Senior AI Engineer (Generative AI / RAG / Agentic AI)

About the position We are seeking a Senior AI Engineer to architect and deliver secure, scalable, production-grade Generative AI solutions. You will design and implement RAG systems, agentic AI orchestration, and cloud-native ML infrastructure across Azure and AWS. This role blends hands-on engineering with technical leadership, including mentoring and setting reusable engineering standards. Responsibilities • Architect and deliver enterprise GenAI, RAG, and conversational AI solutions end-to-end • Design scalable retrieval, prompting, and inference patterns across Azure and AWS • Build ingestion, enrichment, vectorization, and feature pipelines using Databricks, ADF, and EMR • Implement embedding quality checks, drift monitoring, and metadata governance • Engineer secure multi-agent/tool-calling systems using modern agent frameworks and MCP controls • Establish evaluation, safety guardrails, CI/CD, automated testing, and observability for AI workloads • Apply secure AI engineering practices, including threat modeling and compliance-aligned controls • Lead design reviews, code reviews, and mentor engineers; create reference architectures and playbooks Requirements • Bachelor’s in CS/Engineering (Master’s preferred) • 8+ years of software engineering experience • 2+ years building applied Generative AI solutions (RAG, agents, evaluation/safety) in production • Azure: Azure OpenAI, Azure AI Search, Azure AI Agent Service, Azure ML, AKS, ADF, Databricks, Functions, API Mgmt, Key Vault, App Insights • AWS: SageMaker, Bedrock, Lambda, API Gateway, S3, CloudWatch, EMR, EKS, CodePipeline, Outposts • Vector/Indexing: Azure AI Search, Redis, FAISS, HNSW, IVF • Frameworks: Semantic Kernel, AutoGen, Microsoft Agent Framework, CrewAI, Agno, LangChain, MCP, Hugging Face • Languages: Python, C#, .NET, TypeScript • Inference/Deploy: Docker, vLLM, Triton, Ollama, quantized Llama (GGUF), GPU scheduling, multimodal pipelines • MLOps/Platform: MLflow, evaluation tooling, guardrails, Azure DevOps pipelines, Kubernetes, hybrid/multi-cloud • AI-900, DP-900, Responsible AI Certification, AWS ML Specialty, TensorFlow Developer, CKA/CKAD, SAFe Agile Software Engineering Nice-to-haves • AI-102, DP-100, AZ-305, AZ-204 Benefits • Competitive salary • Opportunity for advancement • Training & development