Full Stack Software Engineer (AI Infrastructure)

Bytoa; Laurel (MD); On-site; USD 200,000 - 220,000; Full time

Job summary

Bytoa is seeking a Full-Stack Software Engineer to support our AI infrastructure team in Laurel, MD. You will help build and maintain the platform that enables customer AI capabilities, focusing on inference services and scalable AI infrastructure components.

Salary range listed as $200,000–$220,000 with compensation determined case-by-case. This role requires experience with production systems, AWS, Kubernetes, and observability, and offers opportunities to mentor junior engineers.

Qualifications

• Extensive experience building & maintaining production systems.
• Experience with high-volume web applications and performance optimization.
• Strong background in systems integration across diverse technologies and platforms.

Responsibilities

• Design, implement, and optimize infrastructure for AI model inference at scale.
• Support 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 IaC principles.
• Ensure high availability, reliability, and performance of AI platform components.
• Provide technical guidance and informal mentorship to junior engineers.

Skills

Production systems

Web app architecture

Systems integration

AWS

Kubernetes

Observability

CI/CD

DevOps

Communication

Mentoring

Education

BS in technical discipline

4 additional years of experience in lieu of BS

Job description

Full Stack Software Engineer (AI Infrastructure)

• Laurel, MD

Description:

Bytoa is seeking a Full-Stack Software 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.

Salary range:$200,000-$220,000 Disclaimer: Salary for this position, along with additional compensation options, will be determined on an individual basis following the interview process, considering various factors such as years of experience, skills, education/certifications, contract specifications, market conditions, etc.

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), 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 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.

Skills Requirements:

• 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.
• 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.

Nice to Haves:

• 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.

Experience Requirement:

8 yrs., B.S. in a technical discipline or 4 additional yrs. in place of B.S.

Clearance Requirement:

Active TS/SCI with a polygraph