Job Description

Job Description

  • Deep experience building LLM-based systems (retrieval, agents, workflow orchestration, API chaining)
  • Strong grounding in Python and/or Java and one enterprise framework (Azure OpenAI, AWS Bedrock, or equivalent)
  • Ability to architect reusable components for document intelligence, workflow automation, and copilots
  • Familiarity with vector databases, embeddings, evaluation frameworks, and prompt engineering best practices
  • Design and implement guardrails, safe execution patterns, and quality gates
  • Knowledge of cloud platforms, microservices, serverless, and DevOps practices
  • Comfortable translating business problems into scalable AI pipelines

    • Qualifications

    Experience

  • 6+ years software engineering, 2+ years hands-on LLM/GenAI development
  • Building agentic automation systems or production LLM apps in enterprise context
  • Leading small cross-functional engineering pods
  • Prior work with enterprise datasets, unstructured data, PDFs, OCR, structured checklists
  • Experience driving architectural decisions and mentoring engineers
  • Familiarity with secure data handling and compliance (e.g., role-based access, logging, auditability)

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