Everpure Applied AI
Senior AI Engineer, Agentic AI for Finance
- Location Bangalore, India
- Seniority senior
- Posted 2026-10-29
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role details
Architect, build, and deploy production-grade multi-agent systems and platform components for finance.
Summary generated by AI from the original posting.
Hard requirements to check first
- Clearance：not mentioned in the posting
- Work auth：not mentioned in the posting
Skills
PythonTypeScriptSQLRAGAWSSnowflakeReactEvalsAgentsMCPObservabilityLangGraphAmazon Bedrock AgentCoreModel Context Protocol (MCP)
Excerpt from the original posting
Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. Senior AI Engineer, Agentic AI for Finance THE ROLE Join the AI Factory as a founding engineer driving the Office of the CFO's mission to transform Finance into an agile strategic advisor delivering enterprise-wide productivity and insight. In this high-impact technical contributor role, you will autonomously architect, build, and deploy production-grade multi-agent systems and foundational platform components. You will set technical direction for internal engineers and vendor partners, writing production code daily while maintaining rigorous alignment with the Everpure™ platform architecture. WHAT YOU'LL DO - Architect and deploy multi-agent workflows: Design, ship, and own end-to-end multi-agent systems using LangGraph and Amazon Bedrock AgentCore, ensuring financial calculations, business logic, and outputs remain fully deterministic, auditable, and production-ready. - Build enterprise tool integrations and secure data access: Create secure, least-privilege Model Context Protocol (MCP) tools across core systems (ERP, CRM, ticketing) and implement grounded retrieval architectures and read-only query layers on Snowflake to deliver trusted operational insights. - Deliver enterprise-grade user interfaces and approval portals: Develop performant Next.js portals, administrative consoles, and human-in-the-loop review interfaces to enable business teams to validate outputs and maintain strict governance seamlessly. - Implement robust AI guardrails, safety, and evaluation frameworks: Establish automated evals, shadow-mode validation pipelines, role-based access controls, audit logging, and prompt-injection defenses to safeguard regulated financial workflows before release. - Drive operational reliability and collaborative technical excellence: Monitor platform accuracy, drift, latency, and cost using observability tools like Datadog and Langfuse, while guiding vendor and in-house engineers through rig…
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