Staff Backend Engineer – FinOps, AI Cost Intelligence Platform

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🕒 July 16

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Virtasant

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

🏢 Enterprise

🤝 B2B

Consulting • Enterprise • B2B

Virtasant is a cloud services and optimization company that helps businesses migrate to, manage, and build on public cloud platforms. They combine a proprietary automation platform with managed services and FinOps expertise to reduce cloud costs (claiming average savings of over 50%), support Cloud FinOps programs, and deliver outcome-based engagements rather than hourly or seat-based billing. Virtasant also provides enterprise AI guidance and partners with major cloud providers (AWS, Google Cloud, Azure) to deliver migration, optimization, and 24/7 managed operations.

📋 Description

• 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

🎯 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