Software Engineer III - Python LLM Engineer

JPMorganChase; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

JPMorganChase in Bengaluru, India, seeks an experienced Software Engineer III to join the Asset and Wealth Management Technology team. You will contribute to building trusted, scalable systems and AI-enabled features within an agile environment.

You will design and productionize LLM-powered applications, implement secure tool integration, and collaborate with product partners to deliver high-impact solutions while upholding security, privacy, and responsible AI standards.

Qualifications

• Formal training or certification on software engineering concepts and 3+ years applied experience.
• Experience in software engineering, including delivering production applications and services.
• Strong proficiency inPython and experience with APIs/microservices.
• Hands-on experience buildingLLM/RAG/agentic applications (prompting, structured outputs, tool/function calling).
• Familiarity with agent frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or similar.
• Working knowledge of data handling basics: SQL and/or pandas workflows.
• Experience with cloud platforms (AWS or Azure), CI/CD, observability, and operational reliability practices.
• Hands-on experience with enterprise-authorized AI-assisted software development tools and secure coding practices.
• Understanding of responsible AI use in engineering workflows and secure model outputs.

Responsibilities

• Design and build agentic AI workflows capable of multi-step reasoning, tool orchestration, and task execution with clear boundaries and human approvals where needed.
• Develop and productionize LLM-powered applications such as conversational interfaces, intelligent search, summarization/extraction services, and advisory assistants.
• Implement patterns for tool integration (APIs, internal services, data sources) so agents can safely retrieve data and take actions with authentication/authorization and audit logging.
• Build and maintain RAG components (ingestion, indexing, retrieval, grounding/citations, reranking) and tune for answer quality and latency.
• Produce architecture/design artifacts for distributed systems, including service boundaries, data flows, scalability, resiliency, and non-functional requirements.
• Establish evaluation and monitoring: offline test sets, automated regression checks, prompt/version management, grounding checks, and runtime observability.
• Apply data engineering / analytics skills to support AI features: data cleaning, normalization, deduplication, exploratory analysis, and KPI reporting.
• Leverage enterprise-authorized AI coding assist tools to improve code quality, speed, and productivity and validate outputs via peer review and secure coding standards.
• Apply knowledge of SDLC tools and enterprise AI-assisted development to improve automation and value.
• Collaborate with product, design, and stakeholders to translate requirements into technical solutions while ensuring security, privacy, and responsible AI expectations.
• Mentor engineers and contribute to shared standards and reusable components across AI delivery.

Skills

Python

APIs/microservices

LLM/RAG/agentic

SQL/pandas

Cloud platforms

CI/CD

Observability

Secure coding

Responsible AI

Architectural patterns

Tools

LangChain

LangGraph

LlamaIndex

Semantic Kernel

CrewAI

AutoGen

Job description

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer III at JPMorganChase within the Asset and Wealth Management Technology team, 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job Responsibilities

• Design and buildagentic AI workflowscapable of multi-step reasoning, tool orchestration, and task execution, with clear boundaries, fallback behavior, and human approvals where needed.
• Develop and productionizeLLM-powered applicationssuch as conversational interfaces, intelligent search, summarization/extraction services, and advisory assistants.
• Implement patterns fortool integration(APIs, internal services, data sources) so agents can safely retrieve data and take actions with authentication/authorization, audit logging, and least-privilege access.
• Build and maintainRAG componentswhere applicable (ingestion, indexing, retrieval, grounding/citations, reranking) and tune for answer quality and latency.
• Produce architecture/design artifacts for distributed systems, includingservice boundaries, data flows, scalability, resiliency, and non-functional requirements(latency/throughput/availability).
• Establishevaluation and monitoring: offline test sets, automated regression checks, prompt/version management, hallucination/grounding checks, and runtime observability (traces, latency, cost, tool-call success rates).
• Apply practical data engineering / analytics skills to support AI features:data cleaning, normalization, deduplication, exploratory analysis, and basic KPI reportingon system quality and user behavior.
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
• 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.
• Collaborate with product, design, and stakeholders to translate requirements into technical solutions, delivery plans, and iterative releases and ensure solutions meetsecurity, privacy, and responsible AIexpectations (safe handling of sensitive data, compliance-aware design, and controlled model outputs).
• Mentor engineers and contribute to shared standards, reusable components, and engineering best practices across AI delivery.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 3+ years applied experience
• Experience in software engineering, including delivering production applications and services.
• Strong proficiency inPythonand experience with APIs/microservices.
• Hands-on experience buildingLLM/RAG/agentic applications(prompting, structured outputs, tool/function calling, state management, error handling).
• Familiarity with agent frameworks such asLangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or similar.
• Working knowledge ofdata handling basics: data cleaning, joins/aggregations, simple statistics, exploratory analysis; comfortable with SQL and/or pandas-style workflows.
• Experience withcloud platforms (AWS or Azure), CI/CD, observability, and operational reliability practices.
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
• Strong understanding of secure development practices and validation of AI outputs (correctness, performance, and security).

Preferred qualifications, capabilities, and skills

• Familiarity with vector search and retrieval tuning (embeddings, reranking, query rewriting).
• Experience working in regulated environments or building applications with strict audit/security requirements.