AI Engineer / Machine Learning Engineer

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Description

As an AI Engineer focused on Generative and Agentic AI, you will design, build, deploy, and operate production-ready AI systems, taking ideas from early prototypes through to reliable, enterprise-grade solutions. You will work hands-on with real customer and internal use cases, owning the full lifecycle from design and orchestration to deployment, monitoring, and continuous improvement. The role emphasizes building intelligent systems that can reason, plan, use tools, and make decisions, rather than standalone models or simple chatbots. You will apply modern Generative AI techniques and strong software engineering practices to deliver real-world AI outcomes on a scale. Key Responsibilities Experience needed 5-7 years Generative & Agentic AI Development · Design and build LLM-based systems using: o Retrieval Augmented Generation (RAG) o Embeddings and vector search o Prompt engineering and prompt optimization o Function calling and tool usage o Agentic and multi-agent workflows · Develop AI systems that integrate LLMs with REST APIs, enterprise systems, data platforms, and workflows · Apply LLM evaluation techniques to assess quality, reliability, safety, and performance End-to-End AI Engineering · Own the full lifecycle of AI solutions—from prototype to production · Build, deploy, and operate AI workloads in AWS environments · Ensure production readiness with focus on scalability, reliability, performance, security, and cost optimization · Implement CI/CD pipelines, automated testing, and versioning for AI systems Engineering Excellence & Operations · Apply strong software engineering and distributed systems principles to AI development · Implement observability practices including logs, metrics, traces, and alerts · Monitor model behavior, system health, latency, and failures in production · Contribute to responsible AI practices, governance, and quality standards Collaboration & Enablement · Work closely with other AI engineers, data scientists, platfo

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