What are the responsibilities and job description for the Lead Software Engineer - AI Developer position at JPMorgan Chase?
Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Senior Lead Software Engineer at JPMorganChase within the Community & Consumer Bank - CX Loyalty Travel 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
- Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
- Develops secure and high-quality production code, and reviews and debugs code written by others
- Drives decisions that influence the product design, application functionality, and technical operations and processes
- Serves as a function-wide subject matter expert in one or more areas of focus
- Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
- Influences peers and project decision-makers to consider the use and application of leading-edge technologies
- Adds to the team culture of opportunity, inclusion, and respect
- Ability to tackle design and functionality problems independently with little to no oversight
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 10 years applied experience
- Advanced in programming languages Java, Python or Node.js
- Strong proficiency with RAG architectures — chunking strategies, embedding models, vector stores (Pinecone, OpenSearch, pgvector, FAISS)
- Experience with AI orchestration frameworks: LangChain, LlamaIndex, Semantic Kernel, or CrewAI
- Hands-on experience with AWS Bedrock, Anthropic Claude models, and model invocation APIs
- Proven prompt engineering skills — system prompts, few-shot, chain-of-thought, tool use, structured outputs
- Experience building conversational AI: chatbots (text) and voicebots (speech-to-text, text-to-speech integration)
- Proficiency with AWS services (Lambda, Step Functions, API Gateway, S3, DynamoDB, SQS)
- Experience with CI/CD pipelines, containerization (Docker, ECS/EKS), and infrastructure-as-code
- Strong understanding of API design (REST, GraphQL), microservices architecture, and event-driven systems
- Familiarity with evaluation frameworks for LLM outputs. Experience with guardrails, content filtering, and responsible AI practices
- Financial Services industry experience