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About the role
Must-Have: Bachelor’s degree with experience in AI/ML engineering and solution development. Strong experience in AI/ML engineering, solution architecture, and end-to-end AI solution delivery. Deep understanding of RAG, prompt engineering, vector databases, embeddings, and model evaluation techniques. Hands-on experience with LLMs, generative AI technologies, and agentic AI frameworks for building intelligent applications and orchestration workflows. Strong knowledge of software engineering best practices, including APIs, automation platforms, version control, testing, CI/CD, deployment, and responsible AI principles related to governance, security, and privacy.
Nice-to-Have: Experience with LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, OpenAI Agents SDK, or equivalent agent orchestration frameworks.
orchestration frameworks for intelligent automation.
Automated infrastructure provisioning and management using Terraform and Infrastructure as Code (IaC) practices.
Designed and deployed cloud-based solutions on Azure, AWS, and Google Cloud platforms.
Applied MLOps best practices for enterprise AI deployments and leveraged automation certifications to deliver scalable, reliable solutions.
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