Senior AI/DevOps Engineer

We're looking for a Senior AI/DevOps Engineer who thrives at the intersection of infrastructure, automation, and applied AI. You'll be the person who makes AI-powered features actually ship, scale, and stay healthy in production - building the pipelines, platforms, and guardrails that let the rest of the team move fast with LLMs and ML models. This is a hybrid role: part platform/DevOps engineer, part MLOps practitioner, part AI integrator.

This is a full-time, remote role, with flexibility to work from home. This role works across a globally distributed team spanning India and both US coasts, so comfort with asynchronous collaboration and overlapping across time zones is important. Expect some evening hours to overlap with global teams.

Responsibility

• Design and operate the infrastructure that powers our AI features: LLM integrations, RAG pipelines, vector stores, and model-serving endpoints.
• Build and maintain CI/CD pipelines for both traditional services and AI/ML workloads (model deployment, evaluation, rollback).
• Own observability and monitoring for AI systems - latency, cost, token usage, output quality drift, and failure modes unique to LLM-based features.
• Architect and manage cloud infrastructure on Azure (compute, networking, storage, IAM) using infrastructure-as-code.
• Containerize and orchestrate services with Docker and Kubernetes.
• Integrate with AI APIs and platforms (OpenAI, Anthropic, Azure AI/OpenAI Service, or similar) and build internal tooling to make that integration repeatable across teams.
• Implement guardrails, rate limiting, caching, and cost controls for LLM-powered features.
• Collaborate with product, data, and application engineering teams to translate AI-feature designs into reliable, production-grade systems.
• Coordinate effectively with teammates across India, East Coast, and West Coast time zones.
• Mentor other engineers and help set technical direction for AI infrastructure practices.

Requirements

• Bachelor's Degree in CS or Engineering.
• 5+ years of professional experience in DevOps, platform engineering, or SRE roles.
• Hands-on experience deploying and operating systems in production.
• Expert level in Python, and proficient in Java (specifically targeting backend product engineering context).
• Strong experience with Azure cloud infrastructure and infrastructure-as-code (Terraform, Bicep, ARM, or similar).
• Solid grasp of CI/CD pipeline design and automation (Azure DevOps, GitHub Actions, or similar).
• Proficiency with Docker and Kubernetes for containerization and orchestration.
• Experience integrating with AI/LLM APIs (OpenAI, Anthropic, Azure AI, or similar) and understanding of RAG architectures, vector databases, and prompt/response evaluation.
• Comfort with monitoring and observability tooling (Prometheus, Grafana, Application Insights, or similar), including metrics specific to AI systems (cost, latency, quality).
• Comfortable working independently and owning problems end-to-end.
• Strong written communication and async collaboration skills, given the distributed, multi-time-zone team.

Nice to have

• Expertise in some of the following frameworks: FastAPI, Pydantic.AI, Pydantic 2, Polars, Pandas, Spring Boot, Hibernate, JDBC.
• Experience with LLM evaluation frameworks and prompt engineering.
• Security/compliance experience around AI systems (data privacy, PII handling, model access controls).
• Background in SOLID principles, clean architecture, and TDD.
• Experience in retail, pricing, or data-intensive SaaS products is a plus.