Senior AI Engineer (Generative AI / RAG / Agentic AI)

Globenet Consulting Corp

Senior AI Engineer (Generative AI / RAG / Agentic AI)

Bellevue, WA
Full Time
Paid
  • Responsibilities

    Benefits:

    Competitive salary

    Opportunity for advancement

    Training & development

    Role: Senior AI Engineer (Generative AI / RAG / Agentic AI)

    Location: Washington, DC (Onsite 4 days/week)

    About The AES Group

    The AES Group is a technology staffing and services company delivering high-impact solutions across cloud, data, AI, and emerging technologies for enterprise environments.

    What We Offer

    Competitive pay aligned to performance and outcomes

    Lead cutting-edge Generative AI initiatives at scale

    Career growth through advanced platforms and modern engineering practices

    Collaborative culture where your work is visible and valued

    About the Role

    We are seeking a Senior AI Engineer to architect and deliver secure, scalable, production-grade Generative AI solutions. You will design and implement RAG systems, agentic AI orchestration, and cloud-native ML infrastructure across Azure and AWS. This role blends hands-on engineering with technical leadership, including mentoring and setting reusable engineering standards.

    Responsibilities

    Architect and deliver enterprise GenAI, RAG, and conversational AI solutions end-to-end

    Design scalable retrieval, prompting, and inference patterns across Azure and AWS

    Build ingestion, enrichment, vectorization, and feature pipelines using Databricks, ADF, and EMR

    Implement embedding quality checks, drift monitoring, and metadata governance

    Engineer secure multi-agent/tool-calling systems using modern agent frameworks and MCP controls

    Establish evaluation, safety guardrails, CI/CD, automated testing, and observability for AI workloads

    Apply secure AI engineering practices, including threat modeling and compliance-aligned controls

    Lead design reviews, code reviews, and mentor engineers; create reference architectures and playbooks

    Qualifications

    Bachelor’s in CS/Engineering (Master’s preferred)

    8+ years of software engineering experience

    2+ years building applied Generative AI solutions (RAG, agents, evaluation/safety) in production

    Technical Stack (Required)

    Azure: Azure OpenAI, Azure AI Search, Azure AI Agent Service, Azure ML, AKS, ADF, Databricks, Functions, API Mgmt, Key Vault, App Insights AWS: SageMaker, Bedrock, Lambda, API Gateway, S3, CloudWatch, EMR, EKS, CodePipeline, Outposts Vector/Indexing: Azure AI Search, Redis, FAISS, HNSW, IVF Frameworks: Semantic Kernel, AutoGen, Microsoft Agent Framework, CrewAI, Agno, LangChain, MCP, Hugging Face Languages: Python, C#, .NET, TypeScript Inference/Deploy: Docker, vLLM, Triton, Ollama, quantized Llama (GGUF), GPU scheduling, multimodal pipelines MLOps/Platform: MLflow, evaluation tooling, guardrails, Azure DevOps pipelines, Kubernetes, hybrid/multi-cloud

    Certifications (Required)

    AI-900, DP-900, Responsible AI Certification, AWS ML Specialty, TensorFlow Developer, CKA/CKAD, SAFe Agile Software Engineering

    Certifications (Preferred)

    AI-102, DP-100, AZ-305, AZ-204

    Ready to make an impact? Apply now and join us on our journey!