AI Engineer Level III

Benefits

• Competitive salary
• Opportunity for advancement
• Training & development

AI Engineer – Level III

Location:

Washington, DC (Onsite)

Experience:

8+ years in software engineering | 2+ years in applied GenAI

Step into a senior engineering role where you’ll shape high-impact GenAI systems. Lead innovation across:

• RAG pipelines and multi-agent orchestration
• Azure and AWS-based GenAI platforms
• Model governance, safety, and CI/CD for LLM workloads
• Multi-modal model deployment at scale
• Strategic delivery aligned with real-world enterprise impact

As a Level III AI Engineer, you’ll own the architecture and execution of secure, scalable AI systems. You will lead technical delivery across RAG pipelines, agent frameworks, model ops, and cloud-based ML workflows. This role demands deep hands-on expertise and cross-functional leadership.

• AI Architecture & Delivery:
  Lead design of RAG pipelines using Azure AI Search, Redis, FAISS, HNSW;
  Deliver multi-turn conversational systems with prompt lifecycle, telemetry, and guardrails;
  Integrate LLMs (Azure OpenAI, Claude, Llama, OSS) with dynamic routing for cost/safety balance
• Infrastructure & Orchestration:
  Deploy MCP servers with RBAC, audit logging, version control, and rate limiting;
  Implement agent frameworks using Azure AI Agent Service (registry, policy enforcement, telemetry);
  Operate large-scale inferencing via Azure Batch and AWS EMR
• Data & Feature Pipelines:
  Lead ingestion pipelines: document normalization, metadata tagging, PII redaction, SLA/SLO tracking;
  Operate vectorization workflows with drift detection and quality gates;
  Architect scalable data flows using ADF, Databricks, and EMR
• Agentic AI Development:
  Orchestrate multi-agent systems with Semantic Kernel, Auto Gen, CrewAI, Lang Chain, Agno;
  Govern agent runtimes using MCP controls for security and traceability
• Model Ops & Governance:
  Evaluate and fine-tune models; run A/B testing and latency-cost analysis;
  Build secure CI/CD pipelines with integrated testing, scans, and trace logging;
  Enforce Dev Sec Ops  and AI threat modeling for LLM workloads

• Deep CS knowledge: distributed systems, concurrency, performance tuning
• Expert in SDLC: clean architecture, SOLID, layered testing, Dev Sec Ops  practices
• Secure AI app delivery: sandboxed tools, secrets hygiene, token/cost profiling
• Agile leadership: drive sprints, lead technical planning, manage RACI across teams

• Proficient in GenAI systems: embeddings, transformer models, vector DB indexing
• Production-level expertise in Python, C#, .NET, and Type Script (as needed)
• Hands-on with Azure and AWS tools: AML, AKS, Databricks, Sage Maker, EMR, EKS
• Strong in model traceability, safety tooling, fine-tuning, and runtime observability
• Strategic execution: solution architecture, roadmap alignment, delivery metrics

• Azure:
  Azure OpenAI, AI Search, AML, AKS, ADF, Azure Batch, Databricks, Key Vault, App Insights
• AWS:
  Sage Maker, Bedrock, Lambda, EMR, API Gateway, Comprehend, S3, Cloud Watch, EKS
• Vector DBs:
  Redis, FAISS, HNSW, Azure AI Search
• Frameworks:
  Lang Chain, Semantic Kernel, Auto Gen, Microsoft Agent Framework, CrewAI, Agno
• Inference:
  Docker/Ollama, vLLM, Triton, GGUF quantization, GPU provisioning, edge AI

• Azure AI Fundamentals (AI-900), Data Fundamentals (DP-900)
• Responsible AI certifications
• AWS Machine Learning Specialty
• Tensor Flow Developer
• Kubernetes CKA or CKAD
• SAFe Agile Software Engineering

• Azure AI Engineer (AI-102)
• Azure Data Scientist (DP-100)
• Azure Solutions Architect (AZ-305)
• Azure Developer Associate (AZ-204)

Ready to lead AI at scale? Apply now and help architect the future of enterprise intelligence.