AI Engineer – Level II

AI Engineer – Level II Location: Washington, DC (Onsite)Experience: 5+ years in software engineering | 2+ years in GenAI/LLM systems Why This Role?Join a high-impact AI team building secure, scalable GenAI systems. Gain exposure to: Cutting-edge RAG and agentic AI architectures Azure and AWS AI ecosystems Multi-modal LLM integration across vision and speech Production-grade CI/CD for AI/ML workloads Fast-tracked certifications and career growth Role SummaryAs an AI Engineer (Level II), you’ll design, implement, and optimize enterprise-scale AI systems. You’ll lead architecture, agent orchestration, and model integration while collaborating with cross-functional teams to deliver production-ready solutions. Key ResponsibilitiesAI Architecture & Delivery Design RAG pipelines using Azure AI/Search, Redis, FAISS, HNSW Build conversational systems with prompt lifecycle management and telemetry Integrate LLMs like Azure OpenAI, Claude, Llama, and open-source models Infrastructure & Orchestration Deploy Model Context Protocol (MCP) servers with RBAC and audit trails Implement Azure AI Agent Service patterns for agent registry and policy enforcement Use Azure Batch and AWS EMR for scalable inferencing and processing Data Pipeline Engineering Build ingestion pipelines with PII redaction, metadata enrichment, SLA tracking Operate vectorization pipelines with quality gates and drift detection Leverage ADF, Databricks, and EMR for scalable workflows Agentic AI & Model Ops Orchestrate multi-agent workflows using Semantic Kernel, AutoGen, CrewAI, LangChain Apply governance and lifecycle management for agent runtimes Fine-tune models, conduct A/B testing, and implement CI/CD pipelines with validation Core Competencies Strong CS fundamentals: distributed systems, algorithms, concurrency, networking SDLC excellence: clean architecture, SOLID principles, testing frameworks Secure development: input validation, secret hygiene, sandboxing Performance tuning: latency optimization, vector index profiling Required Skills Expertise in RAG, embeddings, transformer models, and multi-modal pipelines Production-level C#, Python, .NET; TypeScript for service/UI (as needed) Experience with Azure and AWS AI tools and operations Familiarity with fine-tuning, safety tooling, model traceability Strong delivery skills: architecture, stakeholder alignment, roadmap execution Tools & Platforms Azure: OpenAI, AI Search, AML, AKS, ADF, Azure Batch, Databricks, Key Vault AWS: SageMaker, Bedrock, EMR, Lambda, API Gateway, S3, EKS, Comprehend Vector DBs: Redis, FAISS, HNSW, Azure AI Search Frameworks: LangChain, Semantic Kernel, AutoGen, Microsoft Agent Framework, CrewAI, Agno Inference: Docker/Ollama, vLLM, GGUF quantization, GPU provisioning Required Certifications Microsoft Certified: Azure AI Fundamentals (AI-900) Microsoft Certified: Azure Data Fundamentals (DP-900) Responsible AI certification AWS Machine Learning Specialty TensorFlow Developer Kubernetes CKA/CKAD SAFe Agile Software Engineering Preferred (Bonus) Azure AI Engineer (AI-102), Data Scientist (DP-100), Architect (AZ-305), or Developer (AZ-204) Experience with MLflow, Hugging Face, vector tuning (HNSW/IVF) Responsible AI playbooks, incident response frameworks CI/CD for AI (Azure DevOps, AWS CodePipeline), hybrid deployments (Azure Arc, AWS Outposts) Step into a role where AI meets cloud scalability. Apply now and help shape tomorrow’s AI systems. Job Type: Contract Pay: $85.00 - $90.00 per hour Work Location: In person