Software Engineer III - AI Developer

JPMorgan Chase JPMorgan Chase · Banking · Plano, TX +1 · Consumer & Community Banking

Software Engineer III at JPMorgan Chase focused on building AI-powered conversational experiences using RAG architectures, AI orchestration frameworks, and cloud services. The role involves developing secure, high-quality production code, leveraging enterprise AI coding assist tools, and applying prompt engineering skills to create chatbots and voicebots.

What you'd actually do

  1. 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.
  2. 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
  3. Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
  4. Develops secure and high-quality production code, and reviews and debugs code written by others
  5. Drives decisions that influence the product design, application functionality, and technical operations and processes

Skills

Required

  • Formal training or certification on software engineering concepts and 5+ 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
  • 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

Nice to have

  • Financial Services industry experience

What the JD emphasized

  • Strong proficiency with RAG architectures
  • Experience with AI orchestration frameworks
  • Proven prompt engineering skills
  • Experience building conversational AI
  • Hands-on experience using enterprise-authorized AI-assisted software development tools

Other signals

  • Leverages enterprise-authorized AI coding assist tools
  • Strong proficiency with RAG architectures
  • Experience with AI orchestration frameworks
  • Hands-on experience with AWS Bedrock, Anthropic Claude models
  • Proven prompt engineering skills
  • Experience building conversational AI