Senior Engineering Manager, Agentic AI for Finance

THE ROLE

The next leap in enterprise Finance will not come from automating what we already do; it will come from making Finance intelligent — helping the Office of the CFO move from gatekeepers to growth catalysts with faster insight, stronger controls, and better decisions at enterprise scale.

At Everpure, we do not layer AI on top of legacy workflows — we redesign the work itself. Inside the Office of the CFO, our newly formed Finance AI Factory carries a clear mandate: build AI-native Finance from the ground up — agents that surface insight as events happen, documents that are read, routed, and processed under control, and decisions backed by models that are accurate, auditable, and trusted at enterprise scale.

You’ll build the team and the technology with it. As Senior Engineering Manager, Agentic AI for Finance, you’ll hire and lead a high-performing Finance AI Factory engineering team from scratch — designing and shipping production-grade, control-aware AI agents that transform how Finance closes the books, applies cash, reconciles accounts, and executes core workflows. This is a hands-on leadership role — roughly 60% architecture and technical delivery, 40% people leadership — for a builder-turned-manager who can set technical direction, raise the bar on quality, coach a high-caliber team, and translate complex finance process pain into trustworthy automation.

WHAT YOU'LL DO

• Own the end-to-end agentic AI architecture for Finance — agent patterns, orchestration, tool integration, retrieval, reusable frameworks, secure enterprise integrations, and production-grade implementation standards.
• Build and lead a high-performing AI Factory engineering team — technical direction, delivery planning, coaching, performance input, hiring support, and operating cadence — while staying close enough to design systems, review technical decisions, and unblock delivery.
• Embed governance and controls by design — human-in-the-loop gates, audit logging, explainability, guardrails, authorization, and evaluation — so every agent operating near the general ledger is safe, auditable, and adopted by Finance and Audit.
• Deliver and maintain the agent roadmap — from document extraction through close, reconciliation, accruals, prepaid, payroll, fixed assets, and order-to-cash agents — owning build quality, reliability, monitoring, failure handling, and cost management.
• Bridge Finance and IT — translating complex, real-world finance process pain into precise agent specs, and keeping agents integrated with the systems of record without duplicating them.
• We are primarily an in-office environment and therefore, you will be expected to work from the Bangalore office in compliance with Everpure's policies, unless you are on PTO, or work travel, or other approved leave.

WHAT YOU BRING

You don’t need to check every box. The core is deep finance fluency, hands-on AI and automation experience, and the ability to lead transformation through influence — strength across several of the rest rounds out the profile.

• Experience: 12+ years of progressive leadership in software, data, or AI engineering, including hands-on time as a technical lead or architect shipping and scaling production systems.
• Production agentic AI: You've built, deployed, or operated production LLM, agentic AI, or AI-enabled workflow systems in Python, with strong experience in RAG, tool orchestration, structured outputs, memory management, evaluation, and production monitoring. You're fluent with modern agent, observability, and vector-search tooling (e.g., LangChain, LangGraph, Langfuse, Pinecone, Chroma), and have used tools in this class to move AI systems from prototype through reliable production.
• AI architecture: You've designed scalable, reusable agent or AI frameworks on cloud-native AI platforms such as AWS, with containerized deployment, secure enterprise integrations, and production-grade reliability patterns.
• Controls and governance: You've designed or owned AI governance and controls — human-in-the-loop design, audit logging, explainability, authorization, guardrails, and evaluation — in a regulated, enterprise, or financially material environment.
• Engineering leadership: You've led and mentored data, AI, or software engineers as a hands-on player-coach, owning technical direction and engineering standards while staying close to the build. You can translate technical complexity into business impact for non-technical leaders.
• Finance-domain judgment: You've worked closely with core finance processes — close, reconciliation, journal entries, AR/AP, order-to-cash, payroll, fixed assets, or SOX/controls — enough to design AI that is safe to operate near the general ledger.

#LI-ONSITE