Staff Engineer

Experience: 8–15 Years

Location: India (Remote)

Most AI companies are building tools., we're building the worker.

builds AI agents that automate the decision-making and coordination layer behind enterprise software, handling analysis, negotiation, prioritization, and execution across complex supply chain and business operations.

Our customers include Apple, Meta, GE, Pfizer, Johnson & Johnson, Schlumberger, Cardinal Health, and Unilever. They choose because we're rethinking what enterprise software can achieve when AI can execute work autonomously.

If you want to solve challenging engineering problems, build systems that matter, and work with a team that values ownership, initiative, and accountability, is the place for you.

About the Role

As a Staff Engineer, you will design and build the distributed systems, APIs, and AI agent infrastructure that power AI-driven enterprise execution platform.

You'll develop scalable backend services that orchestrate AI agents, enforce business rules, integrate with enterprise resource planning (ERP) and financial systems, and ensure that every AI-driven action is secure, traceable, and reliable.

This role goes beyond traditional SaaS development. You'll build the backend infrastructure for autonomous systems that manage real money, business-critical workflows, and operational risk.

Key Responsibilities

1. Backend & Systems Engineering

• Design, develop, and maintain scalable, high-performance backend services.
• Build reliable systems using modern distributed systems and software architecture principles.
• Own critical services supporting procurement, invoicing, contracts, and payment workflows.
• Implement resilient systems with idempotency, retries, concurrency controls, and robust failure handling.
• Identify and resolve performance bottlenecks across distributed systems.2. API Development & Enterprise Integrations
• Build and maintain robust APIs for AI services, frontend applications, and external systems.
• Integrate with ERP platforms, procurement tools, payment gateways, and financial systems.
• Develop data normalization and transformation pipelines across enterprise platforms.
• Ensure data integrity, security, and consistency across integrations.3. AI Agent Infrastructure & Orchestration
• Build agent execution runtimes, including tool calling, context management, memory, and multi-step reasoning workflows