Sr. Staff Software Engineer, Agentic Applications

Databricks•Mountain View, CA

1d•$233,900 - $321,650

About The Position

As a Senior Staff Software Engineer on Databricks’ Agentic Applications team, you will serve as the hands-on technical lead for the systems that support quoting, ordering, billing, and revenue recognition. You will build first-party, agents-first applications on the Databricks Data Intelligence Platform and own technical architecture across the Quote-to-Cash domain. This includes designing reliable agents for revenue-critical workflows, setting engineering standards, and ensuring agent-assisted decisions are observable, auditable, and trusted by Finance, Deal Desk, and Sales. This is a hands-on technical leadership role rather than a people-management position. You will write code, review designs, and provide senior technical leadership in a domain affecting Databricks’ financial operations. You will define the target architecture across Configure-Price-Quote, deal management, ordering, subscriptions, investments, billing, and revenue recognition, and guide the transition from vendor-configured workflows to first-party, AI-native applications. You will build and evaluate production LLM-powered agents for commercial workflows; establish reliability, review, approval, audit, and policy controls; and provide agents with governed access to systems of record. You will protect the accuracy and compliance of downstream financial outputs, plan a safe migration from the current quoting platform, and partner across Finance, Deal Desk, Sales Ops, Legal, and Platform Engineering to translate business processes into technical roadmaps and measurable outcomes.

Requirements

At least 12 years of software engineering experience, with a clear record of technical leadership and ownership of large-scale production systems.
At least 3 years of hands-on experience building and operating production LLM-powered or agentic applications, such as agents, RAG pipelines, tool use, multi-agent orchestration, or evaluation frameworks for generative outputs.
Strong backend and distributed-systems skills, including API and service design, data modeling, idempotency, consistency, transactional integrity, and observability.
Experience designing human-in-the-loop systems, including approval workflows, review interfaces, audit trails, and guardrails for probabilistic systems in regulated or high-stakes domains.
Experience leading technical architecture for complex business domains; Quote-to-Cash, Order-to-Revenue, billing, pricing, or other revenue-critical enterprise systems are relevant.
Full-stack fluency across modern web frameworks such as React/TypeScript, backend services using Python, Java, Scala, or Go, and data platforms.
Ability to work directly with non-engineering stakeholders and translate ambiguous business workflows into clear agent and system architecture.
Experience mentoring engineers and improving technical execution across a team without relying on positional authority.

Nice To Haves

Domain experience with CPQ, deal management, subscription management, or revenue recognition in a high-growth SaaS or consumption-based business.
Experience building first-party applications on top of, or as replacements for, enterprise SaaS platforms such as Salesforce CPQ/Revenue Cloud, NetSuite, or Zuora; platform-specific configuration expertise is a plus but not required.
Experience with the Databricks platform, including Databricks Apps, Lakebase, Unity Catalog, Mosaic AI Agent Framework, or MLflow tracing and evaluation.
Familiarity with SOX controls, audit requirements, and financial-systems compliance.

Responsibilities

Own and lead the target agentic architecture across Quote-to-Cash, including Configure-Price-Quote, deal management, ordering, subscriptions, investments, billing, and revenue recognition.
Drive the migration from vendor-configured workflows to first-party, AI-native applications built on Databricks Apps, Lakebase, Unity Catalog, and Mosaic AI.
Design, build, and ship production LLM-powered agents for deal guidance, quote generation and summarization, multi-option proposals, approval insights, and pricing and discount recommendations.
Work with Sales, Deal Desk, and Finance to define quality expectations for agent-supported workflows.
Own the evaluation and quality system, including per-workflow criteria, offline evaluation suites, LLM-as-judge and human-labeled benchmarks, behavioral regression testing in CI/CD, online tracing, and user feedback loops.
Build human-in-the-loop controls, including separation of agent proposals from committed actions, diff-based review, approval routing, audit logging, and policy guardrails.
Architect tool-calling and MCP-style interfaces that provide agents governed, runtime access to pricing, product catalog, order, contract, subscription, and billing data.
Maintain single-source-of-truth principles across CRM, ERP, and billing systems.
Ensure agent-assisted quoting and ordering produce accurate, compliance-grade downstream outputs for order validation, billing, invoicing, and revenue recognition.
Plan and sequence migration from the current production quoting platform to the target architecture, deciding what to retire, rebuild, or wrap while avoiding business disruption.
Lead architecture reviews and establish agent engineering patterns for orchestration, memory, retrieval, tool use, and multi-agent coordination.
Mentor senior and mid-level engineers and improve technical execution across the team without relying on positional authority.
Partner with Finance, Deal Desk, Sales Ops, Legal, and Platform Engineering to turn commercial processes into technical roadmaps and measurable business outcomes.
Write code and review designs as the senior technical lead for the domain.