AI / ML Developer

HYERTEK INC•Rockville, MD

just now

About The Position

HyerTek is seeking an experienced and passionate AI Developer to provide technical direction and leadership in the architecture, design, development, and delivery of modern AI solutions for our government clients. This role centers on building production-ready, AI-focused applications that extend Microsoft solutions, leverage frontier models via Microsoft Foundry, and align with the Department of War's enterprise generative AI platform, GenAI.mil. Our AI solutions focus on making the mission workforce more informed, effective, and engaged through intelligent automation, agentic workflows, and enhanced decision-making. Qualified candidates will combine deep knowledge of large language models and prompt engineering with strong architectural skills for scalable, secure AI systems in regulated government environments. We place particular emphasis on building governed LLM applications for the science, defense, and broader government domains, using OpenAI, Gemini, and Anthropic models delivered through Azure and integrated into Microsoft 365, Copilot, and the Power Platform. We value depth across the areas below and expect candidates to demonstrate experience in a meaningful subset of them.

Requirements

Must be a U.S. citizen.
Must be able to obtain DoD security clearance (Secret or Above).
Bachelor's degree in Computer Science, Data Science, AI/ML, or equivalent work experience.
5+ years of software development experience, with 2+ years focused on AI/ML applications and LLM integration.
Hands-on experience building applications with frontier large language models, specifically OpenAI GPT and Anthropic Claude, including an understanding of model selection and routing across providers.
Strong experience building Retrieval-Augmented Generation systems and semantic search applications.
Proficiency with vector and semantic retrieval using Azure AI Search, including embedding storage, indexing, and hybrid search.
Advanced prompt engineering skills with hands-on experience in function and tool calling and AI agent development.
Experience building AI orchestration and multi-step agent workflows, particularly with Semantic Kernel and Microsoft Foundry agent tooling.
Strong Python programming skills, with experience building AI APIs using FastAPI.
Experience with Microsoft Copilot Studio, Semantic Kernel, and custom or declarative copilot development.
Hands-on experience with cloud AI services, specifically Azure OpenAI and Microsoft Foundry model endpoints.
Proficiency with a modern frontend framework (React preferred) for AI application user interfaces, including those embedded in Microsoft and Power Platform experiences.
Experience with containerization (Docker) and orchestration (Kubernetes / Azure Kubernetes Service) for AI service deployment in accredited environments.
Working knowledge of embedding models, transformer architectures, and fine-tuning techniques.
Understanding of AI safety, responsible AI practices, and bias mitigation, with the ability to apply mission-grade guardrails consistent with Department of Defense standards.
Experience with version control, CI/CD pipelines (Azure DevOps or GitHub), and MLOps practices for AI system deployment.
Strong understanding of data preprocessing, document chunking, and knowledge management for RAG systems.
Familiarity with Agile development methodologies and experience working in collaborative AI delivery teams.

Nice To Haves

Familiarity with developing solutions in the context of GenAI.mil
Experience delivering on Microsoft Power Platform and Dataverse, and integrating AI capabilities into Microsoft 365 and Power Apps.
Hands-on experience in GCC High or other accredited government cloud environments.
Experience with AI orchestration frameworks such as LangChain or LlamaIndex.
Experience with open-source LLMs such as Llama, Mistral, or Falcon, and local or self-hosted model deployment.
Knowledge of model fine-tuning techniques, including LoRA, QLoRA, and PEFT methods.
Experience with multimodal AI applications combining text, image, and audio.
Familiarity with AI governance frameworks and compliance requirements for government applications.
Experience with the Hugging Face ecosystem, model deployment, and custom model training.
Knowledge of graph databases (such as Neo4j) for knowledge-graph applications.
Microsoft Azure AI certifications (for example, Azure AI Engineer Associate) or comparable cloud AI credentials.
Experience with real-time AI systems and streaming data processing.
Background in natural language processing, computer vision, or speech recognition.

Responsibilities

Architect and develop large language model applications using OpenAI GPT, Google Gemini, and Anthropic Claude models served through Microsoft Foundry, with a clear understanding of how to select and route between frontier models for a given mission workload.
Design and build solutions that align with and extend GenAI.mil, the Department of War's enterprise generative AI platform, including agentic workflows and use cases certified for Controlled Unclassified Information and Impact Level 5 environments.
Design and implement Retrieval-Augmented Generation systems using Microsoft-native components, including Azure AI Search for vector and semantic retrieval, document processing pipelines, and grounding strategies that reduce hallucination on authoritative mission data.
Build and customize Microsoft Copilot integrations, including Copilot Studio agents, declarative and custom copilots, and extensions developed with Semantic Kernel.
Develop AI orchestration and multi-step agent workflows on the Microsoft stack, integrating frontier models with Microsoft 365, Dataverse, and the Power Platform to automate complex mission and back-office processes.
Implement advanced prompt engineering, function and tool calling, and AI agent architectures for intelligent automation, with attention to evaluation, observability, and governance.
Design and deploy scalable AI APIs using Python and FastAPI, integrated with Azure OpenAI and Microsoft Foundry model endpoints, and packaged for deployment into GCC High and other accredited cloud environments.
Collaborate with data and mission subject-matter experts to tune retrieval, optimize prompts and context strategies, and continuously improve AI system performance against mission outcomes.
Take part in the Agile process and collaborate effectively within cross-functional AI delivery teams.
Build strong internal relationships, mentor others, and evangelize AI best practices, responsible AI guardrails, and emerging capabilities across customer organizations and internally.
Interpret client requirements and recommend optimal AI solutions, model selection, and implementation strategies for the Microsoft and GenAI.mil ecosystem.
Support full-lifecycle AI delivery from requirements gathering through deployment, accreditation support, and maintenance.