Full Stack Software Engineer

Overview 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. What you will do 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 r etrieval 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 you need to have 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: proficiency in Java and Python. 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 What we'd like you to have 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 About BigBear.ai BigBear.ai is a leading provider of AI-powered decision intelligence solutions for national security, supply chain management, and digital identity. Customers and partners rely on Bigbear.ai’s predictive analytics capabilities in highly complex, distributed, mission-based operating environments. Headquartered in McLean, Virginia, BigBear.ai is a public company traded on the NYSE under the symbol BBAI. For more information, visit https://bigbear.ai/ and follow BigBear.ai on LinkedIn: @BigBear.ai and X: @BigBearai. BigBear.ai is an Equal opportunity employer all protected groups, including protected veterans and individuals with disabilities. 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 r etrieval 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 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: proficiency in Java and Python. 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