[Remote] Senior Platform Engineer

Note: The job is a remote job and is open to candidates in USA. Profitmind is a retail analytics SaaS company that transforms competitive and customer data into actionable insights for retailers. They are seeking a Senior Platform Engineer to design and operate their multi-cloud infrastructure, implement automation and security tooling, and ensure the reliability of their platform as they expand into new regions.

Responsibilities

• Own infrastructure as code. Design and operate our cloud infrastructure as Terraform across Azure, AWS, and GCP — landing zones, networking, and IAM — including bringing resources currently managed by partners and templates under our own automated, version-controlled ownership
• Run GitOps delivery. Build and maintain CI/CD and GitOps pipelines (e.g., Argo, GitHub Actions / Azure DevOps) that deploy our services into non-prod and prod environments reliably and repeatably
• Own the release process. Define and run a disciplined SDLC and release process — versioning and tagging releases, promoting builds through environments, and tracking what is deployed where. Maintain traceability from commit to build to deployment (and to the Jira work behind it) so every change is auditable, including for SOC 2 and customer due diligence
• Operate Kubernetes. Manage our Kubernetes / AKS environments — cluster setup, autoscaling, workload deployment, and the operators and platform services that run on them
• Enable EU and multi-region. Stand up EU-resident infrastructure and additional cloud regions, ensuring data residency, networking, and access controls are correct by design
• Drive SOC 2 and security. Implement and maintain org-wide security controls, vulnerability scanning, and access governance across our clouds, GitHub, and Kubernetes — and produce the evidence and discipline that SOC 2 and enterprise customer due diligence require
• Build platform tooling. Develop platform services and developer tooling (in Python or similar) that make the rest of engineering faster — self-service environments, internal automation, cost monitoring, and reusable building blocks
• Support the data platform. Partner with data engineering on the infrastructure under our data pipelines and customer-cloud deployments — from competitive and customer data flows to customer ingestion paths (SFTP and direct warehouse reads), so the platform is reliable and portable across customer environments
• Build secure integrations. Help evolve how we connect to customer and third-party systems — moving beyond today’s SFTP file exchange toward more direct, flexible integrations (both push and pull) such as direct warehouse reads. Build the authentication, authorization, secrets, and key management that make those connections secure by default
• Own observability and cost. Run our observability stack (metrics, logs, traces, alerting) and monitor cloud spend and egress across clouds, driving optimization
• Unblock the team. Treat the engineering teams as your customers. Own access, permissions, and environment requests end to end and turn them around quickly — when someone needs cloud access or a resource to do their job, removing that blocker promptly is part of the role, not a side task
• Reduce single-points-of-knowledge. Document what you build and spread ownership. We are deliberately building a fungible, well-documented platform function, not concentrating critical knowledge in one person

Skills

• Strong software engineering. You write production-quality software — platform services, automation, and tooling in Python, Go or similar — and treat infrastructure as code you engineer, not just configure
• Multi-cloud infrastructure depth. Hands-on experience architecting and operating infrastructure as code with Terraform across more than one major cloud (Azure, AWS, and/or GCP), including per-provider IAM and account/environment segmentation
• GitOps and Kubernetes. Strong, production experience with Kubernetes and GitOps-based delivery (ArgoCD or equivalent), CI/CD pipelines, and deploying real services into real environments
• Release and SDLC discipline. Experience defining release processes — versioning, tagging, environment promotion, and tracking what is deployed where — with traceability from change to deployment
• Security and compliance instinct. Experience implementing security controls and supporting compliance efforts (SOC 2, ISO 27001, or similar), including the evidence and process discipline audits require
• Authentication and secure connectivity. Working knowledge of authentication and authorization (OAuth / OIDC, SSO, IdP federation), secrets and key management, and securing system-to-system integrations
• Observability. Experience operating modern observability tooling (metrics, logs, traces, and alerting — e.g., OpenTelemetry, Prometheus, Grafana, Datadog, or similar) and using it to drive reliability
• Ownership and a service mindset. Self-directed, comfortable with ambiguity, and responsive to the people who depend on you
• Experience standing up EU data residency / GDPR-relevant infrastructure
• MLOps or model-serving infrastructure experience, supporting an ML or data science team
• AI / LLM infrastructure experience
• Cloud cost optimization (FinOps) track record
• Service mesh or custom Kubernetes operator experience

Company Overview