AI Engineer Level I

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ChaTeck Incorporated
Washington, DC, United States
  • Production
  • Applications have closed

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

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