Sr Lead Software Engineer - Agentic AI Solutions
Salary not listed • Bengaluru, Karnataka, India • Full-time
Posted 2d ago
Job Location
Bengaluru, Karnataka, India
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Agent Engineer
About the job
As a Senior Lead Software Engineer at JPMorgan Chase within Asset and Wealth Management, you will be an integral part of an agile team focused on enhancing, building, and delivering market-leading technology products securely, stably, and scalably. You will drive significant business impact by applying deep technical expertise and problem-solving methodologies to a diverse range of challenges across multiple technologies and applications. This role involves designing and implementing LLM-driven agent services for various development tasks and integrating these agents with existing toolchains.
Responsibilities
- Collaborate with stakeholders to define requirements and deliver robust solutions.
- Design and implement LLM-driven agent services for code generation, documentation, testing, and observability on AWS.
- Develop orchestration and communication layers between agents using frameworks like A2A SDK, LangGraph, or AutoGen.
- Integrate AI agents with toolchains such as Jira, Bitbucket, Github, Terraform, and monitoring platforms.
- Contribute to system design, SDK development, and data pipelines supporting agent intelligence.
- Provide technical leadership and mentorship to junior engineers.
- Drive adoption and governance of AI-assisted engineering practices to improve code quality and delivery speed.
- Apply knowledge of AI-assisted development tools to enhance automation value at scale.
- Influence product design, application functionality, and technical operations.
Requirements
- 5+ years of applied software engineering experience with formal training or certification.
- Experience in software engineering using AI technologies.
- Proficiency in Python, Pydantic, FastAPI, LangGraph, and Vector Databases for building RAG-based AI agent solutions.
- Experience with multi-agent orchestration frameworks and deploying end-to-end pipelines on AWS (EKS, Lambda, S3, Terraform).
- Experience with LLM integration, prompt/context engineering, and AI Agent frameworks like Langchain/LangGraph, Autogen, MCPs, A2A.
- Solid understanding of CI/CD, Terraform, Kubernetes, Docker, and APIs.
- Familiarity with observability and monitoring platforms.
- Strong analytical and problem-solving skills.
- Demonstrated experience leading the use of enterprise-authorized AI-assisted software development tools.
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity and security.
- Ability to independently solve design and functionality problems.
- Practical cloud-native experience.