AI Engineer — GTM Analytics
United States · 全职 · 数据与分析
需要对标的能力
AI 应用 · 人机协同大模型原理 · LLM 基础Prompt Engineering · 提示词工程RAG · 检索增强生成Agent · 智能体设计MCP · 工具生态协议Agent 工程 · Harness / 脚手架评测 · Eval 方法论
岗位职责与要求
SLSQ327R637
At Databricks, we are passionate about enabling GTM Analytics Engineering builds the internal data and AI platform that Databricks' own go-to-market organization runs on — used by 6,000+ field users across sales, strategy, and operations. We own the number one Databricks App, the Genie agents, which are powered through the lakehouse (Unity Catalog bronze/silver/gold) beneath them. We are "Customer Zero" for Databricks: we adopt the newest Databricks and AI tooling first, in production, and pave the path for the rest of the company.
We're in the middle of a step-change — moving the app from AI/BI and Genie experience to an AI-native, genie-centric platform that delivers prescriptive recommendations (not just descriptive reports), built to scale for the next 3–5 years. We build with AI in the loop end to end, and a large and growing share of our code is AI-generated and human-reviewed.
The role
As an AI Engineer you'll help build the intelligence and application layers of that platform: Genie-powered analytics agents, LLM-driven workflows (feedback analysis, "what's new" enablement, BRD-to-plan automation), and the Databricks Apps and Lakebase services that serve them. You'll work alongside senior engineers, and you'll be expected to lean on AI coding tools heavily and thoughtfully from day one. This is a high-ownership, fast-shipping team where early-career engineers get real surface area.
What you'll do
· Build and ship features for AI-powered surfaces: Genie analytics agents, LLM-assisted feedback and enablement workflows, and in-app intelligence inside the GTM Hub.
· Develop and integrate agentic workflows — prompts, tools/MCP integrations, retrieval, and evaluation — that turn business questions into reliable, grounded answers.
· Write Python and SQL against our Databricks lakehouse (Unity Catalog, Delta) and Lakebase (Postgres) services that back the apps.
· Use AI coding tools (Claude Code, agentic skills) as a core part of your workflow, and help build the reusable skills and harnesses that make the whole team faster.
· Contribute to evaluation and quality: help measure and improve the accuracy of our AI outputs (eval sets, scorecards, regression checks).
· Partner with data engineers, app engineers, and strategy/ops stakeholders to take work from idea → ticket → PR → production.
· Write clean, well-documented, tested code and participate in code review (human and AI-assisted).
What we look for
· Bachelor's degree in Computer Science, Data Science, or a related field — or equivalent practical experience.
· 7+ years of software and AI engineering related experience.
· Solid fundamentals in Python and SQL.
· Hands-on exposure to LLMs / generative AI — prior work building with APIs, prompts, RAG, Knowledge graphs & agents.
· Genuine fluency with AI developer tools (e.g., Claude, Cursor) and a desire to push how far AI-assisted engineering can go.
· Strong problem-solving, curiosity, and a bias to ship and iterate; comfortable with ambiguity in a fast-moving team.
· Clear written and verbal communication; works well with both engineers and non-technical stakeholders.
Nice to have
· Experience with the Databricks platform (AI Gateways, notebooks, jobs, Unity Catalog, Databricks Apps, Genie) or another cloud data platform.
· Building or evaluating agentic, RAG systems; familiarity with MCP, tool-calling, or eval frameworks.
· Full-stack exposure (React/TypeScript front end, FastAPI/Python back end) or data engineering (dbt, Spark, medallion architectures).
· Experience with Postgres/OLTP, CI/CD (Databricks Asset Bundles, GitHub Actions), or analytics/BI.
Our environment
Databricks (AI Gateway, Unity Catalog, Delta, Jobs, Databricks Apps, Lakebase, Genie) · Python · SQL · React/TypeScript · FastAPI · Claude Code & agentic skills · GitHub + DABs CI/CD. We work in sprints, review each other's PRs, and treat AI as a first-class teammate — with the human judgment to know when it's wrong.
$146,600—$201,650 USD
$132,000—$181,500 USD
$124,600—$171,400 USD
$117,300—$161,250 USD
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
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
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.
查看中文参考译文
SLSQ327R637
在 Databricks,我们致力于推动 GTM Analytics Engineering 团队构建内部数据和 AI 平台——Databricks 自身 go-to-market 组织运行的基础,服务于销售、战略和运营部门的 6,000 多名 field 用户。我们拥有排名第一的 Databricks App,即 Genie agents,它们由底层的 lakehouse(Unity Catalog bronze/silver/gold)提供支持。我们是 Databricks 的"Customer Zero":我们率先在生产环境中采用最新的 Databricks 和 AI 工具,并为公司其他团队铺平道路。
我们正处于一个关键转折点——将应用从 AI/BI 和 Genie 体验转向 AI-native、genie-centric 的平台,提供 prescriptive recommendations(而非仅仅是 descriptive reports),为未来 3–5 年的规模化扩展而构建。我们在端到端流程中构建 AI in the loop,且我们代码中越来越大、不断增长的部分是 AI-generated 并由 human-reviewed 的。
The role
作为 AI Engineer,你将帮助构建该平台的 intelligence 和 application 层:Genie-powered analytics agents、LLM-driven workflows(feedback analysis、"what's new" enablement、BRD-to-plan automation),以及承载这些应用的 Databricks Apps 和 Lakebase services。你将与 senior engineers 并肩工作,并且从第一天起就被期望大量且审慎地使用 AI coding tools。这是一个 high-ownership、fast-shipping 的团队,early-career engineers 能获得真正的发挥空间。
What you'll do
· 为 AI-powered surfaces 构建和交付功能:Genie analytics agents、LLM-assisted feedback 和 enablement workflows,以及 GTM Hub 内的 in-app intelligence。
· 开发和集成 agentic workflows——prompts、tools/MCP integrations、retrieval 和 evaluation——将业务问题转化为可靠、有依据的答案。
· 针对我们的 Databricks lakehouse(Unity Catalog、Delta)和支撑应用的 Lakebase(Postgres)services,编写 Python 和 SQL。
· 将 AI coding tools(Claude Code、agentic skills)作为工作流的核心部分,并帮助构建可复用的 skills 和 harnesses,提升整个团队的效率。
· 为 evaluation 和 quality 做出贡献:帮助衡量和改进 AI outputs 的准确性(eval sets、scorecards、regression checks)。
· 与 data engineers、app engineers 以及 strategy/ops stakeholders 合作,推动工作从 idea → ticket → PR → production。
· 编写 clean、well-documented、tested 的代码,并参与 code review(human 和 AI-assisted)。
What we look for
· 计算机科学、数据科学或相关领域的学士学位——或同等的实践经验。
· 7 年以上软件和 AI engineering 相关经验。
· 扎实的 Python 和 SQL 基础。
· 具备 LLMs / generative AI 的实践经验——有使用 APIs、prompts、RAG、Knowledge graphs 和 agents 进行构建的过往经历。
· 真正熟练使用 AI developer tools(例如 Claude、Cursor),并渴望推动 AI-assisted engineering 能达到的高度。
· 强大的 problem-solving 能力、好奇心,以及 ship 和 iterate 的倾向;在 fast-moving 团队中适应 ambiguity。
· 清晰的 written 和 verbal communication;能与工程师及非技术 stakeholders 良好协作。
Nice to have
· 具备 Databricks 平台(AI Gateways、notebooks、jobs、Unity Catalog、Databricks Apps、Genie)或其他 cloud data platform 的经验。
· 构建或评估 agentic、RAG systems 的经验;熟悉 MCP、tool-calling 或 eval frameworks。
· Full-stack 经验(React/TypeScript front end、FastAPI/Python back end)或 data engineering(dbt、Spark、medallion architectures)。
· 具备 Postgres/OLTP、CI/CD(Databricks Asset Bundles、GitHub Actions)或 analytics/BI 的经验。
Our environment
Databricks(AI Gateway、Unity Catalog、Delta、Jobs、Databricks Apps、Lakebase、Genie)· Python · SQL · React/TypeScript · FastAPI · Claude Code & agentic skills · GitHub + DABs CI/CD。我们按 sprints 工作,互相 review PRs,并将 AI 视为 first-class teammate——同时具备 human judgment 来判断它何时出错。
$146,600—$201,650 USD
$132,000—$181,500 USD
$124,600—$171,400 USD
$117,300—$161,250 USD
About Databricks
Databricks 是数据与 AI 公司。全球超过 10,000 家组织——包括 Comcast、Condé Nast、Grammarly 以及超过 50% 的 Fortune 500 企业——依赖 Databricks Data Intelligence Platform 来统一和 democratize 数据、analytics 和 AI。Databricks 总部位于 San Francisco,在全球设有办公室,由 Lakehouse、Apache Spark™、Delta Lake 和 MLflow 的原创作者创立。欲了解更多信息,请在 Twitter、LinkedIn 和 Facebook 上关注 Databricks。
Benefits
在 Databricks,我们努力提供全面满足所有员工需求的 benefits 和 perks。有关您所在地区提供的 benefits 具体详情,请点击 here。
Our Commitment to Diversity and Inclusion
Compliance
如果履行工作职责需要访问 export-controlled technology 或 source code,Employer 有权决定是否为此类职位申请 U.S. government license,且 Employer 可仅基于此点拒绝继续考虑申请人。
译文仅供辅助阅读,具体要求以原始招聘来源为准。