**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