Senior Staff Software Engineer, Agentic Applications
Enterprise Platform Group · Commercialization (Quote-to-Cash) · Mountain View, CA
As a Senior Staff Software Engineer on the Agentic Applications team, you will be the hands-on technical lead for how Databricks quotes, orders, bills and recognizes revenue. Your core function is to build bespoke first-party, agents-first applications built on the Databricks Data Intelligence Platform. You will own the technical architecture end to end, from quote to cash. You will design agents that work reliably inside revenue-critical workflows, set the engineering standards the team builds on, and make sure every agent-assisted decision can be observed, audited and trusted by Finance, Deal Desk and Sales.
This is a hands-on technical leadership role, not a people-management role. You will write code, review designs, and be the most senior technical voice in a domain that touches every dollar Databricks books.
The impact you'll have
- Own the agentic architecture for Quote-to-Cash. Define and lead the target technical architecture across Configure-Price-Quote, deal management, ordering, subscriptions, investments, billing and revenue recognition. Drive the move from vendor-configured workflows to first-party, AI-native applications built on Databricks Apps, Lakebase, Unity Catalog and Mosaic AI.
- Build production agents that sellers and Deal Desk trust. Design and ship LLM-powered agents for deal guidance, quote generation and summarization, multi-option proposals, approval insights, and pricing and discount recommendations. Work directly with sales, Deal Desk and Finance to define what "good" looks like for each workflow.
- Make agent reliability a core system property. Own the eval and quality system for this domain: per-workflow quality criteria, offline eval suites, LLM-as-judge and human-labeled benchmarks, behavioral regression testing in CI/CD, online tracing, and feedback loops that improve agents based on what users approve, edit and reject.
- Design human-in-the-loop controls for revenue-critical decisions. Build the separation between what an agent proposes and what gets committed, plus diff-based review, approval routing, audit logging, and policy guardrails. Together these decide when an agent can act on its own and when a person has to approve, especially for pricing, discounting, contract terms and order creation.
- Treat systems of record as agent tools. Architect tool-calling and MCP-style interfaces that give agents governed, run-time access to pricing, product catalog, order, contract, subscription and billing data. Follow single-source-of-truth principles across CRM, ERP and billing systems.
- Protect financial integrity at scale. Make sure agent-assisted quoting and ordering produce accurate, compliance-grade outputs downstream: order validation, billing, invoicing and revenue recognition, where errors directly affect financial reporting.
- Lead the migration path. Act as the bridge between today's production quoting platform and the target agentic architecture. Sequence the migration so the business keeps scaling without disruption, and decide what to retire, rebuild or wrap.
- Raise the engineering bar. Lead architecture reviews, establish design patterns for agents (orchestration, memory, retrieval, tool use, multi-agent coordination), and mentor senior and mid-level engineers on production-grade agentic engineering.
- Earn cross-functional credibility. Partner with Finance, Deal Desk, Sales Ops, Legal and the broader Platform engineering org. Turn complex commercial processes into clear technical roadmaps and measurable business outcomes.
What we look for
- 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, RAG 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: API and service design, data modeling, idempotency, consistency and transactional integrity, and observability.
- Proven experience designing human-in-the-loop systems: 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. You are comfortable 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.
Nice to have
- 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 (e.g., Salesforce CPQ/Revenue Cloud, NetSuite, Zuora). Platform-specific configuration expertise is a plus but not a requirement.
- Experience with the Databricks platform (Databricks Apps, Lakebase, Unity Catalog, Mosaic AI Agent Framework, MLflow tracing and evaluation).
- Familiarity with SOX controls, audit requirements, and financial-systems compliance.
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
Zone 1 Pay Range
$233,900—$321,650 USD
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.