Software Engineer – Inference (SWE1) [D.26.0174] with Security Clearance

Requires Top Secret/SCI with Full Scope Poly Salary Range: $163k-$178k per year with an additional $41k-$44k in immediately vested company 401(k) contributions Description: Join us in building the next generation of AI infrastructure that will power innovation across the customer organization. We're seeking a software engineer to support our AI infrastructure team. In this role, you'll help build and maintain the foundation for customer AI capabilities while supporting a broader ecosystem of AI-enabled applications.

Your focus will be ensuring access to the highest available quality LLMs to users throughout the inference software stack. Requirements shift quickly as mission needs evolve and new technologies emerge, so you'll keep sharpening your skills and learning to turn loosely defined problems into working solutions.

Responsibilities:

• Procure, configure, and test new inference models, preparing them for release to our user base.
• Develop in-house services and techniques to guarantee continual high-quality inference service for our customer.
• Work with model vendor teams and representatives to create reliable pipelines for closed-source model usage.
• Collaborate with teammates on surge efforts to support short-term, high-priority inference needs from our customer.
• Engage with other teams in our organization to establish solid infrastructure for our services and integrate LLM-powered tools for user needs.
• Skills Requirements: Experience with Python and/or other modern programming languages.
• Familiarity with Argo CD and/or other CI/CD frameworks.
• Experience with Kubernetes/Helm.
• Familiarity with AWS or other cloud service providers.
• Ability to learn new technologies quickly.
• Strong communication skills and willingness to ask questions. Nice to Haves:
• Experience with vLLM, LiteLLM, or similar inference-serving frameworks.
• Experience with other LLM hosting frameworks and practices.
• Experience supporting production software using Site Reliability Engineering (SRE) best practices.
• Experience with Elastic, Grafana/Prometheus, or other observability frameworks and practices.
• Experience with Docker and containerization.
• Experience in traffic shaping and quality-of-service engineering.
• Knowledge of and interest in hosting AI capabilities.

YOE Requirement: 3 yrs., B.S. in a technical discipline or 4 additional yrs. in place of B.S.