Responsibilities
AI/ML Development and Integration
• Develop and integrate AI/ML capabilities into mission-focused web applications, including large language model (LLM) integration, retrieval-augmented generation (RAG) pipelines, and intelligent automation workflows
• Assist in the design and implementation of data ingestion, embedding, vector search, and model serving pipelines
• Support prompt engineering, model evaluation, and performance tuning for deployed AI features
• Research and prototype emerging AI/ML tools, frameworks, and techniques to identify opportunities for mission improvement
• Support the design and development of agentic AI systems, including autonomous agents capable of multi-step planning, tool use, and orchestrated task execution within mission workflows
Full-Stack Application Development
• Build and maintain web application features using modern frontend frameworks (e.g., React, TypeScript) and backend frameworks (e.g., Python, FastAPI)
• Design and implement RESTful APIs and contribute to database design and query optimization (e.g., PostgreSQL)
• Write clean, testable, and well-documented code following team coding standards and established design patterns
• Participate in code reviews, sprint planning, and collaborative development within an Agile workflow
CI/CD and DevSecOps
• Contribute to the development and maintenance of CI/CD pipelines for automated testing, security scanning, and deployment
• Support containerized application builds and deployments using Docker and container orchestration platforms (e.g., Kubernetes)
• Assist with static application security testing (SAST) integration and remediation of findings within the development pipeline
• Help maintain and improve infrastructure-as-code configurations and deployment automation scripts
Collaboration and Communication
• Collaborate with the AI and Automation team to plan, estimate, and deliver work in iterative development cycles
• Document technical designs, implementation decisions, and operational procedures for team and stakeholder reference
• Support demonstrations, briefings, and technical reviews for program leadership and government stakeholders
Required Qualifications
Education
• Bachelor's degree in Artificial Intelligence, Machine Learning, Computer Science, Data Science, Software Engineering, or a closely related technical field
Experience
• Professional experience in software development, AI/ML engineering, or a related technical role (internship and academic project experience considered)
Technical Skills
• Proficiency in Python and at least one modern web development language or framework (e.g., JavaScript/TypeScript, React)
• Foundational understanding of AI/ML concepts, including natural language processing (NLP), large language models (LLMs), embeddings, and vector search
• Experience with relational databases (e.g., PostgreSQL, MySQL, SQL Server) and RESTful API design
• Familiarity with version control systems (Git) and collaborative development workflows (branching strategies, merge requests, code reviews)
• Basic understanding of containerization (Docker) and container orchestration concepts (Kubernetes)
• Familiarity with CI/CD pipeline concepts and at least one CI/CD platform (e.g., GitLab CI/CD, GitHub Actions, Azure DevOps, Jenkins)
• Exposure to at least one cloud platform (AWS, Microsoft Azure, or Google Cloud) and general understanding of cloud-native application architecture
Security Clearance
• Active Secret security clearance
Certification
• Must obtain CompTIA Security+ certification (or equivalent DoD 8570/8140 baseline certification) within 30 days of start date
Work Environment
• On-site position at a U.S. government facility in Huntsville, AL
• Small, collaborative team environment with direct mentorship from senior engineers
• Opportunity to contribute to meaningful mission outcomes through hands-on engineering of AI-driven solutions
• Fast-paced environment where you will be encouraged to learn, experiment, and grow your technical capabilities
Preferred Qualifications
Education
• Bachelor's degree with a concentration or specialization in Artificial Intelligence or Machine Learning
• Relevant graduate coursework or a Master's degree in AI/ML, Computer Science, or a related field
Experience and Skills
• Experience building or contributing to RAG (retrieval-augmented generation) architectures or LLM-powered applications
• Hands-on experience with AI/ML frameworks and libraries such as LangChain, LlamaIndex, Hugging Face Transformers, PyTorch, or TensorFlow
• Exposure to agentic AI concepts and frameworks, including multi-agent orchestration, tool-use patterns, and autonomous task execution (e.g., LangGraph, CrewAI, AutoGen, or similar)
• Experience with FastAPI, Flask, or Django for building backend services
• Experience with React, Next.js, or similar component-based frontend frameworks and UI libraries (e.g., Material UI)
• Familiarity with SAST tools (e.g., Semgrep, SonarQube, Bandit) and secure software development practices
• Experience with Kubernetes (e.g., GKE, EKS, AKS) in a development or deployment capacity
• Exposure to infrastructure-as-code tools (e.g., Terraform, Helm) or GitOps workflows
• Experience developing or deploying applications within U.S. government or Department of Defense IT environments
• Familiarity with FedRAMP, IL4/IL5, or CMEK compliance concepts in cloud environments
Certifications (any of the following are a plus)
• AWS Certified Machine Learning - Specialty or AWS Certified Solutions Architect - Associate
• Google Cloud Professional Machine Learning Engineer or Google Cloud Associate Cloud Engineer
• Microsoft Certified: Azure AI Engineer Associate or Azure Developer Associate
