Summary
What you’ll impact
The Senior Backend Engineer designs, builds, and maintains high‑throughput, low‑latency services that orchestrate AI agents for enterprise procurement and payment workflows. They use Python, Go, or Node.js to create microservice APIs, integrate with ERP and financial systems, and manage SQL/NoSQL data stores. Responsibilities include building workflow orchestration, rule‑engine compliance layers, secure data pipelines, and full observability and audit capabilities for AI decisions. They work with product and AI teams to define performance standards, develop testing frameworks, and mentor peers on reliability best practices.
Responsibilities
What you'll do
- High-throughput, low-latency backend services that power AI agent execution
- Workflow orchestration systems for complex, multi-step enterprise processes
- Rule engines and policy enforcement layers for enterprise compliance
- APIs and integrations with ERPs, procurement tools, payment rails, and data providers
- Observability, audit, and traceability systems for AI-driven decisions
- Secure data pipelines handling sensitive financial and operational data
- Agent execution runtimes, multi-agent coordination, and observability pipelines for AI-driven workflows
- Evaluation and testing harnesses to validate agent behaviour, reliability, and output quality
- Design and build scalable backend services using modern system design principles
- Own critical services that manage procurement, invoice, contract, and payment workflows
- Implement orchestration logic that coordinates AI agents, humans, and enterprise systems
- Build resilient systems with strong guarantees around idempotency, retries, and failure handling
- Build and maintain robust APIs consumed by AI services, frontend apps, and external systems
- Integrate deeply with ERP systems, procurement platforms, and payment gateways and financial rails
- Handle complex data normalisation and transformation across enterprise systems
- Build agent execution runtimes: tool calling, context management, memory, and multi-step reasoning loops
- Implement multi-agent coordination—parallel and sequential workflows with human-in-the-loop escalation
- Instrument agent execution with full trace capture: tool calls, LLM I/O, latency, token usage, and cost
- Design evaluation frameworks for agent output quality, task success rate, and regression detection
- Build automated test harnesses for agent pipelines—unit, integration, and replay-based regression tests
- Define and track agent reliability metrics: task completion rate, escalation rate, cost per workflow, and SLA adherence
- Design systems with enterprise-grade reliability, monitoring, and alerting
- Implement fine-grained access controls, audit logs, and data security best practices
- Ensure backend systems meet compliance requirements for financial and regulated data
- Optimize backend systems for latency, throughput, and cost efficiency
- Design services that scale across global customers and billions of transactions
- Proactively identify and fix bottlenecks in distributed systems
Requirements
What you’ll bring
- 6-15 years experience building strong production backend systems
- Strong proficiency in Python, NodeJS, Go, or similar backend languages
- Deep understanding of distributed systems, APIs and microservices, databases (SQL and NoSQL), and message queues / event-driven architectures
- Proven experience designing scalable, fault-tolerant systems
- Strong grasp of consistency, concurrency, and data integrity trade-offs
- Experience working with financial systems, enterprise SaaS platforms, or sensitive/regulated data
- Comfort operating in environments where backend failures have a real business impact