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Databricks

Builds cloud software for data analysis and AI

Senior Staff Software Engineer - Agentic Applications

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeMountain View, CA, USAIn-person

About the Job

Requirements

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

Responsibilities

  • Own the target technical architecture for Quote-to-Cash across Configure-Price-Quote, deal management, ordering, subscriptions, investments, billing and revenue recognition, and lead the move from vendor-configured workflows to first-party, AI-native applications built on Databricks Apps, Lakebase, Unity Catalog and Mosaic AI.
  • Design and ship 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 success for each workflow.
  • Own the domain's evaluation and quality system, including per-workflow quality criteria, offline evaluation suites, LLM-as-judge and human-labeled benchmarks, behavioral regression testing in CI/CD, online tracing, and feedback loops based on user approvals, edits and rejections.
  • Build human-in-the-loop controls that separate agent proposals from committed decisions, including diff-based review, approval routing, audit logging and policy guardrails; determine when agents may act autonomously and when human approval is required, especially for pricing, discounting, contract terms and order creation.
  • Architect tool-calling and MCP-style interfaces that provide agents governed, run-time access to pricing, product catalog, order, contract, subscription and billing data, while maintaining 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.
  • Sequence the migration from the current production quoting platform to the target agentic architecture so the business can scale without disruption, and decide what to retire, rebuild or wrap.
  • Lead architecture reviews, establish agent design patterns for orchestration, memory, retrieval, tool use and multi-agent coordination, and mentor senior and mid-level engineers on production-grade agentic engineering.
  • Partner with Finance, Deal Desk, Sales Ops, Legal and the broader Platform engineering organization to translate commercial processes into technical roadmaps and measurable business outcomes.

Desired Qualifications

  • 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, and MLflow tracing and evaluation.
  • Familiarity with SOX controls, audit requirements and financial-systems compliance.

About the Company

Databricks

Builds cloud software for data analysis and AI

Databricks builds cloud software that businesses use to organize data, analyze it, and develop AI applications. Its lakehouse architecture brings the flexible storage of a data lake together with the querying and management tools of a data warehouse. Data engineers prepare and update datasets, analysts build reports, and developers train models or create applications in a shared workspace with controls over who can use the data. The platform runs on Amazon, Microsoft, and Google clouds, and customers pay for computing usage or commit to longer contracts for discounted rates. Databricks was founded in 2013 and is headquartered in San Francisco, California.

Company size
10,001+
Company stage
Late Stage VC
Total funding
$32.1B
Headquarters
San Francisco, CA
Founded
2013

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