Staff Backend Engineer – FinOps, AI Cost Intelligence Platform

This is a fully remote position, open to applicants in United States.

📋 Description

• Create and develop backend-focused platform features for our system.

• Operationalize AI-driven capabilities such as anomaly detection, recommendations, and agent-based workflows.

• Implement AI thoughtfully throughout the entire software development lifecycle - including prototyping, testing, iteration, and deployment.

• Design and develop distributed data pipelines that manage cloud billing, usage, and AI telemetry.

• Construct dependable systems that accommodate backfills, late-arriving data, and historical reprocessing.

• Develop scalable data models and APIs that drive customer-facing analytics and AI cost insights.

• Collaborate closely with the Product team to transform vision into delivered features.

• Proactively identify obstacles, communicate effectively, and iterate rapidly.

• Contribute to establishing engineering standards and practices as the product evolves.

• Create AI features with defined evaluation criteria, feedback loops, and safeguards (accuracy, latency, cost, and explainability) to ensure models enhance predictably over time.

⛳️ Requirements

• Over 8 years of professional software engineering experience, with extensive backend proficiency in Python (Java or C++ as additional languages).

• Experience in developing and managing data-intensive backend systems or pipelines in a production environment.

• Strong grasp of data modeling, reliability, and data processing principles.

• Capability to design scalable systems and bring them from concept to production.

• Familiarity with AI-driven development to accelerate and enhance product development.

• Practical experience working on AWS.

• Proven track record of utilizing AI in real production systems (beyond mere experimentation - established, repeatable patterns).

• Comfortable navigating ambiguity with a product-led focus.

• Ability to architect backend services that facilitate asynchronous workflows, event-driven pipelines, and AI agents operating over time rather than in single request/response cycles.

• Proficient in explaining why certain AI methodologies were not adopted, including trade-offs concerning latency, explainability, data availability, or long-term maintainability.

🏝️ Benefits

• High ownership, high trust environment.

• Opportunity to take ownership and influence technical delivery at scale.

• Collaborate closely with experienced engineering and delivery teams.

• Gain exposure to broader cloud optimization and consulting initiatives over time.