Full Stack Software Engineer

Bigbear.ai • Columbia, MD

21h

About The Position

BigBear.ai is seeking a Full Stack Software Engineer to help build the next generation of AI infrastructure that will drive innovation across the customer organization. In this role, you will support the AI infrastructure team by building and maintaining the platform that serves as the foundation for the customer’s AI capabilities. You will focus on inference services while supporting the broader ecosystem of AI-enabled applications. This position is ideal for experienced engineers who can independently design, implement, and operate scalable AI infrastructure components. If you are passionate about cutting-edge AI technologies and building robust systems, this is the opportunity for you.

Requirements

• Clearance: Must possess and maintain an active TS/SCI w/Polygraph
• Education & Experience: 8 years of experience with a B.S. in a technical discipline or 4 additional years of experience in place of a degree
• Technical Expertise:
• Proven experience building and maintaining production systems at scale
• Experience with high-volume web application architecture and performance optimization
• Strong background in systems integration across diverse technologies and platforms
• Hands-on experience with cloud engineering in AWS
• Proficiency with Kubernetes administration and deployment patterns
• Strong Python programming skills
• Experience implementing observability solutions (APM, OpenTelemetry, Grafana, Prometheus)
• Familiarity with CI/CD pipelines and DevOps practices
• Strong change management and organizational influence skills
• Ability to thrive in ambiguous environments and create structure where needed
• Excellent communication and collaboration skills

Nice To Haves

• AI Inference Expertise: Experience with AI inference serving technologies (e.g., vLLM, LiteLLM)
• Agentic Frameworks: Previous experience with agentic frameworks (e.g., LangChain)
• Vector Databases: Knowledge of vector databases and embedding systems
• Distributed Systems: Experience with high-performance computing or distributed systems

Responsibilities

• Infrastructure Design: Design, implement, and optimize infrastructure for AI model inference at scale
• AI Services Development: Support the development and maintenance of production AI services and applications, including retrieval augmented generation (RAG), autonomous agents, and emerging technologies
• Problem Solving: Navigate ambiguity and define solutions for underspecified systems and requirements
• Technology Adoption: Drive adoption of new technologies and practices across engineering teams
• Monitoring & Observability: Implement monitoring, logging, and observability solutions for AI services
• Automation: Automate infrastructure provisioning and configuration using Infrastructure as Code (IaC) principles
• Reliability: Ensure high availability, reliability, and performance of AI platform components
• Security: Contribute to security best practices for AI systems and data
• Mentorship: Provide technical guidance and informal mentorship to junior engineers

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level