DevOps Engineer, GCP

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Satori Analytics

WebsiteLinkedInAll Job Openings

51 - 200 employees

🤖 Artificial Intelligence

🤝 B2B

🏢 Enterprise

Artificial Intelligence • B2B • Enterprise

Satori Analytics is a data and AI transformation partner focused on bringing clarity to decision-making through advanced analytics, data management, and AI solutions. They specialize in embedding and adopting AI, generative AI, workflow automation, business intelligence, and data governance across various industries. Satori Analytics partners with leading technology vendors and has deep expertise in verticals such as Retail, Financial Services, Consumer Packaged Goods, and Energy. They prioritize delivering high, sustainable business value and return on investment to their clients through custom solutions and flexible partnering services. With a strong track record and a client repeat rate of over 90%, Satori Analytics is dedicated to excellence and innovation in data and AI solutions.

📋 Description

• **What Your Day Might Look Like:** • - **Cloud infrastructure as code**: Own and extend our Terraform estate across multiple GCP environments (base, core, obs, dev, test, prod), including GKE clusters, Cloud SQL (Postgres/MySQL), networking, buckets, and IAM. Drive the in-progress "Neo" platform rollout and the cutover/retirement of legacy infrastructure. • - **Kubernetes & containers**: Manage workloads on GKE, maintain Dockerfiles and Helm-style application configs for ~10 backend services, and tune autoscaling, resource limits, and pod disruption budgets. • - **Maintain and improve our GitHub Actions pipelines**: PR checks (Python/JS lint, type-check, tests), Terraform prechecks, image builds and pushes, auto-deploy, and DB-migration labelling/gating. Reduce build times and flakiness, and make deploys self-service for product teams. • - **Data & messaging infrastructure**: Operate Postgres, Redis, and Celery-based async workers; manage Alembic migrations, queue health, and backpressure for long-running simulation jobs. • - **Observability**: Own our monitoring stack — Grafana dashboards, ClickHouse, Langfuse (LLM tracing), and Celery queue metrics. Build alerting and SLOs so we catch issues before customers do. • - **Security & secrets**: Manage secret distribution, least-privilege IAM, and remediation tracking. Partner with engineering on findings in our security assessment process. • - **Cost & reliability**: Keep an eye on cloud and LLM-proxy (LiteLLM) spend, right-size resources, and improve resilience of the simulation and evaluation pipelines. • **You'll work with:** • - Cloud: Google Cloud Platform (GKE, Cloud SQL, GCS, IAM); some AWS / IBM footprint • - IaC: Terraform (>= 1.14), multi-environment root modules • - Containers/orchestration: Docker, docker compose (local), Kubernetes / GKE • - CI/CD: GitHub Actions • - Backend: Python 3.13+ (managed with uv), Celery, FastAPI-style HTTP APIs; Node/Express services • - Data: PostgreSQL, MySQL, Redis, ClickHouse • - Observability: Grafana, Langfuse, custom Celery metrics • - LLM infra: LiteLLM proxy

🎯 Requirements

• **Your Superpowers 🚀** • - 3+ years in DevOps / SRE / Platform Engineering, or strong backend experience with heavy infra ownership. • - Solid hands-on Terraform (modules, state, multi-environment) and cloud experience (GCP preferred; AWS/Azure transferable). • - Production Kubernetes experience: deployments, services, autoscaling, debugging pods, rollouts/rollbacks. • - Strong Docker fundamentals and comfort writing/optimising Dockerfiles. • - CI/CD pipeline design and maintenance (GitHub Actions, or equivalent like GitLab CI / CircleCI). • - Comfortable scripting and reading code in Python and/or Bash; able to navigate a polyglot monorepo. • - Operational experience with relational databases and managed database services (migrations, backups, performance). • - A reliability mindset: monitoring, alerting, incident response, and writing runbooks. • **Bonus points for:** • - Experience operating Celery / distributed task queues and Redis at scale. • - Familiarity with LLM/AI infrastructure (model proxies, GPU scheduling, token/cost management). • - Observability tooling depth (Grafana, Prometheus, ClickHouse, OpenTelemetry, Langfuse or similar tracing). • - Security/compliance experience (IAM hardening, secret management, vulnerability remediation). • - Cost-optimisation experience for cloud + third-party API spend. • - Experience supporting a monorepo with multiple language ecosystems and editable/internal package dependencies.

🏖️ Benefits

• **Perks on Perks** • - Competitive salary. • - Training budget to level up your skills from top tech partners like Microsoft, AWS, Salesforce, and Databricks – whether it’s certifications or courses, we’ve got you covered. • - Private insurance, top-tier tech gear, and the chance to work with a stellar crew.