Senior Backend

Location: Remote
Type: Full-time
Team: Cost Optimisation (CO) – Product Engineering
Reports to: Product Lead (CO)

Virtasant is a global technology services company with a network of over 4,000 professionals across 130+ countries. We specialise in cloud architecture, engineering, and transformation, helping enterprises deliver at scale while building internal capability and reducing third-party dependency.

We work with ambitious, forward-thinking organisations to solve real-world challenges through hands-on execution, deep technical expertise, and a delivery-led approach.

We're hiring a senior backend-first product engineer to help build and scale our AI-powered cost intelligence platform.

This role is explicitly product-focused. You will not be pulled into client delivery. Your mission is to build core platform capabilities that mature our current FinOps platform into a smart intelligence platform - including AI-driven insights, workflows, and agent-based features that can be sold as standalone capabilities.

You'll operate with high autonomy, significant ownership, and direct access to product leadership. Think founding engineer energy , without the chaos.
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.

• 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.

• 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.

• Design systems that support model evaluation, prompt/version management, and deterministic fallbacks to ensure AI-driven features are observable, testable, and production-safe.

• Build AI features with explicit evaluation criteria, feedback loops, and guardrails (accuracy, latency, cost, and explainability) so models improve predictably over time.

Success in the first 6–12 months looks like:

• 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 professional software engineering experience.

• Strong backend engineering background (full-stack a plus, not required).

• Hands-on experience building on AWS.

• Strong proficiency in Python (Java/C++ acceptable as secondary languages).

• 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.

What Matters More Than Checklists

We care deeply about how you think and build, not just what tools you've used.

We're looking for engineers who can:

• Tell a compelling story about a product journey, not just features shipped

• Explain why decisions were made and what trade-offs were considered

• Fail fast, learn quickly, and iterate relentlessly

• Clearly articulate technical roadblocks and collaborate on solutions

• Thrive in a fast-paced, high-ownership environment

• Not a Solutions Architect role.

• Not client-facing delivery work.

• Not a support or "overflow" engineering position.

This role is protected, by design, to focus on product and platform.

• 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.

• 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.