AI Engineer – GenAI RAG Agentic AI
Washington, AR - USA
Job Summary
AI Engineer GenAI / RAG / Agentic AI
Location: Washington DC (Hybrid 4 Days Onsite)
Job Type: Contract
About Us
Job Summary
STAFFXPERT LLC is seeking an AI Engineer on behalf of our client in Washington DC. This role is ideal for a hands-on engineer with strong software development experience and deep expertise in Generative AI Retrieval-Augmented Generation (RAG) Agentic AI systems and cloud-native AI platforms across Azure and AWS.
The ideal candidate will have experience designing and deploying scalable AI applications secure multi-agent systems and enterprise-grade AI infrastructure in production environments.
Key Responsibilities
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Design and implement enterprise-scale RAG pipelines using Azure AI Search vector databases embeddings semantic/hybrid search and re-ranking strategies.
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Develop secure conversational AI and multi-agent solutions using frameworks such as:
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Semantic Kernel
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AutoGen
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LangChain
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CrewAI
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Microsoft Agent Framework
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Build and integrate Model Context Protocol (MCP) services with governance RBAC audit logging and secure tool-calling capabilities.
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Develop scalable ingestion ETL/ELT and vectorization pipelines using Azure and AWS data platforms.
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Work with Azure AI Agent Service and cloud-native AI infrastructure across Azure and AWS ecosystems.
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Optimize LLM performance latency safety and operational cost through evaluation frameworks and monitoring.
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Implement CI/CD pipelines automated testing observability and security best practices for AI workloads.
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Collaborate with cross-functional teams including engineering product security and platform teams.
Required Qualifications
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6 years of software engineering experience with strong development fundamentals.
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2 years of hands-on experience with GenAI/LLM technologies in production environments.
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Strong programming experience in:
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Python
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C#
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.NET
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Experience building enterprise AI applications using:
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RAG architectures
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Vector databases
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Embeddings and semantic search
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Multi-agent orchestration
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Hands-on experience with Azure technologies including:
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Azure OpenAI
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Azure AI Search
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Azure ML
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AKS
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Azure Functions
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Azure Data Factory
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Azure Databricks
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Experience with AWS services such as:
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Bedrock
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SageMaker
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Lambda
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API Gateway
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EKS
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EMR
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Strong understanding of:
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Distributed systems
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Secure coding practices
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CI/CD
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Performance optimization
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AI governance and observability
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Preferred Qualifications
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Experience with Hugging Face MLflow Ollama vLLM or Triton.
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Knowledge of vector search optimization (HNSW/IVF) and GPU scheduling.
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Experience with Responsible AI governance and AI safety frameworks.
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Familiarity with multi-cloud AI deployments and Kubernetes-based AI infrastructure.
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Relevant cloud and AI certifications are a plus.