Software Engineer Iii- AI & Engineering/software as a Service

Software Engineer III role focused on architecting and implementing full-stack and agentic AI solutions, including multi-agent applications, RAG pipelines, and tool-calling agents. The role involves leading end-to-end delivery, mentoring junior engineers, and working with cloud-native infrastructure.

What you'd actually do

  1. Architect, design, and implement scalable, reliable, and maintainable full-stack software systems and services.
  2. Design and operationalize RESTful and asynchronous APIs on cloud-native infrastructure (AWS, Azure, or GCP), including containerized workloads, CI/CD pipelines, and infrastructure-as-code.
  3. Lead end-to-end delivery of complex features from requirements gathering through deployment and monitoring.
  4. Architect and deliver production-grade agentic AI and multi-agent applications using popular frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel; design patterns including orchestrator-agent hierarchies, RAG pipelines, tool-calling agents, and context/memory management.
  5. Conduct thorough code reviews, enforce coding standards, and champion engineering best practices.

Skills

Required

  • Java
  • Spring-based application development
  • microservices
  • APIs
  • messaging
  • event-driven architectures
  • AWS
  • GCP
  • Docker
  • Kubernetes
  • Terraform
  • CI/CD tooling
  • SQL
  • NoSQL data stores
  • Store and Associate Technology (SAT)
  • backend development
  • cloud development

Nice to have

  • LangChain
  • LangGraph
  • AutoGen
  • CrewAI
  • Semantic Kernel
  • Kafka
  • RabbitMQ
  • SQS
  • observability
  • security
  • code quality tools
  • machine learning pipelines
  • data engineering workflows
  • Large Language Models (LLMs)
  • agentic AI architectures
  • OWASP guidelines
  • secure coding standards
  • tech lead
  • staff engineer

What the JD emphasized

  • Must have experience in Store and Associate Technology (SAT)
  • 7+ years of software engineering experience
  • Demonstrated experience designing and delivering solutions that incorporate Large Language Models (LLMs) and/or agentic AI architectures in a professional setting.

Other signals

  • architect and deliver production-grade agentic AI and multi-agent applications
  • design patterns including orchestrator-agent hierarchies, RAG pipelines, tool-calling agents, and context/memory management