Senior AI Engineer

Systems Innovation Engineering

1d

About The Position

We are looking for a Senior AI Engineer to work alongside our balanced agile delivery teams on highly complex DoD projects, specifically developing AI-powered DevSecOps processes that accelerate the velocity of development and testing of our mission planning and decision support systems. Hypergiant with its partners is building innovative agentic AI solutions that leverage cloud-based AI platforms and custom model context protocol (MCP) connectors to seamlessly integrate existing capabilities and processes to orchestrate application creation . An ideal candidate is able to design and implement custom agentic workflows, build and deploy MCP connectors for containerized services, and ensure system security and reliability. This position will work alongside our infrastructure and security teams on highly complex DoD projects.

Requirements

• At least 5+ years of professional software engineering experience with a focus on Python and TypeScript/JavaScript
• Proven experience building and deploying production AI systems, custom integrations, and agentic workflows using LLM-based platforms
• Hands-on experience with Model Context Protocol (MCP) architecture or similar plugin/connector frameworks and workflow orchestration tools (n8n, Airflow, LangGraph) for complex AI pipelines
• Demonstrated expertise with containerization technologies (Docker, Kubernetes) and cloud-native deployment patterns for scalable AI systems
• Solid understanding of Amazon Web Services cloud platform including their native AI/ML services, vector databases, graph databases, and observability solutions
• Experience with RESTful API design, GraphQL, and event-driven architectures across multiple LLM providers (OpenAI, Anthropic, Bedrock, Groq)
• Experience with advanced prompt engineering techniques and specialized knowledge of ensemble prompting strategies for effectively combining and synthesizing outputs from multiple LLM models
• Proficient with infrastructure-as-code tools (e.g., terraform)
• Experience with CI/CD pipelines and automated deployment strategies
• Familiarity with security best practices for AI systems, including authentication, authorization, logging, and data encryption
• Strong understanding of microservices architecture and distributed systems
• Proficient with version control systems (e.g., Git) and effective collaborative development workflows
• Must be a US Citizen and eligible to obtain and maintain a US Security Clearance

Nice To Haves

• Experience building custom LLM integrations, RAG architectures, or AI agent frameworks beyond standard implementations using frameworks such as LangChain
• Familiarity with graph databases and advanced vector database optimization techniques
• Experience with specialized LLM evaluation frameworks and benchmarking methodologies, including tools like LangFuse
• Experience with monitoring and observability tools (Datadog, New Relic, Prometheus/Grafana)
• Familiarity with design and documentation tools for creating system architecture diagrams
• Experience with component development frameworks like Storybook
• Knowledge of Outline or similar documentation platforms for technical knowledge management
• Experience with project management and issue tracking tools such as Jira
• A portfolio of past AI projects or MCP connector repositories with code samples or GitHub links
• Experience auditing third-party AI services and dependencies
• Familiarity with compliance frameworks relevant to AI systems (CMMC, FedRAMP)
• Penchant for learning new AI technologies and frameworks, balanced with strong organizationally-minded thinking
• Ability to make effective architecture decisions for AI systems and document them clearly
• Design-minded attention to detail in user interface implementation for AI-powered applications
• Ability to travel as needed
• Active Security Clearance

Responsibilities

• Build and deploy custom model context protocol (MCP) connectors for new and existing services
• Design and implement custom agentic workflows using cloud AI platforms
• Develop server-side application logic and APIs that integrate AI capabilities with existing enterprise systems
• Contribute to the development and maintenance of reusable AI component libraries and shared code infrastructure
• Write high-quality code, applying best practices, coding standards, and design patterns for AI systems
• Participate in the entire AI solution lifecycle, including requirement gathering, design, development, testing, and deployment, using an agile, iterative process
• Participate in code reviews and ensure code quality through effective testing strategies and security validation
• Collaborate with infrastructure teams, security teams, developers, designers, testers, project managers, product managers, and project sponsors
• Communicate tasking estimation and progress regularly to a development lead and product owner through appropriate tools
• Ensure seamless integration with backend systems, cloud services, databases and messaging systems
• Team with other developers, fostering a culture of continuous learning and professional growth in AI engineering

Benefits

• Paid Time Off
• Paid Company Holidays
• Medical, Dental & Vision Insurance
• Optional HSA and FSA
• Base and Voluntary Life Insurance
• Short Term & Long-Term Disability Insurance
• 401k Matching
• Employee Assistance Program

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed