Senior Backend / Product Engineer (AI Platform)
Location: Remote
Type: Full-time
Team: Cost Optimisation (CO) – Product Engineering
Reports to: Product Lead (CO)
About Virtasant
- 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.
The Role
- 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.
What You'll Be Doing
- 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.
What We're Looking For (Non-Negotiables)
- 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
What This Role Is Not
- 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.
Why This Role Stands Out
- 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.
Why Virtasant
- 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
