DevOps / Platform Engineer
Job Description
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Mimica is an AI-powered process intelligence platform enabling enterprises and individuals to reclaim their most precious resource: time. Mimica automatically analyzes your team’s work, then generates AI agents to execute it. Our software turns everyday work into data-backed decisions, helping companies remove process bottlenecks, automate the right tasks, and upskill teams with precision and confidence.
We’ve raised $26 million in Series B financing and are scaling fast. Backed by investors including Khosla Ventures and Paladin Capital, our proprietary AI technology is trusted by Fortune 500 companies to accelerate transformation. Mimica is recognized as a Top 100 AI Start-up by Accel and an industry Leader by the Everest Group.
Your mission
Mimica is growing fast, and so is the demand on our Platform Team. As a DevOps / Platform Engineer, you will join a lean but highly capable team that is the backbone of every engineering squad in the company.
We service the entire engineering organization: keeping environments healthy, unblocking teams, and building the infrastructure that lets everyone else move faster. We’re looking to increase our capacity as demand for our services is growing fast.
On top of the day-to-day demand from other teams, we are taking on some of our most ambitious infrastructure projects yet: expanding to multi-region and single-tenancy environments, supporting BYOC (Bring Your Own Cloud) deployments, migrating our IaC from Terraform to Crossplane, and getting serious about FinOps.
We are looking for engineers with either an application development or a systems/infrastructure background.
What matters more than your origin story is your hands-on comfort with Kubernetes, IaC, and cloud platforms, your curiosity, and your ability to collaborate closely with other engineering teams. If you want to work in a place where your contributions are visible, your scope is broad, and the problems are real, this is the role for you.
Part of your day-to-day
Support engineering teams across Mimica in developing mature, resilient applications running on GKE, advising on best practices and unblocking issues quickly.
Develop and maintain infrastructure-as-code using Terraform and ArgoCD, as well as Mimica-specific Platform applications written in Python.
Manage and maintain GKE environments across multiple regions (EKS experience is also acceptable), including IAM and identity management on GCP (AWS acceptable).
Investigate and triage issues in existing applications, observe database and system component health, and implement changes to support the SDLC of other teams.
Participate in a scheduled on-call rotation to monitor system health, respond to incidents, and ensure high platform availability.
Contribute to migrating our IaC layer from Terraform to Crossplane and support expansion into multi-region clusters and single-tenancy environments.
Drive FinOps initiatives, helping us get visibility into and control over cloud spend across multiple accounts and environments.
Help design and implement access patterns for new BYOC and single-tenancy environments, making it seamless for engineers to navigate an increasingly complex multi-environment landscape.
Instrument, monitor, and improve observability across our stack using tools such as Honeycomb and Grafana.
Requirements / What we're looking for
Solid hands-on experience with Kubernetes, whether on GKE (preferred), EKS, OnPrem, or another managed Kubernetes service. You know your way around cluster configuration, scheduling, RBAC, and debugging live issues.
Proven experience with Terraform as your primary IaC tool. Familiarity with Terragrunt is a plus.
IAM and identity management experience on at least one major hyperscaler: GCP (preferred) or AWS.
Experience with ArgoCD or a comparable GitOps tool for continuous delivery.
Observability experience with at least one major platform: Honeycomb, Datadog, Grafana, or New Relic. You know how to set up meaningful dashboards, alerts, and traces.
Comfortable writing code, particularly in Python, to automate platform tasks and build internal tooling.
Background in startups or scale-ups: you are used to ambiguity, moving fast, and wearing multiple hats.
Strong communication and collaboration skills: You can translate infrastructure complexity into clear language for application engineers, and you know when to raise a flag versus just fixing it.
Experience leading and participating in incident responses. You systematically decompose problems and know how to get to the root cause without panicking.
Bonus / Nice to have
Experience running GPU workloads on Kubernetes, particularly in the context of ML infrastructure.
Familiarity with Crossplane (or strong interest in migrating to it from Terraform).
Experience with Temporal for workflow orchestration.
Hands-on knowledge of Grafana Alloy, Loki, or similar observability tooling in the Grafana ecosystem.
Experience with MongoDB, PostgreSQL, or SQL Server.
Security engineering experience, particularly around hardening Kubernetes environments or supporting compliance initiatives (e.g. SOC 2).
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Mimica
View Company ProfileMimica is an innovative enterprise AI company that specializes in automated process discovery and task mining. Founded in 2017, the company provides a crucial foundational layer for robotic process automation (RPA) initiatives. Under the hood, Mimica’s intelligent software runs passively on employee desktops, utilizing advanced machine learning and computer vision to silently observe, record, and analyze complex manual workflows across various applications. It then automatically generates highly detailed, step-by-step process maps and RPA blueprints (such as PDDs - Process Design Documents). Their primary target audience includes enterprise automation leaders, Centers of Excellence (CoEs), and business analysts who need to identify automation opportunities and accurately calculate ROI before investing in expensive bot development. What sets Mimica apart in the process intelligence market is its ability to eliminate the notoriously slow, biased, and manual interview processes traditionally used to document workflows, replacing them with objective, data-driven insights that dramatically accelerate digital transformation timelines.
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