Lead Engineer- Advanced AI

Target Target · Retail · Bangalore, India

Lead Engineer for Target's Advanced AI team, responsible for designing, building, deploying, and maintaining end-to-end AI/ML systems, including LLM-powered applications and agentic architectures. Focuses on production-grade, scalable, and reliable applications, providing technical leadership, contributing to architecture, and ensuring strong engineering practices across development, testing, deployment, and observability.

What you'd actually do

  1. help design, build, deploy, and maintain AI/ML applications that support automation, insight, and action across core business workflows
  2. provide hands-on technical leadership for AI engineering initiatives
  3. contribute to architecture and design decisions, evaluate appropriate models, frameworks, and tools, write maintainable production-quality code, and help establish strong engineering practices across development, testing, deployment, observability, documentation, and ongoing support
  4. partner with senior engineers and engineering leaders to shape technical approaches, identify implementation risks, resolve roadblocks, and support the evolution of reusable AI engineering patterns
  5. help deliver production-grade AI applications that create measurable business value while raising the technical quality and capability of the broader team

Skills

Required

  • Python
  • PyTorch
  • TensorFlow
  • LangChain
  • LlamaIndex
  • Semantic Kernel
  • model APIs
  • prompt orchestration
  • agent development patterns
  • retrieval-augmented generation
  • evaluation frameworks
  • observability tools
  • cloud ML platforms
  • containers
  • orchestration technologies
  • system design
  • application architecture
  • model and framework tradeoffs
  • experimentation
  • evaluation strategy
  • performance optimization
  • production deployment considerations for AI systems
  • scalable, maintainable, and well-tested services, APIs, data pipelines, applications, or platforms
  • version control
  • CI/CD
  • code review practices
  • documentation
  • operational monitoring
  • production support
  • translate ambiguous business problems into clear technical approaches
  • collaborate with cross-functional partners
  • explain technical concepts clearly
  • mentor engineers
  • contribute to technical direction
  • raise the quality of engineering practices within a team

Nice to have

  • MS in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics or a related technical field

What the JD emphasized

  • build and operate production systems
  • building and operating production systems
  • production-grade applications
  • production-grade AI applications
  • production deployment considerations for AI systems
  • production support

Other signals

  • builds end-to-end AI/ML systems
  • production-grade applications
  • agentic architectures
  • deliver production-grade AI applications