Staff Backend Engineer – FinOps, AI Cost Intelligence Platform

Virtasant

Staff Backend Engineer responsible for backend-first development on multi-cloud FinOps platform at Virtasant. Focusing on AI cost intelligence with high autonomy and ownership in a remote role.

Posted 7/16/2026full-timeRemote • 🇺🇸 United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in backend software engineering, particularly in Python, with a strong focus on building data-intensive systems and AI-driven features. Capable of designing scalable architectures and implementing robust data pipelines while collaborating effectively with product teams.

Highest-signal resume keywords

Backend Software EngineeringPython ProgrammingData Pipeline DevelopmentAI-Driven DevelopmentAWS Experience

ATS Keywords

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Hard Skills

Data ModellingReliability EngineeringScalable System DesignAsynchronous WorkflowsEvent-Driven PipelinesAI ImplementationAnomaly DetectionRecommendationsCloud Billing ProcessingAI Telemetry

Soft Skills

Clear CommunicationProblem SolvingCollaborationAdaptability

Industry Keywords

SDLCProduction SystemsFeedback LoopsGuardrailsLatencyExplainabilityData AvailabilityLong-Term Maintainability

Tech Stack

Tools & technologies

AWSCloudJavaPythonSDLC

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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