Full Stack Software Engineer

Talentify

Columbia (MD)

On-site

USD 150,000 - 210,000

Full time

14 days+
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Job summary

BigBear.ai is seeking a Full Stack Software Engineer to build the next generation of AI infrastructure, focusing on inference services and AI-enabled applications. You will design scalable infrastructure, develop production AI services, and mentor junior engineers in a fast-paced environment.

The role requires strong Java/Python skills, experience with cloud engineering in AWS, Kubernetes, observability tools, and CI/CD practices. A TS/SCI w/Polygraph clearance is required.

Qualifications

  • 8 years of experience with a B.S. in a technical discipline or 4 additional years of experience in place of a degree.
  • Proficiency in Java and Python.
  • Proven experience building and maintaining production systems at scale.
  • Experience with high-volume web application architecture and performance optimization.

Responsibilities

  • 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) and autonomous agents.
  • 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).
  • 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

Skills

Java
Python
AWS
Kubernetes
CI/CD
Observability
Distributed systems
Web architecture
Security best practices
Communication skills

Education

Bachelor's degree in a technical discipline

Tools

Grafana
Prometheus
OpenTelemetry
LangChain
vLLM
LiteLLM
Docker
CI/CD tooling

Job description

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 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 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.

  • 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
  • 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
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