AI Engineer

General Dynamics Information Technology is a global technology and professional services company that delivers consulting, technology and mission services. As an AI Engineer, you will be responsible for designing, developing, and deploying AI models and systems to enhance productivity and decision-making within the organization.

Responsibilities:

• 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 enhances 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
• Must stay updated on emerging AI related technologies and recommend improvements to existing AI systems

Requirements:

• Education: Bachelor's Degree in Computer Science, Computer Engineering, Data Science or a related field
• Experience: 5+ years of experience in AI and machine learning, including hands-on experience with designing, developing, and deploying AI models and systems
• 1+ years of experience developing products or functional prototypes using RAG and agentic AI technologies
• Proven track record of delivering end-to-end AI projects and successfully integrating AI solutions into business processes
• Proficiency in programming languages such as Python, R, or Java
• Deep understanding of machine learning frameworks like TensorFlow or PyTorch
• Strong hands-on experience with MCP, LangGraph, LlamaIndex, or similar agentic frameworks
• Deep understanding of prompt or context engineering, tool definition, and state management for agents
• Experience with cloud computing platforms, such as Azure, OCI, AWS, or Google Cloud, including AI services like Azure AI Foundry, Bedrock, or Vertex AI
• Strong background in working with large datasets and performing data preprocessing, feature engineering, and model evaluation
• Masters degree
• Advanced coursework or a Certification in AI, Machine Learning or related areas desirable