Agentic AI Engineer

Job Description

As an Agentic AI Engineer, you will design, develop, and deploy AI models, algorithms, and systems to enhance productivity, decision‑making, and automation within the organization.

• Architect and implement production‑grade multi‑agent AI solutions with modern orchestration frameworks, enabling reliable, transparent, and secure agentic workflows.
• Build and maintain end‑to‑end agentic AI pipelines, from data ingestion and embedding to deployment and continuous evaluation, optimized for reusability and scalability.
• Develop, test, and deploy internal AI applications that enhance people‑powered, AI‑enabled productivity.
• Provide unified observability with logging, metrics, and alerts, and analyze agent runtime behavior to tune latency, accuracy, and cost in production.
• Integrate agentic AI services with existing enterprise systems and uphold AIOps practices for consistent deployment and scaling.
• Collaborate with cross‑functional teams including data scientists, software engineers, and product/service owners to align AI projects with business goals.
• Stay updated on emerging AI‑related technologies and recommend improvements to existing AI systems.

• Bachelor’s degree in Computer Science, Computer Engineering, Data Science, or a related field.
• 5+ years of experience in AI and machine learning, including hands‑on design, development, and deployment of AI models and systems.
• At least 1 year of experience developing products or functional prototypes using Retrieval‑Augmented Generation (RAG) and agentic AI technologies.
• Hands‑on experience designing or implementing an agentic workflow solution (beyond prompt engineering).
• Proficiency in Python, and knowledge of R or Java as applicable.
• Deep understanding of machine‑learning frameworks such as Tensor Flow or PyTorch.
• Experience with agentic frameworks such as MCP, Lang Graph, Llama Index or equivalent.
• Strong background in prompt or context engineering, tool definition, and state management for agents.
• Experience with cloud computing platforms (Azure preferred, OCI, AWS, or Google Cloud) and associated AI services.
• Strong background in working with large datasets, preprocessing, feature engineering, and model evaluation.
• Preferred:
  Master’s degree or advanced coursework/certification in AI or machine learning.

Remote – United States.

$161,500 – $218,500, with compensation based on experience, geographic location, and contractual terms.

Competitive pay, paid time off, 401(k) with company match, medical/dental/vision plans, and additional benefits as described by GDIT.

Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans.