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AI Engineer – Level II

Job in Washington, District of Columbia, 20022, USA
Listing for: Data Freelance Hub
Full Time position
Listed on 2026-02-23
Job specializations:
  • Software Development
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 85 - 90 USD Hourly USD 85.00 90.00 HOUR
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 Details

Location:

Washington, DC (Onsite)

Experience:

5+ years in software engineering; 2+ years GenAI/LLM

Pay: $85-90/hour

Type:
Contract

Role Summary

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.
Core Competencies & Required Skills
  • 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
Tools & Platforms
  • 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
Certifications
  • 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
Bonus / Preferred
  • 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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