AI Innovation Engineer Intern
About The Position
BigBear.ai is seeking an AI Innovation Intern to support BigBear.ai’s Innovation Org. This internship is designed for a student pursuing a degree in Information Systems, Computer Science, Data Science, Artificial Intelligence, Software Engineering, or a related technical field. The Innovation Org serves as a connective layer across BigBear.ai’s business units and corporate functions, helping teams adopt GenAI tools, identify reusable capabilities, standardize effective workflows, and translate emerging AI technologies into practical enterprise value. The intern will work alongside senior technical leaders to help build agentic workflows, support AI enablement activities, research emerging tools and patterns, document reusable practices, and assist with mapping business-unit needs to technical capabilities. This role is well-suited for a student who enjoys both hands-on technical development and cross-functional problem solving. The ideal candidate is comfortable learning quickly, asking good questions, organizing ambiguous information, and turning prototypes, research, or team feedback into useful artifacts for broader enterprise adoption.
Requirements
- Currently enrolled in a Bachelor's or Master's degree program in: Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related technical field
- U.S. Citizenship required
- Familiarity with at least one programming language such as Python, JavaScript, or other Object Oriented or Functional programming languages
- Basic understanding of AI, machine learning, data science, or large language model concepts
- Interest in GenAI tools, agentic workflows, retrieval-augmented generation, automation, or applied AI systems
- Ability to work with structured and unstructured information and synthesize findings into clear technical notes or recommendations
- Strong problem-solving, analytical, and communication skills
- Ability to work in a remote or hybrid environment with guidance from senior technical staff
- Willingness to learn new tools, frameworks, and enterprise workflows quickly
Nice To Haves
- Experience with Python and common data/AI libraries such as pandas, Polars, NumPy, scikit-learn, or similar tools
- Exposure to LLM-based workflows, RAG systems, LangChain, Hugging Face, vector databases, embeddings, or prompt engineering
- Familiarity with relational databases, SQL, PostgreSQL, or database-backed application development
- Exposure to vector databases such as Weaviate, Pinecone, Chroma, FAISS, or similar technologies
- Experience with Docker, GitHub, CI/CD concepts, cloud platforms, or DevOps practices
- Familiarity with REST APIs, Flask, FastAPI, web applications, or full-stack development concepts
- Experience building or contributing to prototypes, internal tools, dashboards, notebooks, or user-facing technical workflows
- Exposure to knowledge graphs, graph databases, semantic search, or entity-relationship modeling
- Ability to document technical patterns, summarize research findings, and create reusable materials for broader team adoption
- Prior internship, academic project, or team project experience involving AI/ML, data engineering, software development, or automation
Responsibilities
- Assist in the design, development, and testing of AI-enabled workflows, agentic prototypes, RAG pipelines, and reusable automation patterns
- Support the Innovation Org in identifying common technical needs, workflow gaps, and reusable capabilities across business units and corporate functions
- Help research, evaluate, and document emerging GenAI tools, agent frameworks, vector databases, retrieval patterns, prompt workflows, and software-development practices
- Contribute to lightweight prototypes, demos, internal tools, or reference implementations that demonstrate practical use of GenAI and automation
- Assist with mapping business-unit needs to existing BigBear.ai capabilities, reusable assets, internal expertise, and potential technology solutions
- Support documentation of reusable engineering assets, prompts, workflows, reference architectures, lessons learned, and internal enablement materials
- Collaborate with senior engineers and technical leads on software-development tasks using Python, APIs, databases, cloud tools, and modern AI/ML libraries
- Help prepare internal artifacts such as capability maps, technical summaries, use-case notes, workflow diagrams, demo materials, and research briefs
- Participate in agile development activities, code reviews, technical discussions, and knowledge-sharing sessions
- Support enterprise AI adoption efforts by helping capture lessons learned, success stories, technical patterns, and opportunities for standardization
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What This Job Offers
Career Level
Intern
Education Level
No Education Listed
