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Sr. Gen AI Developer

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Architect (Level: Manager)
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CREQ250087 Requisition #

  • Strong hands‑on experience (10-12 years) in Python or Java (mandatory).

  • Proven experience designing and delivering LLM / GenAI solutions (e.g., RAG, orchestration, prompt engineering, AI‑assisted automation).

  • Solid understanding of microservices, APIs, distributed systems, and enterprise integration patterns.

  • Experience reviewing and governing AI‑assisted / GenAI‑generated code.

  • Strong foundation in secure coding practices and performance optimizatio

  • AI & GenAI Experience designing and implementing LLM‑based solutions (RAG, agents, copilots, automation).

  • Understanding of model lifecycle, inference pipelines, performance tuning, and cost optimization.

  • Familiarity with AI governance concepts such as bias, explainability, auditability, and model risk controls.

  • Experience with cloud‑native or hybrid environments, containers, and orchestration platforms.

  • Exposure to CI/CD pipelines, observability, and production support models.

  • Knowledge of secure coding practices and enterprise security standards.

Technical Skills & Experience:

  • Mandatory Strong Hands-on Experience (10-12 years): Python or Java development.

  • AI/GenAI Solution Delivery: Proven experience in designing and implementing LLM/GenAI solutions, including RAG, orchestration, prompt engineering, AI-assisted automation, agents, and copilots.

  • Architecture & Systems: Solid understanding of microservices, APIs, distributed systems, and enterprise integration patterns.

  • Cloud & Deployment: Experience with cloud-native or hybrid environments, containers, and orchestration platforms. Exposure to CI/CD pipelines, observability, and production support models.

AI Governance & Lifecycle:

  • Model Management: Understanding of the model lifecycle, inference pipelines, performance tuning, and cost optimization.

  • AI Governance: Familiarity with concepts such as bias, explainability, auditability, and model risk controls.

  • Code Review: Experience reviewing and governing AI-assisted/GenAI-generated code.

Security & Optimization:

  • Secure Development: Strong foundation in secure coding practices, enterprise security standards, and performance optimization.

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