Platform Engineering Manager

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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 build and operate our AI-native Internal Developer Platform (IDP)-

the foundational layer that powers engineering velocity across the organization. You will own multi-cloud

infrastructure (AWS & Azure), define golden paths, drive cloud modernization aligned to Well-Architected

Frameworks, and deliver the observability, shared services, and agentic infrastructure that give every team a

production-ready foundation. A defining dimension of this role is partnering with peer engineering leaders to actively

migrate teams onto the platform and positioning it as the organization's AI-first engineering foundation.

Key Responsibilities:

Platform Strategy & Architecture

• Own and execute thePlatformroadmap: compute, networking, identity, observability, shared services, and AI/ML

  tooling across AWS and Azure

• Lead cloud modernization against the AWS and Azure Well-Architected Frameworks across all five pillars:

  operational excellence, security, reliability, performance efficiency, and cost optimization

• Define golden paths-standardized self-service workflows for service scaffolding, DB provisioning, environment

  spin-up, and AI workload deployment-with escape hatches for edge cases

• Own multi-cloud strategy; ensure consistent IAM, networking, and FinOps governance across providers

IaC & CI/CD Automation

• DriveOpenTofu/Ansibleas source of truth for all infrastructure; enforce GitOps and policy-as-code for governance,

  auditability, and security

• Build and mature CI/CD pipelines (GitHub Actions, ArgoCD) to maximize deployment frequency, reduce lead time,

  and enable zero-ticket self-service provisioning

Observability

• Own org-wide observability: metrics, logs, traces, and alerting-extended to AI/LLM signals (token usage, model

  latency, inference cost, agent task completion rates)

• Operate a centralized observability platform (Datadog/Signoz, OpenTelemetry, Grafana/Prometheus/Loki, or

  equivalent) delivered via golden paths; define SLIs/SLOs as onboarding defaults for all services

• Ensure full-stack coverage across infrastructure, Kubernetes, APM, distributed tracing, AI pipelines, and cost

  anomaly detection

Shared Services

• Build and operate a self-service shared services catalog: secrets management, API gateways,model registries, and

  LLM gateways

• Rationalize duplicative per-team infrastructure; maintain shared services to production SLA standards with clear

  ownership and consistent security controls

AI Platform & Agentic Infrastructure

• Own GPU/accelerated compute, model serving, vector databases, RAG pipelines, and LLM API gateway

  management (AWS Bedrock, Azure OpenAI, Anthropic)

• Build AI golden paths for self-service model deployment and LLM integration; design agentic infrastructure including

  orchestration runtimes, tool registries, memory/state services, and human-in-the-loop workflows

• Establish governance, cost controls, prompt injection guardrails, and model access policies for AI API usage and

  inference spend

• Partner with data science and ML engineering to translate agentic workflow requirements into reusable platform

  primitives

Platform Adoption & Team Migration

• Collaborate onmigration program: partner with peer managers to plan and execute structured workload migrations

  onto the platform with hands-on support-not just documentation

• Define onboarding playbooks covering golden paths, shared services, observability setup, CI/CD cutover, and AI

  capability onboarding; track and report adoption metrics to leadership

• Identify and remove migration blockers-technical gaps, missing services, or organizational friction-and feed

  them into the platform roadmap

Developer Experience, Leadership & Culture

• Build a self-service developer portal (Backstage, GitHubor equivalent) with service catalogs, golden paths, and

  AI/agentic workflow templates; track DORA metrics and developer experience KPIs

• Hire, 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 roadmapping

• Lead architecture reviews; make pragmatic build-vs-buy decisions; partner with security and compliance on

  governance priorities

Security, Compliance & FinOps

• Embed secure-by-default guardrails: IaC scanning, RBAC, secrets management, container hardening, and AI-specific

  controls (prompt injection defense, model access governance, data residency)

• Own cloud cost optimization across AWS and Azure including AI inference spend; maintain SOC 2/ISO 27001

  compliance posture

About You:

Required

• 8+ years in infrastructure, DevOps, or platform engineering; 2+ years in engineering management
• Cloud: Deep hands-on AWS and Azure expertise: multi-cloud architecture, IAM, networking, compute, and AI/ML

  services (SageMaker, Bedrock, Azure OpenAI, Azure ML)

• IaC & CI/CD: Terraform required; GitOps, policy-as-code; GitHub Actions / ArgoCD at scale
• DP: 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 and

  enforcement

• Shared Services: Built and operated multi-team shared service catalogs with production-grade SLAs
• Adoption: Led structured platform migration and adoption programs in partnership with peer engineering leaders
• Kubernetes & WAF: Kubernetes cluster management, Helm, RBAC, service mesh; AWS and Azure Well-Architected

  Framework reviews

• Strong cross-functional influencing skills; comfortable as a peer to engineering managers and product leaders

Nice to Have

• AWS SA Pro / Azure Expert / CKA/CKAD | Python, Go, or Bash

What We Offer

We’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: $160,000 - 200,000 (+10% annual bonus)