Senior Software Engineer

Indeed•Remote,

112d•$118,000 - $248,000

About The Position

As a Software Engineer III on the AI Gateway & Guardrails team at Indeed, you will own and drive the development of platform services that connect Indeed's AI-powered products to large and small language models (LLM and SLM), and safeguards AI actions. You will work alongside experienced engineers developing features for two core services; 1) AI Gateway, Indeed’s unified entry point for multiple model providers with built-in best practices, and 2) AI Guardrails Platform, Indeed’s universal safety layer for language model powered products. In this role, you’d remove technical barriers to entry for teams all across Indeed to experiment with generative AI. This work provides an opportunity to leverage cutting-edge technologies across multiple cloud providers, influence the product direction for a broad spectrum of client teams, and guide best practices for AI use. You will contribute to architectural decisions, drive service reliability through SLOs and operational readiness, and partner with product teams across Indeed to ensure the platform meets compliance and quality standards required for production AI deployment.

Requirements

A Bachelor’s degree in Computer Science, Mathematics, Computer Engineering, or Electrical Engineering, and a minimum of 5 years of related experience; or a Master’s degree with a minimum of 3 years of experience; or a PhD without experience
Experience building or operating large-scale distributed systems, ideally within platform or infrastructure environments
Proficiency with cloud infrastructure across major providers (AWS, GCP, or Azure), including deployment, monitoring, and operations
Experience with or interest in AI/ML systems, including LLM-based services, prompt engineering, or AI safety approaches
Familiarity with reliability engineering practices such as SLOs, error budgets, observability tools, and on-call readiness
Solid grounding in data structures, algorithms, and core computer science principles, with a track record of solving complex technical problems
Demonstrated ownership, accountability, and a proactive mindset, paired with curiosity and a drive to continuously learn

Responsibilities

Design, implement, and maintain platform services that provide secure, scalable, and reliable access to LLM and SLM providers across multiple cloud environments.
Contribute to multi-provider access, failover, and rate-limiting capabilities across cloud platforms (Azure, AWS, and GCP).
Drive improvements to the AI Guardrails Platform, such as content moderation and Personally Identifiable Information (PII) redaction.
Facilitate technical discussions and contribute architectural decisions at the service and system level.
Identify and implement reliability improvements through SLOs, observability tooling, alerting, and runbook development.
Collaborate with engineers, product managers, and governance partners across teams to deliver compliant, production-ready AI systems.
Share knowledge and provide technical guidance with teammates.