About the Role We're looking for an AI Engineer to join our team supporting the BioSurveillance Integration Platform (BIP), a mission-critical program delivering data-driven insight for biosurveillance, force health protection, and operational decision-making. You'll design, develop, integrate, and operationalize AI/ML capabilities that support mission analytics, automated workflows, decision support, and intelligent applications. You'll work alongside data engineers, data scientists, platform engineers, architects, and customer stakeholders to transform mission requirements and trusted data into secure, production-ready AI solutions. This role follows a phased work arrangement: fully remote during Phase 1 (stand-up and early build), transitioning to hybrid during Phase 2 to support integration, testing, and delivery milestones. What You'll Do Design, develop, test, and deploy AI/ML solutions supporting biosurveillance, mission analytics, decision support, and operational workflows Build AI-enabled applications and workflows using large language models (LLMs), machine learning models, and other AI technologies Develop and integrate AI agents, Retrieval-Augmented Generation (RAG) systems, and LLM-powered workflows Integrate AI capabilities with enterprise data platforms, APIs, mission applications, and existing data pipelines Develop prompt engineering, structured output, tool-calling, and agentic workflow capabilities for mission use cases Build evaluation frameworks to measure model accuracy, reliability, relevance, latency, and operational performance Implement safeguards, validation, monitoring, logging, and human-in-the-loop controls for production AI systems Optimize AI applications for performance, scalability, reliability, and cost Evaluate models, frameworks, and emerging AI technologies for suitability within mission and security requirements Collaborate closely with data engineers, data scientists, platform engineers, architects, and mission analysts to deliver production-ready AI capabilities Produce architecture documentation, model documentation, evaluation results, AI workflow diagrams, runbooks, and release documentation What You'll Need Bachelor's degree, or equivalent relevant experience Demonstrated experience developing AI/ML applications or AI-enabled software in a production or applied environment Proficiency in Python and experience with common AI/ML libraries and frameworks Experience working with LLMs, APIs, prompt engineering, or machine learning models Understanding of software engineering principles, REST APIs, Git, testing, and production deployment practices Experience integrating AI capabilities with structured and unstructured data Active Secret clearance , with ability to maintain it throughout the period of performance U.S. Citizenship Nice to Have Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related field Experience building agentic AI systems, RAG pipelines, vector search, tool-calling, or multi-agent workflows Experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar AI orchestration frameworks Experience with commercial and open-source LLMs, including OpenAI, Anthropic, Google, Meta Llama, or Mistral models Experience deploying and operating models using Azure AI, AWS Bedrock/SageMaker, Google Vertex AI, or similar platforms Experience with Palantir Foundry, Maven Smart System, or other federal-scale data and AI platforms Experience with vector databases and semantic search technologies Familiarity with MLOps/LLMOps practices including model evaluation, versioning, monitoring, observability, and deployment Experience implementing AI guardrails, model evaluation, responsible AI practices, and human-in-the-loop workflows Experience deploying AI capabilities in restricted, disconnected, on-premises, or air-gapped environments Prior experience on federal/DoD programs operating under the Risk Management Framework (RMF) Familiarity with healthcare or biosurveillance data such as HL7 v2, HL7 FHIR, or DoD medical reporting formats AI/ML or cloud certification from AWS, Microsoft Azure, Google Cloud, NVIDIA, or equivalent

Tools & Platforms AI/ML:

Python, PyTorch, TensorFlow, Hugging Face, OpenAI APIs, Anthropic APIs, LangChain, LangGraph, LlamaIndex Data & AI Platforms:

Palantir Foundry, Maven Smart System, Apache Spark, Databricks Cloud & MLOps:

AWS Bedrock/SageMaker, Azure AI, Google Vertex AI, Docker, Kubernetes Development & Collaboration:

Git, REST APIs, Jira, Confluence, Microsoft Office 365 Benefits 401(k) 401(k) matching Health insurance Life insurance Referral program

Pay:

$50,000.00 - $70,000.00 per year

Benefits:

401(k) 401(k) matching Health insurance Life insurance Referral program

Work Location:

Hybrid remote in Omaha, NE 68127