Senior AI Engineer

Position Title: Senior AI Engineer
Location: Washington DC Onsite, 4 days in a week

Let's create our future together at The AES Group!

About The AES Group

The AES Group is a premier technology staffing and services company that has been bringing businesses and talent together for over 20 years to deliver innovative technology solutions that create meaningful impact. AES helps enterprises, including Fortune 500 organizations, engage customers, empower employees, and transform operations through cloud, data, AI, and emerging technologies.

About the Role

We are seeking a senior-level AI Engineer to architect, lead, and deliver scalable, secure Generative AI solutions with enterprise-grade performance. This role focuses on Retrieval-Augmented Generation (RAG), agentic AI orchestration, and cloud-native ML infrastructure across Azure and AWS.

The ideal candidate combines deep hands-on engineering expertise with solution architecture leadership, ensuring AI platforms are secure, observable, cost-efficient, and aligned to measurable business outcomes. This role also includes mentoring engineers and elevating overall team capability.

Key Responsibilities

AI Architecture & Solution Delivery

• Architect and deliver enterprise GenAI, RAG, and conversational AI solutions end-to-end.
• Design scalable retrieval, prompting, and inference patterns across Azure and AWS.
• Align AI solution design with business goals, security requirements, and performance targets.

AI Data, RAG & Feature Engineering Pipelines

• Lead ingestion, normalization, enrichment, and vectorization of AI knowledge sources.
• Implement embedding quality controls, drift monitoring, and metadata governance.
• Build and optimize scalable AI data and feature pipelines using Databricks, ADF, and EMR.

Agentic AI & Platform Engineering

• Engineer secure multi-agent and tool-calling systems using modern agent frameworks.
• Implement MCP and policy controls for agent safety, traceability, and runtime governance.
• Design governed AI platforms with registry, broker, telemetry, and access controls.

Model Operations, Security & Governance

• Evaluate and optimize models for quality, safety, latency, and cost efficiency.
• Establish CI/CD, automated testing, guardrails, and observability for AI workloads.
• Apply secure AI engineering practices including threat modeling and compliance controls.

Technical Leadership & Mentorship

• Lead engineering execution, agile delivery, and cross-functional technical collaboration.
• Mentor and coach engineers through design reviews, code reviews, and best practices.
• Build reusable standards, reference architectures, and engineering playbooks.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field required; Master's preferred.
• 8+ years of software engineering experience.
• 2+ years hands-on experience in applied Generative AI including RAG, agent systems, and model evaluation/safety.
• Proven experience delivering production AI systems in regulated or enterprise environments with the following technology stack:

• Azure: Azure OpenAI, Azure AI Search, Azure AI Agent Service, Azure ML, AKS, Azure Batch, Azure Data Factory (ADF), Azure Databricks, Azure Functions, API Management, Key Vault, App Insights, Azure Arc
• AWS: SageMaker, Bedrock, Lambda, API Gateway, Comprehend, S3, CloudWatch, EMR, EKS, AWS Outposts, AWS CodePipeline
• Vector DBs: Azure AI Search, Redis, FAISS, HNSW, IVF indexing
• Frameworks: Semantic Kernel, AutoGen, Microsoft Agent Framework, CrewAI, Agno, LangChain, Model Context Protocol (MCP), Hugging Face
• Languages & Application Stack: Python, C#, .NET, TypeScript
• Inference: Docker, Ollama, vLLM, Triton, quantized Llama (GGUF), edge inference, GPU provisioning, GPU scheduling, multi-modal pipelines, dynamic model routing
• MLOps & AI Tooling: MLflow, AI evaluation suites, safety and guardrail tooling, CI/CD for AI workloads, Azure DevOps pipelines
• Platforms & Orchestration: Kubernetes, containerized GPU workloads, hybrid/multi-cloud deployments

Certifications Required

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

Certifications Preferred

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

What We Offer

• Competitive pay aligned to performance and outcomes
• Opportunities to lead cutting-edge AI initiatives
• Professional growth with industry-leading clients and technologies
• Open, collaborative culture where your impact is visible and valued

Join The AES Group and help build the next generation of enterprise AI platforms. Apply now.