Platform Engineering Manager

*Applicants must be authorized to work in the U.S. for any employer.*We cannot sponsor employment-based visas at this time.Let’s Tango! Where Innovation Meets Impact.At Tango Analytics, we’re all about helping businesses make smarter decisions through powerful technology, insightful data, and a whole lot of collaboration. Whether you're a creative thinker, a strategic planner, a tech wizard, or a customer champion, there's a place for you on our team. We believe work should be meaningful and fun — so if you're ready to make a difference while enjoying the journey, come join us and let's Tango!We are looking for a Platform Engineering Manager to join our dynamic and growing Platform Engineering team. About the Role: We are seeking a Platform Engineering Manager to serve as a true player-coach, with the role split between people leadership and hands-on technical contribution. You will lead, develop, and set direction for the Platform Engineering team while remaining deeply involved in the work—designing architecture, contributing to infrastructure and automation, troubleshooting complex issues, and helping operate the platform alongside your engineers.You will own our AI-native Internal Developer Platform (IDP), multi-cloud infrastructure across AWS and Azure, golden paths, observability, shared services, and cloud modernization aligned with Well-Architected Frameworks. You will also partner closely with peer engineering leaders to migrate teams onto the platform and establish it as the organization’s production-ready, AI-first engineering foundation.Key Responsibilities:Platform Strategy & ArchitectureOwn and execute the Platform roadmap: compute, networking, identity, observability, shared services, and AI/MLtooling across AWS and AzureLead cloud modernization against the AWS and Azure Well-Architected Frameworks across all five pillars:operational excellence, security, reliability, performance efficiency, and cost optimizationDefine golden paths - standardized self-service workflows for service scaffolding, DB provisioning, environmentspin-up, and AI workload deployment - with escape hatches for edge casesOwn multi-cloud strategy; ensure consistent IAM, networking, and FinOps governance across providersIaC & CI/CD AutomationDrive OpenTofu/Ansible as source of truth for all infrastructure; enforce GitOps and policy-as-code for governance,auditability, and securityBuild and mature CI/CD pipelines (GitHub Actions, ArgoCD) to maximize deployment frequency, reduce lead time,and enable zero-ticket self-service provisioningObservabilityOwn org-wide observability: metrics, logs, traces, and alerting – extended to AI/LLM signals (token usage, modellatency, inference cost, agent task completion rates)Operate a centralized observability platform (Datadog/Signoz, OpenTelemetry, Grafana/Prometheus/Loki, orequivalent) delivered via golden paths; define SLIs/SLOs as onboarding defaults for all servicesEnsure full-stack coverage across infrastructure, Kubernetes, APM, distributed tracing, AI pipelines, and costanomaly detectionShared ServicesBuild and operate a self-service shared services catalog: secrets management, API gateways, model registries, andLLM gatewaysRationalize duplicative per-team infrastructure; maintain shared services to production SLA standards with clearownership and consistent security controlsAI Platform & Agentic InfrastructureOwn GPU/accelerated compute, model serving, vector databases, RAG pipelines, and LLM API gatewaymanagement (AWS Bedrock, Azure OpenAI, Anthropic)Build AI golden paths for self-service model deployment and LLM integration; design agentic infrastructure includingorchestration runtimes, tool registries, memory/state services, and human-in-the-loop workflowsEstablish governance, cost controls, prompt injection guardrails, and model access policies for AI API usage andinference spendPartner with data science and ML engineering to translate agentic workflow requirements into reusable platformprimitivesPlatform Adoption & Team MigrationCollaborate on migration program: partner with peer managers to plan and execute structured workload migrationsonto the platform with hands-on support - not just documentationDefine onboarding playbooks covering golden paths, shared services, observability setup, CI/CD cutover, and AIcapability onboarding; track and report adoption metrics to leadershipIdentify and remove migration blockers - technical gaps, missing services, or organizational friction — and feedthem into the platform roadmapDeveloper Experience, Leadership & CultureBuild a self-service developer portal (Backstage, GitHub or equivalent) with service catalogs, golden paths, andAI/agentic workflow templates; track DORA metrics and developer experience KPIsHire, develop, and retain high-performing platform engineers; build AI fluency across the team and foster a platform-as-a-product culture with feedback loops, OKRs, and iterative roadmappingLead architecture reviews; make pragmatic build-vs-buy decisions; partner with security and compliance ongovernance prioritiesSecurity, Compliance & FinOpsEmbed secure-by-default guardrails: IaC scanning, RBAC, secrets management, container hardening, and AI-specificcontrols (prompt injection defense, model access governance, data residency)Own cloud cost optimization across AWS and Azure including AI inference spend; maintain SOC 2/ISO 27001compliance postureAbout You:Required8+ years in infrastructure, DevOps, or platform engineering; 2+ years in engineering managementCloud: Deep hands-on AWS and Azure expertise: multi-cloud architecture, IAM, networking, compute, and AI/MLservices (SageMaker, Bedrock, Azure OpenAI, Azure ML)IaC & CI/CD: Terraform required; GitOps, policy-as-code; GitHub Actions / ArgoCD at scaleDP: Proven track record building an IDP with self-service workflows, golden paths, and developer portal (Backstage,GitHub, or equivalent)Observability: OpenTelemetry, Datadog, Signoz, or Prometheus/Grafana at scale; SLI/SLO definition andenforcementShared Services: Built and operated multi-team shared service catalogs with production-grade SLAsAdoption: Led structured platform migration and adoption programs in partnership with peer engineering leadersKubernetes & WAF: Kubernetes cluster management, Helm, RBAC, service mesh; AWS and Azure Well-ArchitectedFramework reviewsStrong cross-functional influencing skills; comfortable as a peer to engineering managers and product leadersNice to HaveAWS SA Pro / Azure Expert / CKA/CKAD | Python, Go, or BashWhat We OfferWe’re committed to creating an environment where you can thrive—professionally and personally. Our offerings include:Competitive Compensation We recognize and reward your contributions with a salary package that reflects your value.Comprehensive Benefits Including health, dental, and vision insurance, a 401(k) plan with company match, and generous paid time off to support your well-being.Flexible Work Environment Whether remote, hybrid, or in-office, we support work arrangements that promote productivity and balance.Inclusive & Collaborative Culture We foster a workplace where diverse perspectives are valued, teamwork is encouraged, and everyone has a voice.Tango is proud to be an equal opportunity employer. We are committed to equal opportunity regardless of race, ethnicity, religion, parental status, sexual orientation, age, citizenship, disability, or veteran status.Base pay offered is contingent on qualifications and other operational considerations. Base pay is just one piece of the full compensation structure offered at Tango. If this pay range is outside of your expectations, we still encourage you to apply and have a conversation with us.Base pay offered for this position is: $180,000 - 220,000 (+10% annual bonus)