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Salary
≈ $18k – $39k per year (Estimated)
Location
In office (Mumbai)
Seniority
Senior · 7+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 14, 2026. First seen by Alion on Oct 5, 2026.

Overview
Company
Impact
Profile match
Clearwater delivers a unified, front-to-back investment management platform for institutional investors across public and private markets, risk, and data in real time.

About the Team

Beacon by Clearwater is the AI-powered risk analytics and modeling arm of the Clearwater platform, giving institutional investors the tools to test scenarios and evaluate portfolio exposures in real time.

As Clearwater brings Beacon to more clients, the number of client environments we provision, monitor, and support grows with it and the only way that works is through standardization and automation. This team builds the tooling that keeps a growing fleet of client deployments consistent, observable, and supportable: automating away repetitive operational work, turning incident learnings into permanent platform fixes, and giving client-facing teams the self-service tools they need to onboard and support clients without engineering escalations.

What You’ll Do

  • Build internal tools and automation primarily in Python to monitor, diagnose, and support a fleet of client deployments across AWS and Azure.
  • Drive standardization across client environments: detect and remediate configuration and infrastructure drift, converge legacy deployments onto golden paths, and make “the standard way” the easy way.
  • Improve fleet-wide observability: build monitoring, alerting, and dashboards that surface problems across all client deployments before clients notice them.
  • Turn runbooks into code; converting the manual diagnostic and remediation steps support engineers perform today into automated checks, self-healing jobs, and one-click tools.
  • Extend the client provisioning and deployment pipeline (Terraform, configuration generation) to make onboarding new clients faster and more repeatable.
  • Work directly with client-facing teams (onboarding, support, client success) to find where operational toil lives.

What We’re Looking For

  • 7-10 years of experience in software engineering, site reliability engineering, DevOps, or platform engineering.
  • Strong programming skills in Python (our platform core and tooling language); comfort writing production-quality code with tests, not just scripts.
  • Hands-on experience with at least one major cloud provider (AWS or Azure): networking (VPCs/VNets, subnets, security groups, load balancers, VPN), IAM/RBAC, storage, and compute.
  • Working knowledge of infrastructure-as-code, ideally Terraform, and what it means to manage many environments from shared modules and per-environment configuration.
  • Solid Linux fundamentals: you can read logs, trace a process, debug a service that won’t start, and automate what you did, so no one must do it by hand again.
  • An automation reflex: when you solve a problem twice, your instinct is to build a tool.
  • A collaborative, service-oriented mindset: your customers are internal teams, and your success is measured by how much easier you make their jobs.

Nice to Have

  • Experience operating multi-tenant or fleet-style environments (many similar deployments managed as one).
  • Observability stack experience (metrics, log aggregation, alerting, dashboards).
  • Formal incident management experience (on-call, postmortems, blameless RCA culture).
  • Exposure to financial services, fintech, or other regulated environments.

Why This Role

  • Direct, visible impact: every tool you ship makes onboarding the next client faster and supporting every existing client cheaper. This team is a force multiplier for the entire Beacon business.
  • Breadth: you’ll touch cloud infrastructure, a large Python platform codebase, deployment pipelines, and the human workflows of support and onboarding teams.
  • Growth: you’ll work across nearly every layer of a sophisticated financial-engineering platform, alongside experts in cloud infrastructure, quantitative finance, and large-scale SaaS operations.
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