Design, build, and operate a secure, scalable GenAI platform on AWS (including Bedrock). Own platform lifecycle, enable LLM inference, RAG, Agents and guardrails, ensure observability, incident management, security, compliance, cost optimization, and reliability for production-grade regulated-financial environments. Provide Python-based development and support for microservices and REST APIs.
JD Experience – 8 + years Key Responsibilities • Design, build, and operate a secure, scalable, and cost efficient enterprise Generative AI platform on AWS, supporting production grade LLM applications in regulated environments. • Own the full GenAI platform lifecycle, including architecture, deployment, operations, monitoring, incident management, and continuous reliability and performance improvements. • Implement and run AWS Bedrock–based solutions, enabling LLM inference, RAG, Agents, and Guardrails with high availability, fault tolerance, and SLA compliance. • Establish strong operational and governance frameworks, covering observability, alerting, RCA, security controls, access management, compliance, and cost optimization. • Bring deep expertise in cloud ML platforms and financial services, with strong Python skills, AWS services knowledge, GenAI hands on experience, and a background in production support, reliability engineering, and AI governance. Required Skills • 8+ years of experience in hands on exposure to AI/ML or Generative AI systems • Strong understanding of AI evaluation techniques, including hallucination detection, factual accuracy, bias, and output consistency • Knowledge of Responsible AI principles, including fairness, transparency, and explainability • Python (must-have) and Experience with: REST APIs and microservices
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Design, build, and operate a secure, scalable GenAI platform on AWS (AWS Bedrock) for production LLM applications. Own platform lifecycle: architecture, deployment, monitoring, incident management, reliability, governance, access controls, compliance, and cost optimization. Apply Responsible AI, hallucination detection, RAG, agents, and security controls in regulated financial environments.
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Design, build, and operate a secure, scalable Generative AI platform on AWS (including Bedrock) to support production LLM applications in regulated financial environments. Own platform lifecycle: architecture, deployment, operations, monitoring, incident management, reliability, and performance. Implement LLM inference, RAG, Agents, guardrails, observability, security controls, access management, compliance, and cost optimization. Provide production support, reliability engineering, and AI governance.
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AgentsAWSAws BedrockLlmMicroservicesPythonRagRest Apis
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