Role: AI Engineer – Level I

Locations: Washington, DC - onsite

Position Summary

As an entry-level AI Engineer, you will support the development of scalable, secure AI systems with a focus on Retrieval-Augmented Generation (RAG), agentic AI, and cloud-based infrastructure. You will work under guidance to implement foundational components, contribute to data pipelines, and gain hands-on experience with Azure and AWS technologies.

Key Responsibilities

Support AI Solution Development

Assist in building RAG pipelines using Azure AI/Search and vector DBs (e.g., Redis, FAISS).
Participate in developing conversational AI features: chunking, embedding, re-ranking, citation formatting.
Collaborate on integrating multi-modal models (Azure OpenAI, OSS LLMs) with prompt routing and basic guardrails.

AI Infrastructure Integration

Learn to deploy Model Context Protocol (MCP) servers and implement RBAC, audit trails, and validation mechanisms.
Contribute to agent orchestration patterns using Azure AI Agent Service, gaining exposure to policy enforcement.

Data Pipeline Contribution

Support ingestion and ETL/ELT processes: document normalization, metadata tagging, PII redaction.
Use Azure Data Factory and Databricks for scalable, orchestrated data processing workflows.

Model Operations & Optimization

Assist in model evaluations, safety checks, and offline testing suites.
Participate in implementing CI/CD pipelines with basic security scans and performance logging.

Core Engineering Skills

Familiar with CS fundamentals: algorithms, data structures, distributed systems.
Exposure to SDLC best practices: clean code, SOLID principles, testing patterns.
Awareness of secure coding principles and performance optimization techniques.

Tech Stack Exposure

Azure: Azure OpenAI, AI/Search, AML, Functions, Key Vault, ADF, Databricks

AWS: SageMaker, Bedrock, Lambda, API Gateway, S3, EMR

Vector DBs: Azure AI Search, Redis, FAISS

Frameworks: Semantic Kernel, AutoGen, LangChain (beginner level)

Local Inference: Docker/Ollama for running small LLMs

Qualifications

Education: Bachelor’s in CS, Engineering, Data Science, or equivalent hands-on learning

Experience: 2+ years in software engineering, with exposure to GenAI concepts and cloud services

Certifications (Required for Level I)

Microsoft Certified: Azure AI Fundamentals (AI-900)
Microsoft Certified: Azure Data Fundamentals (DP-900)
Responsible AI awareness or certification
AWS Machine Learning Specialty (preferred for Level I)
TensorFlow Developer, Kubernetes CKA/CKAD (plus)

Required Skills

Understanding of RAG workflows, embeddings, vector databases
Basic implementation of agent orchestration and prompt management
Proficient in Python and C# for backend development
Exposure to LLM integration, fine-tuning, and safety evaluation
Comfortable working in Agile teams with cross-functional collaboration

Ready to grow your AI career? Apply now and contribute to impactful enterprise AI solutions

The AES Group AI Jobs

Latest AI Jobs at The AES Group

AI Engineer Level I