Role overview
*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.
What you'll work on
- 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
What we're looking for
- 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.
Tags & focus areas
Used for matching and alerts on DevFound Contract Ai Ai Engineer Generative Ai