Senior DevOps Engineer
MindBridge Verified employer
Actively hiring · Posted 5d ago · JEV26105580055F24
Job description
The Role As a **DevOps Engineer** you'll own the infrastructure and delivery backbone that keeps our platform running as we grow. You'll build the CI/CD, cloud infrastructure, and observability that let a small, fast-moving team ship confidently — and you'll keep our AI and data workloads reliable and affordable at scale. This is a hands-on role with real ownership: you won't be maintaining someone else's setup, you'll be shaping ours. You'll work closely with the backend, AI/ML, and data teams to make deployment boring, incidents rare, and scaling a non-event. --- What You'll Own **CI/CD & developer experience** - Build and maintain fast, reliable CI/CD pipelines so engineers ship multiple times a day with confidence. - Make the path from commit to production simple, safe, and repeatable, with sensible automated testing, rollbacks, and release controls. **Cloud infrastructure & IaC** - Own our cloud infrastructure (AWS/GCP) end to end, managed as code (Terraform or similar) — no click-ops. - Design for scale and cost-efficiency as store and conversation volumes grow. **Containers & orchestration** - Run our services on containers/Kubernetes: deployments, autoscaling, networking, and resource management. - Support the specific needs of AI/ML workloads, including GPU-backed inference and batch processing for the speech pipeline. **Reliability & observability (SRE)** - Own uptime, performance, and incident response — monitoring, logging, tracing, alerting, on-call, and blameless postmortems. - Define and defend SLOs; keep the platform dependable as it scales across clients. **Data & pipeline infrastructure** - Support the infrastructure behind large-scale, edge-to-cloud data movement and processing (audio ingestion, ASR/AI pipelines, analytics). - Keep data workloads reliable, performant, and cost-aware. **Security & compliance** - Bake security into the platform: secrets management, IAM/least-privilege, encryption in transit and at rest, network hardening, and vulnerability management. - Support compliance readiness (including India's DPDP Act and enterprise-client security requirements) for a product that handles sensitive customer conversations. **Cost & scale** - Own cloud cost visibility and optimization; make scaling decisions that balance reliability and spend. --- What You'll Bring - 6+ years in DevOps, SRE, platform, or infrastructure engineering, running production systems at meaningful scale. - Strong hands-on experience with a major cloud provider (**AWS or Azure or GCP**) and Infrastructure-as-Code (**Terraform** or equivalent). - Solid experience with **containers and Kubernetes** in production. - Experience building and owning **CI/CD** pipelines (e.g. GitHub Actions, GitLab CI, Jenkins, Argo, or similar). - Comfort with a scripting/automation language (Python, Go, or Bash) and a strong automation-first mindset. - Real experience with **observability** (Prometheus/Grafana, ELK, Datadog, OpenTelemetry, or similar) and running incident response / on-call. - A security-conscious approach — secrets, IAM, encryption, and least-privilege as defaults. - Startup temperament: ownership, pragmatism, and a bias to automate and ship. - Based in or willing to relocate to Bangalore, and up for an onsite/hybrid, in-person team. Bonus Points - Experience running **ML/AI or GPU workloads** in production (inference serving, batch pipelines, model deployment). - Experience with data-intensive infrastructure — streaming/queues (Kafka, SQS), data pipelines, or large object/audio storage. - Exposure to **edge devices / IoT fleets**, OTA updates, or high-volume device-to-cloud ingestion. - Experience with compliance/security frameworks (SOC 2, ISO 27001, DPDP). - FinOps / cloud cost-optimization experience. - Early-stage startup experience. --- Why Join - Own infrastructure that's already live with leading retail brands and growing fast — real scale, real impact. - Work across genuinely interesting workloads: speech AI, GPU inference, large-scale data, and edge-to-cloud ingestion. - Small team, high ownership, direct line to engineering leadership — your decisions ship. - Build the platform foundation of a category-defining product from an
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