Design, deploy, and operate a secure, scalable Generative AI platform on AWS (Bedrock) for production LLM applications. Own architecture, deployment, monitoring, incident management, reliability, governance, and cost optimization in regulated financial environments.
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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Information Technology • Consulting
Design, build, and operate a secure, scalable Generative AI platform on AWS (including Bedrock) for production LLM applications in regulated environments. Own platform lifecycle: architecture, deployment, operations, monitoring, incident management, reliability, and cost optimization. Implement RAG, Agents, inference, guardrails, observability, access controls, and governance, with emphasis on Responsible AI and production reliability in financial services.
Top Skills:
AgentsAWSAws BedrockLlmsMicroservicesObservability/MonitoringPythonRest ApisRetrieval-Augmented Generation (Rag)
Information Technology • Consulting
Design, build, and operate a secure, scalable enterprise Generative AI platform on AWS (including AWS Bedrock). Own platform lifecycle: architecture, deployment, operations, monitoring, incident management, reliability, and governance. Implement LLM inference, RAG, Agents, guardrails, observability, security controls, access management, compliance, and cost optimization. Support production-grade GenAI applications in regulated/financial environments.
Top Skills:
AgentsAWSAws BedrockLlmsMicroservicesPythonRest ApisRetrieval-Augmented Generation (Rag)
Information Technology • Consulting
Design and deliver GenAI solutions: prototype to production LLM services, build RAG pipelines, fine-tune models (LoRA/QLoRA/PEFT), engineer prompts/tools/memory, ensure safety and evaluation, deploy with MLOps (CI/CD, containers, IaC), optimize inference, and ensure security/compliance while collaborating with product, data, and SRE teams.
Top Skills:
Agentic PatternsChunkingCi/CdContainerizationContent FiltersDocument StoresEmbeddingsEvaluation FrameworksFilteringFoundation ModelsGuardrailsHosted ApisInfrastructure As CodeLlmLoraMultimodalObservability ToolingOpen-Source ModelsPeftPii HandlingPrompt EngineeringQloraRagRe-RankingRetrievalVector Databases
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