Full Stack Software Engineer
Bigbear
Columbia, MD · Posted September 25, 2026
See every open role at Bigbear
More in Maryland job market · Manufacturing & Industrial · Engineering jobs
Pay compared with the market
This listing does not state pay. Across 84 open full stack software engineer listings that state pay, the middle half runs $137,000 to $206,500 and the median is $173,500.
Listed pay is what employers advertise, not what people are paid.
Full Stack Software Engineer salaries by state · Check your own pay
About the job
Residency
All applicants must reside in the United States at the time of application.
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
Pay transparency
Please note the targeted compensation range is provided as an estimate, and any actual compensation offer may vary depending on the needs of the company, or an applicant's skillset, competencies, experience, education, certifications, location, or other factors. The estimated range does not include the value of any benefits offered.
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