More jobs:
AI Engineer – Level II
Job in
Washington, District of Columbia, 20022, USA
Listed on 2026-02-23
Listing for:
Data Freelance Hub
Full Time
position Listed on 2026-02-23
Job specializations:
-
Software Development
AI Engineer, Machine Learning/ ML Engineer
Job Description & How to Apply Below
Overview
AI Engineer – Level II in Washington, DC. Contract position, pay $85.00 - $90.00 per hour. Requires 5+ years software engineering and 2+ years GenAI/LLM, expertise in Azure and AWS tools, relevant certifications.
Job DetailsLocation:
Washington, DC (Onsite)
Experience:
5+ years in software engineering; 2+ years GenAI/LLM
Pay: $85-90/hour
Type:
Contract
As 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 Responsibilities- AI 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 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, Auto Gen, CrewAI, Lang Chain;
Apply governance and lifecycle management for agent runtimes;
Fine-tune models, conduct A/B testing, and implement CI/CD pipelines with validation.
- Strong CS fundamentals: distributed systems, algorithms, concurrency, networking
- SDLC excellence: clean architecture, SOLID, testing frameworks
- Secure development: input validation, secret hygiene, sandboxing
- Performance tuning: latency optimization, vector index profiling
- Expertise in RAG, embeddings, transformer models, and multi-modal pipelines
- Production-level C#, Python, .NET;
Type Script 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
- Azure:
OpenAI, AI Search, AML, AKS, ADF, Azure Batch, Databricks, Key Vault - AWS:
Sage Maker, Bedrock, EMR, Lambda, API Gateway, S3, EKS, Comprehend - Vector DBs:
Redis, FAISS, HNSW;
Azure AI Search - Frameworks:
Lang Chain, Semantic Kernel, Auto Gen, Microsoft Agent Framework, CrewAI - Inference:
Docker/Ollama, vLLM, GGUF quantization, GPU provisioning
- Microsoft Certified:
Azure AI Fundamentals (AI-900) - Microsoft Certified:
Azure Data Fundamentals (DP-900) - AWS Machine Learning Specialty
- Tensor Flow Developer
- Kubernetes CKA/CKAD
- SAFe Agile Software Engineering
- Azure AI Engineer (AI-102), Data Scientist (DP-100), Architect (AZ-305), or Developer (AZ-204) certifications
- Experience with MLflow, Hugging Face, vector tuning (HNSW/IVF)
- Responsible AI playbooks, incident response frameworks
- CI/CD for AI (Azure Dev Ops, AWS Code Pipeline), hybrid deployments (Azure Arc, AWS Outposts)
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