apply strong data modeling and schema design.
- Apply event-driven and asynchronous processing patterns where appropriate; ensure reliability and idempotency.
- Build CI/CD pipelines, release automation, and environment promotion controls; drive repeatable, safe delivery.
- Implement robust testing strategies (unit, integration, end-to-end), establish strong observability (logs, metrics, tracing, alerting), diagnose performance/reliability issues in live systems, and translate ambiguous requirements into clear technical designs and deliverables with effective stakeholder communication.
Qualifications:
- BS/BA degree in Computer Science, Engineering, Information Systems, or equivalent experience.
- 3+ years of hands-on software engineering experience delivering production systems.
- Strong experience building backend services and APIs in
- Java and/or Python
- Solid foundation in
- distributed systems
- , service design, and API contract management.
- Experience with cloud-native development and familiarity with
- services.
- Experience with
- , release automation, and modern deployment practices.
- Proficiency in testing practices and production readiness (quality, reliability, operational support).
- Strong collaboration and communication skills; ability to convert business intent into executable technical plans.
- 1+ years integrating AI/LLM functionality into enterprise applications, including guardrails and monitoring.
- Experience with vector search/embeddings and retrieval-enabled architectures (RAG).
- Experience with observability platforms and SRE-style operational practices.
- Experience with secure SDLC practices and governance expectations.
- Experience in financial services, technology risk, controls, or audit-oriented environments. Relevant cloud certifications.

Qualifications

- BS/BA degree in Computer Science, Engineering, Information Systems, or equivalent experience.
- 3+ years of hands-on software engineering experience delivering production systems.
- Strong experience building backend services and APIs in Java and/or Python
- Solid foundation in distributed systems service design, and API contract management.
- Experience with cloud-native development and familiarity with services.
- Experience with release automation, and modern deployment practices.
- Proficiency in testing practices and production readiness (quality, reliability, operational support).
- Strong collaboration and communication skills; ability to convert business intent into executable technical plans.
- 1+ years integrating AI/LLM functionality into enterprise applications, including guardrails and monitoring.
- Experience with vector search/embeddings and retrieval-enabled architectures (RAG).
- Experience with observability platforms and SRE-style operational practices.
- Experience with secure SDLC practices and governance expectations.
- Experience in financial services, technology risk, controls, or audit-oriented environments.
- Relevant cloud certifications.

Responsibilities

- Build and operate resilient backend services and APIs that power enterprise workflows and AI-enabled capabilities.
- Integrate LLM/prompt capabilities into production services with guardrails, fallback paths, response validation, and clear auditability.
- Design service interfaces with strong API contract management, versioning, and integration patterns.
- Implement retrieval patterns (e.g., RAG) and orchestration workflows using LangChain or similar frameworks, connecting models to approved enterprise data sources and APIs (subject to firm-approved tooling).
- Implement and optimize vector search/embedding solutions (e.g., pgvector or equivalent) including indexing strategy, metadata filtering, hybrid search, and production scaling (subject to firm-approved tooling).
- Build intuitive user experiences for AI-powered applications and dashboards using modern front-end frameworks (React preferred).
- Design and manage persistence layers using relational and/or NoSQL databases; apply strong data modeling and schema design.
- Apply event-driven and asynchronous processing patterns where appropriate; ensure reliability and idempotency.
- Build CI/CD pipelines, release automation, and environment promotion controls; drive repeatable, safe delivery.
- Implement robust testing strategies (unit, integration, end-to-end), establish strong observability (logs, metrics, tracing, alerting), diagnose performance/reliability issues in live systems, and translate ambiguous requirements into clear technical designs and deliverables with effective stakeholder communication.

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