Senior Agentic AI/ML Engineer

Senior Agentic AI/ML Engineer

Iron EagleX is seeking a Senior Agentic AI/ML Engineer to support our AI team in Crystal City, VA. This role will design, develop, deploy, and sustain machine learning, artificial intelligence, and agentic AI capabilities that support advanced analytics, automation, and mission-focused decision-making. The AI/ML Engineer will work across the full AI development lifecycle, including data preparation, model development, agentic workflow design, evaluation, integration, deployment, and operational sustainment.

Meaningful Work and Personal Impact: As a Senior Agentic AI/ML Engineer, you will be a core member of the AI team responsible for building practical, reliable, and scalable AI, machine learning, and agentic AI solutions. You will help transform complex data, emerging AI concepts, and mission needs into production-ready capabilities that improve workflows, enhance analytics, automate complex tasks, and support mission outcomes.

Job Duties (Include But Are Not Limited To):

• Design, develop, train, evaluate, and deploy machine learning models to support mission and business use cases.
• Develop clean, maintainable, and efficient Python code while adhering to best practices and coding standards.
• Build and maintain AI/ML pipelines for data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.
• Design, develop, and integrate modern AI model capabilities into applications and workflows, including prompting, tool calling, RAG, structured outputs, and agentic patterns.
• Develop and support agentic AI workflows that can reason over tasks, use tools, retrieve relevant information, execute multi-step processes, and interact with external systems under defined controls and guardrails.
• Evaluate agentic systems for accuracy, reliability, safety, task completion, tool-use effectiveness, latency, and operational suitability.
• Support the development of AI-enabled applications, analytics tools, automation capabilities, and decision-support systems.
• Collaborate with data engineers, software engineers, analysts, and stakeholders to define requirements and deliver effective AI/ML and agentic AI solutions.
• Design, develop, and integrate APIs, services, and external tools to enable AI/ML and agentic capabilities within larger software systems.
• Establish and maintain reproducible environments, CI/CD workflows, and container-based deployments using tools such as Docker.
• Work with structured and unstructured data sources to ensure data quality, integrity, usability, and performance.
• Implement and maintain version control using Git to streamline collaboration and code management.
• Ensure all developed solutions meet high standards for security, quality, reliability, explainability, and maintainability.
• Contribute to all stages of the AI/ML, agentic AI, and software development life cycles, from concept and experimentation through testing, deployment, monitoring, and sustainment.

Required Skills:

• Proficiency in Python and commonly used AI/ML libraries and frameworks.
• Hands-on experience developing, training, evaluating, and deploying machine learning models.
• Strong understanding of supervised learning, unsupervised learning, model evaluation, feature engineering, and data preprocessing techniques.
• Experience working with structured and/or unstructured data in support of analytics or AI/ML use cases.
• Familiarity with modern AI and language model concepts, including prompting, embeddings, retrieval-augmented generation, structured outputs, tool calling, and model evaluation.
• Experience designing, developing, or integrating agentic AI workflows or applications using LLMs, tools, APIs, memory, retrieval, and multi-step task execution.
• Understanding of agentic AI concepts, including task planning, goal decomposition, tool selection, orchestration, human-in-the-loop review, guardrails, and evaluation of agent behavior.
• Experience designing or supporting AI/ML pipelines and reproducible development environments.
• Understanding of MLOps concepts, including model versioning, experiment tracking, model registry, CI/CD, monitoring, and deployment of ML-enabled systems.
• Familiarity with LLMOps or agent operations concepts, including prompt/version management, evaluation datasets, observability, traceability, safety controls, and monitoring of deployed AI systems.
• Familiarity with RESTful APIs and integrating AI/ML or agentic AI capabilities into software applications, workflows, or enterprise systems.
• Proficiency with Git-based version control and collaborative software development workflows.
• Familiarity with containerization tools such as Docker.
• Ability to work effectively both independently and collaboratively in a fast-paced environment.
• Strong problem-solving skills and the ability to translate complex technical concepts into practical, secure, and mission-relevant solutions.

Desired Skills:

• Experience with PyTorch, TensorFlow, scikit-learn, MCP, Google ADK, A2A, LangChain, LangGraph, or similar AI/ML and agentic AI frameworks and tools.
• Experience building or supporting LLM-powered applications, including chat-based interfaces, agentic workflows, tool calling, retrieval-augmented generation, workflow automation, or multi-agent systems.
• Experience designing agents that interact with external tools, APIs, databases, knowledge bases, or enterprise systems.
• Familiarity with agentic design patterns such as planner-executor, router, evaluator, reflection, tool-using agents, multi-agent collaboration, and human-in-the-loop escalation.
• Familiarity with vector databases, semantic search, embeddings, and knowledge retrieval systems.
• Experience evaluating LLM and agentic AI systems using automated evaluations, benchmark datasets, human review, red teaming, or operational performance metrics.
• Experience with cloud-native AI/ML development or deployment environments.
• Experience with Docker and Kubernetes for scalable deployment of AI/ML and agentic AI workloads.
• Familiarity with data engineering concepts, including ETL workflows, data validation, and data pipeline orchestration.
• Experience with relational databases such as PostgreSQL.
• Experience with DevSecOps practices, secure software delivery, or mission-focused software environments.
• Familiarity with AI safety, security controls, data protection, and governance considerations for deployed AI and agentic systems.

What You'll Need to Succeed:

• Clearance: Current TS/SCI Clearance with current or willingness to obtain CI polygraph
• Experience: 10+ years of related experience
• Education: Bachelor's degree in Computer Science, Software Engineering, or a related field (or equivalent experience)
• Role requirements: Work is onsite in Crystal City, VA with optional CONUS travel
• Due to US Government Contract Requirements, only US Citizens are eligible for this role

GDIT is your place. At GDIT, the mission is our purpose, and our people are at the center of everything we do.

• Growth: AI-powered career tool that identifies career steps and learning opportunities
• Support: An internal mobility team focused on helping you achieve your career goals
• Rewards: Comprehensive benefits and wellness packages, 401K with company match, competitive pay and paid time off
• Community: Award-winning culture of innovation and a military-friendly workplace