Artificial Intelligence Engineer Need Certified "AI-102","AZ-204","AZ-305","DP-100"

Job Title: AI Developer (Need Certified "AI-102","AZ-204","AZ-305","DP-100") Location: Washington, DC(Hybrid role, 4 days onsite) Duration: 6+ months Contract Client : US Tech Solutions / World Bank Note : No Data Analyst/Data Science profiles needed here. Only AI engineer. Key Responsibilities • Design, implement, and operate Retrieval-Augmented Generation (RAG) services using Azure AI/Search, including chunking, embeddings, re-ranking, evaluation, and citation display. • Design and deploy Model Context Protocol (MCP) tools/servers to integrate security scanners, inventory systems, approvals, and Azure DevOps/GitHub services. • Build agentic AI solutions using AutoGen, CrewAI, and/or Agno, enabling secure tool-calling and multi-agent orchestration for troubleshooting and workflow automation. • Develop production-grade chatbots (multi-turn, retrieval-grounded) with prompt management, guardrails, audit logging, and telemetry. • Integrate Azure OpenAI securely behind API Management (APIM), manage secrets with Key Vault, handle events via Event Hub, and instrument with App Insights/Log Analytics. • Evaluate and (where appropriate) fine-tune open-source models (e.g., PEFT/LoRA), balancing quality, latency, cost, and safety. • Ship with CI/CD on Azure DevOps, implement unit/integration tests, red-team for prompt-injection/jailbreaks, and document runbooks. Minimum Qualifications • 4-8 years total software development experience, with 2+ years in applied LLM/GenAI. • Strong Python skills and hands-on experience with Azure OpenAI and Azure AI/Search (vector search, hybrid search, semantic ranking). • Practical experience with agent frameworks (AutoGen, CrewAI, Agno) and MCP/tool-use patterns. • Proven Azure PaaS experience: Azure Functions or Web Apps, APIM, Key Vault, Event Hub; familiarity with Entra ID/RBAC and secure API design. • Experience implementing observability (App Insights, Log Analytics/KQL) and CI/CD with Azure DevOps. Nice to Have (including Certifications) • RAG evaluation frameworks (e.g., Ragas), custom golden sets, KQL proficiency, Cosmos DB familiarity. • Security-first mindset: content safety, prompt-injection defenses, data privacy controls, and threat modeling for AI systems. • Experience with cost monitoring/optimization of LLM workloads and latency tuning. Certifications (any of): • Microsoft Certified: Azure AI Engineer Associate (AI-102) • Microsoft Certified: Azure Developer Associate (AZ-204) • Microsoft Certified: Azure Solutions Architect Expert (AZ-305) • Microsoft Certified: Azure Data Scientist Associate (DP-100)