Job description

Residency All applicants must reside in the United States at the time of application. Overview BigBear.ai is seeking a S oftware Engineer to support our AI infrastructure team. In this role, you'll help build and maintain the platform that provides the foundation for the customer's AI capabilities, focusing on inference services while supporting the broader ecosystem of AI-enabled applications. This role is intended for experienced engineers who can independently design, implement, and operate scalable AI infrastructure components. What you will do • Design, implement, and optimize infrastructure for AI model inference at scale • Support the development and maintenance of production AI services and applications, including retrieval augmented generation (RAG), autonomous agents, and emerging technologies • Navigate ambiguity and define solutions for underspecified systems and requirements • Drive adoption of new technologies and practices across engineering teams • Implement monitoring, logging, and observability solutions for AI services • Automate infrastructure provisioning and configuration using Infrastructure-as-Code (IaC) principles • Ensure high availability, reliability, and performance of AI platform components • Contribute to security best practices for AI systems and data • Provide technical guidance and informal mentorship to junior engineers What you need to have • 8+ years of relevant experience, or Bachelor's degree in a technical discipline + 4+ years of experience • Clearance: TS/SCI w/Poly • 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 • Experience with AI inference serving technologies (vLLM, LiteLLM, etc.) • Previous experience with agentic frameworks (LangChain) • Knowledge of vector databases and embedding 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 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.

Requirements

Must-haves

All applicants must reside in the United States at the time of application.
This role is intended for experienced engineers who can independently design, implement, and operate scalable AI infrastructure components.
Design, implement, and optimize infrastructure for AI model inference at scale
Support the development and maintenance of production AI services and applications, including retrieval augmented generation (RAG), autonomous agents, and emerging technologies
Navigate ambiguity and define solutions for underspecified systems and requirements
Drive adoption of new technologies and practices across engineering teams
Implement monitoring, logging, and observability solutions for AI services
Automate infrastructure provisioning and configuration using Infrastructure-as-Code (IaC) principles
Ensure high availability, reliability, and performance of AI platform components
Contribute to security best practices for AI systems and data
Provide technical guidance and informal mentorship to junior engineers
What you need to have
8+ years of relevant experience, or Bachelor's degree in a technical discipline + 4+ years of experience
Clearance: TS/SCI w/Poly
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

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiawskubernetespythonci/cd

Platform: jibe
Effort: medium

Benefits

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