Senior Software Engineer – AI Infrastructure

Responsibilities

• Design, implement, and optimize infrastructure for AI model inference at scale.
• Lead the development and maintenance of production AI services and applications, including retrieval augmented generation (RAG), autonomous agents, and emerging technologies.
• Serve as technical lead for AI infrastructure initiatives, coordinating work across integrated teams.
• Navigate ambiguity and define solutions for complex, underspecified systems and requirements.
• Establish new technical policies, standards, and governance frameworks where gaps exist.
• Drive adoption of new technologies and practices across engineering teams.
• Implement and oversee monitoring, logging, and observability solutions for AI services.
• Ensure high availability, reliability, performance, and security of AI platform components.
• Communicate effectively with stakeholders at multiple organizational levels.

Requirements

• Extensive experience designing, building, and operating large-scale production systems.
• Hands-on experience with cloud engineering in AWS.
• Advanced proficiency with Kubernetes administration and deployment patterns.
• Strong Python programming skills.
• Experience implementing and scaling observability solutions (APM, OpenTelemetry, Grafana, Prometheus).
• Proven ability to lead technical initiatives and influence organizational change.
• Experience developing technical policies and governance frameworks.
• Excellent communication, stakeholder management, and leadership skills.

Nice 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.
• Track record of successfully driving technical and cultural change.