Virtasant logo
Virtasant

We are a global, diverse team of cloud experts building the next generation of cloud solutions.

Staff Backend Engineer – FinOps, AI Cost Intelligence Platform

Backend EngineerSoftware EngineerFull TimeRemoteLeadTeam 51-200H1B No SponsorCompany SiteLinkedIn

Location

United States

Posted

1 day ago

Salary

0

Seniority

Lead

Bachelor Degree8 yrs expEnglishAWSCloudJavaPythonSDLC

Job Description

Staff Backend Engineer – FinOps, AI Cost Intelligence Platform

Virtasant

• Design and build backend-heavy platform features for our platform • Productionalise AI-enabled capabilities (e.g. anomaly detection, recommendations, agent-based workflows) • Implement AI thoughtfully across the entire SDLC - prototyping, testing, iteration, and deployment • Design and build distributed data pipelines that process cloud billing, usage, and AI telemetry • Build reliable systems that handle backfills, late-arriving data, and historical reprocessing • Design scalable data models and APIs that power customer-facing analytics and AI cost insights • Collaborate closely with Product to turn vision into shipped features • Identify blockers early, communicate clearly, and iterate fast • Help shape engineering standards and patterns as the product matures • Build AI features with explicit evaluation criteria, feedback loops, and guardrails (accuracy, latency, cost, and explainability) so models improve predictably over time

Job Requirements

  • 8+ years of professional software engineering experience, with deep backend expertise in Python (Java or C++ as secondary languages)
  • Experience building and operating data-intensive backend systems or pipelines in production
  • Strong understanding of data modelling, reliability, and data processing
  • Ability to design scalable systems and take them from concept through production
  • Experience with AI driven development to accelerate and drive product development
  • Hands-on experience building on AWS
  • Demonstrated experience using AI in real production systems (not just experimentation - clear, repeatable patterns)
  • Comfortable working in ambiguity with product-led direction
  • Ability to architect backend services that support asynchronous workflows, event-driven pipelines, and AI agents that operate over time rather than single request/response cycles
  • Comfort articulating why certain AI approaches were not used, including trade-offs around latency, explainability, data availability, or long-term maintainability.

Benefits

  • High ownership, high trust environment
  • Opportunity to own and shape technical delivery at scale
  • Work closely with experienced engineering and delivery teams
  • Exposure to broader cloud optimisation and consulting initiatives over time

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