Senior Software Engineer – Inference (SWE3) [D.26.0205] with Security Clearance

Dover Networks LLC; Capitol Heights (MD); On-site; USD 260,000 - 285,000; Full time

Job summary

Dover Networks LLC is hiring a senior software engineer to support our AI infrastructure team. You will help build the foundation for customer AI capabilities and ensure access to high-quality LLMs across the inference stack.

Responsibilities include leading deployment of models, mentoring engineers, and collaborating with cross-functional teams to deliver reliable AI services. TS/SCI clearance is required with Full Scope Polygraph.

Qualifications

• Requires TS/SCI clearance with Full Scope Polygraph; no sponsorship.
• Senior software engineer for AI infrastructure and inference services.
• Proven ability to translate high level goals into engineering outcomes.

Responsibilities

• Lead evaluation, configuration, and deployment of inference models.
• Translate stakeholder goals into engineering outcomes.
• Mentor engineers and promote development best practices.
• Develop in-house services to ensure high-quality inference.
• Collaborate with teams to build infrastructure for AI tools.
• Support surge efforts for high-priority inference needs.

Skills

Python

Leadership

Mentoring

Communication

Cloud computing

Education

Bachelor's degree in a technical discipline

Tools

Argo CD

CI/CD frameworks

Kubernetes

Helm

AWS

Job description

Applicants must already hold a TS/SCI clearance with a current Full Scope Polygraph before applying. We are not sponsoring or processing clearances for this position. Candidates who are seeking to obtain a clearance do not meet the minimum requirements.

Salary Range: $260k-$285k per year with an additional $65k-$71k 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 senior 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. Responsibilities 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:

• Lead the evaluation, configuration, and deployment of inference models for our users.
• Translate high-level stakeholder goals into engineering outcomes.
• Mentor engineers and grow development best practices and standards for the team.
• Develop in-house services and techniques to guarantee continual high-quality inference service for our customer.
• Engage with other teams in our organization to establish solid infrastructure for our services and integrate LLM-powered tools for user needs.
• Collaborate with teammates on surge efforts to support short-term, high-priority inference needs from our customer.

Skills Requirements:

• Experience with Python and/or other modern programming languages.
• Experience with Argo CD and/or other CI/CD frameworks.
• Experience with Kubernetes/Helm.
• Experience with AWS or other cloud service providers.
• Strong communication skills and ability to mentor other engineers.
• Excellent leadership and stakeholder management skills.
• Ability to balance hands-on engineering with leadership and coordination responsibilities.
• Knowledge of and interest in hosting AI capabilities. YOE Requirement: 12 yrs., B.S. in a technical discipline or 4 additional yrs. in place of B.S.

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.