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Lead AI Engineer

fa-ewmy-saasfaprod1

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What AI roles keep asking for: LLMs (30%), Python (28%), AWS (21%), Generative AI (18%), Machine learning (16%), Observability (15%), RAG (13%) — counted across their open postings here.

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Questions you are likely to be asked

  1. Why do you want to join fa-ewmy-saasfaprod1?
  2. What is your experience with System design? Tell me one thing you learned the hard way.
  3. How would you explain your model's result to someone who is not technical?
  4. What would you check first if a model's accuracy dropped after going live?
  5. When would you not use machine learning for a problem?

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We are seeking a Lead AI Engineer with strong software engineering foundations and hands-on experience in Generative and Agentic AI. In this role, you will architect, design and build production-grade AI systems powered by large language models and intelligent agents. You will design scalable AI workflows, integrate autonomous agents into real-world applications, and help translate cutting-edge AI capabilities into reliable business solutions. • 8+ years of professional software development experience (Dotnet/React/Full-stack) with mentorship/team leadership experience. • Minimum 2 years of hands-on experience building applications using Generative AI or agentic AI systems. • Strong proficiency in Python and backend engineering principles. • Experience designing RESTful APIs and scalable service architectures. • Practical experience with LLM APIs, embeddings, vector search, or RAG pipelines. • Working knowledge of AI governance principles, responsible AI practices, or compliance considerations. • Familiarity with agent frameworks and autonomous decision workflows. • Understanding of data structures, system design, and performance optimization. • Strong analytical thinking and problem-solving skills. Preferred Qualifications • Experience deploying AI applications in cloud environments (preferably AWS). • Familiarity with vector databases and knowledge retrieval architectures. • Experience working with Git, CI/CD pipelines, and production deployments. • Exposure to containerization and orchestration tools (Docker, Kubernetes). • Experience implementing evaluation or monitoring pipelines for AI agents. • Knowledge of AI safety, guardrails, and responsible AI practices. • Knowledge of distributed systems or event-driven architecture.

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Listed on oraclehcm · posted 2026-09-18. ApplySarthi collects openings and links to application pages; the role is advertised by fa-ewmy-saasfaprod1, not by us.