Summary
We are seeking a senior AI engineer to design, build, and maintain cloud‑native data and AI platforms. The role involves extensive work with AWS, Kubernetes, Snowflake, and Terraform, creating robust CI/CD pipelines and integrating AI tools for code review and automated diagnostics. Candidates should have strong DevOps/SRE background, experience with LLM systems, and the ability to quickly adopt new technologies.
Highlights
Senior role focusing on building and scaling AI and data platforms with cutting‑edge cloud technologies. Opportunity to shape infrastructure, work with LLMs, and influence AI‑driven automation. Competitive environment that values technical clarity and hands‑on innovation.
Description
We're looking for a senior AI engineer who sits at the intersection of platform and AI engineering.
You have the seniority to keep things simple and bring technical clarity to business conversations.
The stack spans AWS, Kubernetes, Snowflake, and GitLab CI.
We don't expect a perfect stack match.
We're hiring for the person and seniority first.
We want to keep our maintenance boring.
We're looking at using AI to do review, self-healing and root-cause analysis.
You are the kind of person that enjoys going deep into the tech when it matters.
We see ourselves doing a mix of AI use cases and evolving our data/AI platforms.
We use Claude Code and expect you to be comfortable pair-programming with AI.
What You'll Do
Build and evolve AWS infrastructure (networking, compute, storage, security) for Data & AI platforms and AI use casesPartner with engineers and business people to produce ML pipelines and new AI use cases (model serving, evals, guardrails, and the surrounding infrastructure that keeps them robust and scalable)Run and maintain Kubernetes clusters (deployments, scaling, keeping workloads healthy)Manage and optimize our Snowflake environment (access control, cost management, performance tuning, and data pipeline reliability)Build and maintain CI/CD pipelines (GitLab CI, AI-assisted code review, policy checks, test generation) that make deploying boringDesign infrastructure as code (Terraform) that is readable, reviewable, and version-controlledSet up and improve observability and self-healing (monitoring, alerting, dashboards, LLM-driven diagnosis, runbook automation)
What We're Looking For
We care most about strong fundamentals and flexibility to pick up new tools.
You don't need to tick every box.
5+ years of experience in DevOps, SRE, platform engineering, infrastructure, or AI engineeringDeep hands-on experience with AWS (IAM, VPC, ECS/EKS, S3, Lambda, CloudWatch, or similar)Solid experience operating Kubernetes clustersExperience managing cloud data warehouses in productionStrong Infrastructure as Code skills (Terraform preferred)Use of AI tools in your own engineering workflowHands-on experience building and operating LLM systems in production (prompts, evals, tool-use, guardrails, or agentic patterns)