Virtasant

Staff Backend / Product Engineer- FinOps & AI Cost Intelligence Platform

Vaga remota de Backend Engineering com fit claro de localização do candidato.

Publicada18 de jul. de 2026

Países elegíveis1 país aceito

Sinal de senioridadeSenior

Modelo de trabalhoRemoto

Locais aceitos para candidatos

Estados Unidos

Resumo da vaga

Conteúdo da vaga extraído em seções para revisão mais rápida.

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.
You will help define how AI capabilities move from experimentation to durable product features, with an emphasis on reliability, cost efficiency, and clear user value - not just model novelty.
Build AI features with explicit evaluation criteria, feedback loops, and guardrails (accuracy, latency, cost, and explainability) so models improve predictably over time.

2+ production-ready features shipped.
Tangible progress towards operating as a smart intelligence platform.
Clear, repeatable engineering patterns for AI-enabled development.
Utilize lightweight but rigorous AI engineering practices (evaluation harnesses, rollout strategies, and rollback mechanisms) that allow the platform to scale AI features safely and repeatedly.

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.

You’ll work on a real AI product, not internal tooling or demos.
Near-founding-engineer level autonomy and influence.
Direct impact on product direction and commercial outcomes.
Opportunity to help shape a platform with standalone, licensable AI capabilities.
A rare chance to build product inside a consultancy without being consumed by client work.
You’ll build AI capabilities informed by real enterprise-scale cost and usage data, enabling smarter models and workflows than greenfield or synthetic-data products.