Senior Software Engineer, AI Inference Asset Delivery Platform

Quick Facts

• Role: Senior Software Engineer for an AI inference asset delivery platform

Description

Own the end-to-end asset integration pipeline that moves assets from client teams to server nodes across data centers. Lead the transition from a repository-based workflow to microservices and RESTful APIs, including package builds/build automation, storage endpoints, and operational dashboards and alerting. Collaborate with client teams building on Large Language Models using ML concepts.

Responsibilities

• Design and build microservices and RESTful APIs for asset intake, packaging, storage, and distribution to server nodes across data centers

• Lead migration from repository-based asset management to a service-oriented architecture

• Own package build pipelines and coordinate automation with build teams

• Provide storage endpoints and clear onboarding paths for client teams

• Build and maintain monitoring dashboards and alerting mechanisms for pipeline health

• Develop internal tools (CLIs, microservice, automation pipelines, front end) to improve developer experience

• Drive architectural decisions prioritizing reliability, observability, and ease of adoption

• Collaborate cross-functionally with product, security, and engineering teams, plus client teams

• Provide technical mentorship and elevate engineering standards; set API and design standards

• Apply systems thinking to understand how changes propagate across the platform

• Adapt to rapidly changing requirements without compromising long-term objectives

Requirements

• 7+ years of software engineering experience building and operating production systems

• Expert-level proficiency in Python or Java with production web services and RESTful API design

• Experience designing and operating microservices, including services spanning multiple data centers; ability to reason about scale, concurrency, and failure modes

• Proven experience designing and implementing internal tools, automation, and service-level components

• Foundational understanding of machine learning and LLM concepts

• Ability to collaborate closely across teams and influence decisions through clarity, empathy, and technical depth

• Comfort working in dynamic, fast-changing environments

• Experience building monitoring dashboards and alerting for services you own

• Bachelor’s degree in Computer Engineering, Electrical Engineering, Computer Science or related field

Benefits

• Opportunity to build and integrate technologies that enable AI inference asset delivery in cloud environments and support resilient, scalable systems.