P-1549

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.

The Mission

Databricks agents are only as good as the context they can retrieve. Whether an agent is answering a question about last quarter's revenue, debugging a failing job, generating SQL against a 10,000-table lakehouse, or summarizing a Wiki page, its quality is bounded by what it can find — and how well it understands what it finds.

We are hiring a Senior Staff Applied AI Engineer to own context retrieval for Databricks agents across SaaS providers. This is a zero-to-one role with two deeply connected charters:

1. Build the retrieval stack — query understanding, content understanding, ranking, retrieval, and evaluation — across the Enterprise SaaS data stored across multiple systems.
2. Build the search subagents that sit on top of that stack and reason about what context is needed, how to retrieve it, and whether the right thing actually came back — closing the loop between an agent's intent and the substrate that serves it.

If you have deep Information Retrieval wisdom, have shipped retrieval systems for RAG and agentic workloads, and want to build the substrate — and the agents on top of it — that make every Databricks agent measurably smarter, this role is for you.

What You Will Do

• Build the full retrieval stack from scratch. Own the end-to-end system: query understanding, content understanding and indexing, hybrid retrieval, ranking, and evaluation. Make the architectural calls that will define how Databricks agents access context for years to come.
• Retrieve across heterogeneous data — structured and unstructured. Index and rank across structured assets (tables, columns, SQL queries, dashboards, code, notebooks, jobs) and unstructured content (docs, wikis, tickets, chat, images, video, audio). Each modality has its own signals — design retrieval that exploits them rather than flattens them.
• Connect to the SaaS surface area customers actually use. Build connectors and retrieval adapters for the systems where enterprise knowledge lives. Treat each retrieval source with its own freshness, permissions, and ranking signals.
• Optimize for two consumers at once. Retrieval must serve both LLMs (grounded, token-efficient, hallucination-resistant context) and humans (intuitive, explainable discovery). These are different objectives and require different signals — own both.
• Crack query understanding for agents. Agent queries don't look like web queries. Build query rewriting, decomposition, intent classification, and entity resolution tuned for multi-turn agentic workflows.
• Crack content understanding at scale. Build the pipelines that extract structure, entities, embeddings, summaries, and metadata from every supported asset type — and keep them fresh as customer data evolves.
• Build search subagents that reason about retrieval. Design the agentic layer that decides what context is needed, which sources to query, how to decompose and route the search, and — critically — whether the retrieved content is actually sufficient to answer the question. These subagents will plan multi-hop searches, issue follow-up queries when results are weak, ground claims against retrieved evidence, and hand back high-confidence context (or signal failure) to upstream agents. This is where IR meets agentic reasoning.
• Build the evaluation flywheel for both retrieval and subagents. Stand up offline evals (nDCG, MRR, Recall@K, Precision@K), LLM-as-judge harnesses, human-in-the-loop labeling, and online experimentation. Extend evaluation beyond ranking metrics to measure subagent decision quality — did it ask the right follow-up?, did it correctly recognize when retrieval failed?, did it ground its answer in the right evidence?. Quality you can't measure is quality you can't ship.
• Set technical direction and grow the team. Set the multi-year roadmap, mentor senior engineers, partner with Research, Product, and Platform leaders, and raise the technical bar across the org.

What We're Looking For

• 10+ years of software engineering experience, with significant time spent building production retrieval, search, or RAG systems at scale.
• Deep Information Retrieval (IR) expertise: lexical retrieval (BM25, Lucene/Elasticsearch/OpenSearch), dense retrieval (embeddings, ANN indexes — FAISS, ScaNN, HNSW), hybrid retrieval, and learning-to-rank.
• Hands-on experience with modern LLM-era retrieval: RAG architectures, query rewriting, re-ranking with cross-encoders, long-context strategies, and grounding techniques that reduce hallucination.
• Experience designing agentic systems on top of retrieval — search planners, multi-hop / iterative retrieval, self-reflection and sufficiency checks, tool-using agents that decide what to fetch and verify what came back.
• Strong grasp of relevance evaluation: nDCG, MRR, Precision@K, Recall@K; offline/online experimentation; LLM-as-judge frameworks; building human labeling pipelines.
• Experience working across structured and unstructured data — you've indexed and ranked over tables, code, and documents in the same system, and have opinions about how to do it well.
• Track record of building 0→1: you've stood up a retrieval system from an empty repo, made the foundational architectural decisions, and grown it into something that customers depend on.
• Demonstrated ability to operate as a technical leader: setting direction across teams, mentoring senior engineers, and influencing roadmap with research, product, and platform partners.

Nice to Have

• Experience building retrieval over enterprise SaaS sources (permissions, freshness, multi-tenancy, ACL-aware indexing).
• Background in agentic systems, tool use, or multi-turn retrieval for LLM agents.
• Contributions to open-source IR/search projects, or publications at SIGIR, KDD, WWW, EMNLP, or similar venues.
• Experience training or fine-tuning embedding models, rerankers, or query understanding models.

Why This Role

• Foundational impact. Retrieval is the single biggest lever on agent quality. The stack you build will sit underneath every Databricks agent and every customer-built agent on our platform.
• Greenfield with scale. You get the rare combination of starting from a clean sheet and having immediate access to massive enterprise scale, real customer data, and a world-class research org.
• The right team. You'll work alongside engineers and researchers behind Lakehouse, Apache Spark™, Delta Lake, MLflow, MosaicML, and DBRX.

Location

This role is based in our Mountain View, CA or San Francisco, CA office. Hybrid in-office collaboration expected.

RDQ427R175

At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

At Databricks, the Compute Infrastructure organization builds and operates the foundation that runs all Data, AI and stateful workloads across all major clouds. Our platform launches tens of millions of VMs per day, operates thousands of Kubernetes clusters, and must deliver extreme elasticity, reliability and cost efficiency.

As a Senior Software Engineer on the Compute Infra team, you will design and build the systems that power Databricks’ compute infrastructure to enable engineers to quickly launch and scale world-class products.

The impact you will have:

• Develop the compute abstractions that provide powerful capabilities for all Databricks workloads, enabling engineers to build world-class products with high velocity and best-in-class performance
• Design the workload orchestration and scheduling systems that orchestrates all types of workloads (serving, batch, stateful, GPU) with high performance and efficiency
• Scale the fleet management systems that launch and configure millions of VMs every day across cloud providers
• Raise the technical and operational bar through strong design practices, testing, and a culture of engineering excellence and platform mindset.
• Lead cross-team initiatives that span product and infrastructure surface areas.

What we look for:

• BS (or higher) in Computer Science or related field
• 5+ years of experience designing and building large-scale distributed systems
• Strong proficiency in one or more languages such as Java, Scala, Go, or C++
• Experience with service-oriented architectures and large scale distributed systems
• Familiarity with cloud platforms (AWS, Azure, GCP) and container/orchestration technologies (Kubernetes, Docker)
• Track record of shipping infrastructure that supports mission-critical workloads at scale

RDQ427R169

While candidates in the listed locations are encouraged for this role, we are open to remote candidates in other locations.

Databricks is looking for a Principal Data Scientist to serve as the statistical voice of the Data Science organization. This person will make Databricks smarter and more data-driven at the highest levels of leadership — translating the full power of data science into clear, actionable narratives for our CEO, C-suite, and Board of Directors.

Our vision is simple: data drives every Databricks decision and action. To get there, we need a world-class statistician and communicator — someone who can bridge the gap between deep analytical rigor and executive decision-making. This is a pure IC role with company-wide influence: no direct reports, maximum leverage.

Databricks was founded in 2013 by the original creators of Apache Spark, Delta Lake, and MLflow. We built the Databricks Data Intelligence Platform to help organizations unify their data, analytics, and AI workloads. With more than 10,000 organizations worldwide — including over half of the Fortune 500 — relying on Databricks, and a team of 7,000+ employees, we are at the forefront of the data and AI revolution. We have been recognized as a leader by Gartner, Forrester, and IDC, and have raised more than $4 billion in funding at a $62 billion valuation.

The Impact You Will Have

• Executive translation. Translate complex data science findings into clear, actionable narratives for the CEO, C-suite, and Board of Directors — ensuring data science insights directly inform the company's most critical decisions.
• Statistical authority. Serve as the company's chief statistical voice and the final quality backstop for analytical rigor in high-stakes executive decisions. Advance the state-of-the-art in how Databricks applies statistical methods to business problems.
• Org-wide uplevel. Raise the communication bar across the entire Data Science organization by setting standards, coaching teams, and co-authoring key executive-facing deliverables. Make every DS team better at telling their story.
• Strategic insights. Produce deep strategic analyses on revenue, platform health, operational efficiency, and competitive positioning — the kind of synthesized, judgment-rich insight that AI cannot autonomously create.
• Cross-functional influence. Partner with engineering VPs, product leaders, and executive staff to embed a data-driven decision-making culture across the company. Be the trusted analytical advisor in rooms where critical decisions are made.
• External thought leadership. Represent Databricks externally as a data science thought leader at industry conferences, in publications, and in the broader statistical community. Build an external identity that attracts world-class talent.
• Methodology and standards. Define and evolve company-wide scientific methodologies — experimentation frameworks, forecasting systems, causal inference approaches — to match and push industry state-of-the-art.

What We Look For

Required

• 15+ years of experience in data science, statistics, or quantitative research spanning industry and/or academia.
• Proven track record of presenting statistical and data science concepts to C-suite and Board-level audiences, with measurable impact on executive decision-making.
• Broad expertise across data science disciplines: experimentation, causal inference, forecasting, optimization, and machine learning.
• Exceptional written and verbal communication — the ability to make complex statistical concepts intuitive and compelling for non-technical executives.
• Track record of upleveling teams: setting analytical standards, mentoring senior data scientists, and improving org-wide output quality.
• Experience at the intersection of statistics and large-scale technology or data platforms.
• Ph.D. in Statistics, Mathematics, Computer Science, or a related quantitative field.

Preferred

• Academic research or teaching background in statistics or a quantitative field.
• Industry experience at multiple tier-1 technology companies.
• Published research or recognized thought leadership in applied statistics.
• Experience building or leading a "Chief Statistician" or equivalent function.
• Experience in infrastructure, platform, or systems-oriented data science.

RDQ427R268

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers and driven by customer obsession, we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

Customers trust Databricks with their most sensitive data and workloads, and Security Infrastructure Operations (SIO) is the team that sustains and improves Databricks' cloud security posture across every cloud service provider we operate in. We are looking for a Senior Engineering Manager to lead this team and drive the strategy for how cloud identity, access, and environment changes are reviewed, executed, and automated at scale. You will own the operational backbone of Databricks' cloud security, spanning IAM policy enforcement, CSP account provisioning, compliance evidence collection, and security data pipelines. Your goal is to ensure that Databricks engineers can move fast without compromising security. This is a high-visibility, cross-functional leadership role that partners with Security, Security Engineering, IT and engineering teams across the company.

The impact you will have:

• Build, lead, and grow a high-performing team of engineers responsible for cloud IAM operations, CSP environment management, security data pipelines, and compliance operations across AWS, Azure, and GCP.
• Define and execute the strategy and roadmap for automating cloud access assignment, approval workflows, and IAM policy enforcement to reduce manual toil while strengthening security controls.
• Own the end-to-end lifecycle of CSP account, subscription, and project provisioning, including secure onboarding of acquired companies' cloud environments into Databricks' organizations with minimal disruption.
• Drive compliance programs including Cloud User Access Reviews, audit evidence collection, and IAM policy alignment to meet SOC2, FedRAMP, and other regulatory requirements.
• Ensure the reliability and timeliness of security data pipelines that ingest CSP audit logging, enabling downstream detection and response capabilities.
• Partner closely with Security, Security Engineering, and IT to interpret and operationalize security policies, ensuring consistent enforcement with high transparency and minimal friction for engineering teams.
• Lead complex, multi-quarter initiatives spanning multiple teams and external partners, demonstrating leverage by executing through technical leads and developing future leaders on the team.
• Lead GovCloud escort operations, including staffing a 24x7 on-call rotation for SEV0 incidents, and continuously improving operational resilience.
  
  

What we look for:

• 8+ years of experience in security engineering, cloud infrastructure, or production/site reliability engineering, with deep hands-on expertise in at least one major cloud provider (AWS, Azure, or GCP).
• 5+ years of engineering management experience, including building teams, developing senior engineers and managers, and navigating complex people situations such as promotions and performance management.
• Strong technical understanding of cloud IAM (policies, principals, roles, federation), CSP organizational structures, and identity governance frameworks.
• Demonstrated success leading operational teams that balance high-throughput request execution with automation and process improvement.
• Experience with compliance and audit workflows (SOC2, FedRAMP, ISO, or similar), including evidence collection and access review programs.
• Track record of driving cross-functional initiatives that require influencing without direct authority across security, infrastructure, and engineering organizations.
• Strong communication and stakeholder management skills, with the ability to translate security policy into practical operational processes that engineering teams can follow.
• BS (or higher) in Computer Science, Information Security, or a related technical field.

P-1605

About Databricks

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

The Role

At Databricks, we don’t just use the cloud; we are "cloud maximalists." Unlike most companies that treat multi-cloud as a backup strategy, we run our platform across every region of every major cloud provider (AWS, Azure, and GCP) simultaneously. This creates a massive, high-consequence engineering surface area that requires a unique breed of Production Engineer.

In this role, you won’t just run our cloud environments; you will own and evolve the secure infrastructure, access patterns, and guardrails that keep Databricks’ global platform safe and compliant in production. You will be responsible for the "sovereign layer" of our infrastructure, ensuring that our Data Intelligence Platform operates with 100% reliability and security in highly regulated, air-gapped, and sovereign environments. If you are an engineer who views infrastructure as a software problem and thrives on the complexity of global-scale networking, IAM, and automation, this is your team.

The Impact You’ll Have

Security-Focused Cloud Operations

• Design, automate, and operate the IAM, account/subscription, and project lifecycle across AWS, Azure, and GCP, enforcing least-privilege and standardized access patterns at scale.
• Review, implement, and continuously improve cloud identity and access policies (IAM, Okta, Opal) to align with Databricks security standards and audit requirements.

Production Engineering & Automation

• Build and maintain reliable, observable automation and tooling to apply cloud changes (roles, policies, accounts, networking) safely and repeatedly.
• Treat operational and security issues as software problems: eliminate toil, drive root-cause analysis, and codify fixes into infrastructure and tooling.

Security Data Pipelines & Compliance

• Own and improve security and audit logging data pipelines from cloud providers into our internal systems, ensuring timely, accurate data for detection, investigations, and audits.
• Partner with Security, Compliance, and Audit teams to provide evidence, clarifications, and policy updates that keep our environments aligned with evolving standards.

Regulated & Specialized Environments

• Operate and improve specialized, highly regulated environments (e.g., FedRAMP / GovCloud) including release management, patching cadences, and supporting secure access workflows (e.g., SAW).
• Ensure high availability and resiliency for critical security and access infrastructure across these environments.

On-Call & Incident Response

• Participate in a 24x7 on-call rotation for high-severity incidents impacting cloud accounts, IAM, or security data pipelines.
• Act as a key partner to product engineering, security engineering, and field teams during incidents to restore service and harden systems for the future.

What We Look For

• Required: Candidates must be eligible for a Top Secret / Sensitive Compartmented Information (TS/SCI) security clearance.
  • Nice to have: Possession of a current polygraph (Counterintelligence or Full Scope) is highly desired and considered a significant plus.
• Education- BS, MS, or PhD in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• Experience: 12+ years of experience, including leading the strategy for cloud IAM, account architecture, or security-critical infrastructure across multiple environments or business units.
• Cloud & Infrastructure Expertise
  • Deep hands-on experience with at least one major cloud provider (AWS, Azure, or GCP) in areas such as IAM, networking, accounts/subscriptions/projects, and audit logging.
  • Strong background in Infrastructure-as-Code and automation (e.g., Terraform, CloudFormation, or similar) and CI/CD for infrastructure changes.
• Security & Compliance Mindset
  • Proven experience working in or with security-sensitive or regulated environments (e.g., SOC2, FedRAMP, ISO 27001, financial services, public sector) and translating requirements into concrete technical controls.
  • Familiarity with access review processes, policy baselines, and audit evidence for cloud environments.
• Operational Excellence
  • Demonstrated success running high-availability, security-critical services, including on-call responsibilities and incident management.
  • Strong debugging and problem-solving skills across distributed systems, with the ability to navigate ambiguous issues spanning multiple teams and platforms.

Bonus

• Experience with Okta, Opal, or similar identity/access tooling.
• Background operating secure admin workstations (SAW) or comparable hardened access patterns.
• Experience migrating cloud accounts or subscriptions during M&A or large-scale reorganizations.

P-1603

About Databricks

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

The Role

At Databricks, we don’t just use the cloud; we are "cloud maximalists." Unlike most companies that treat multi-cloud as a backup strategy, we run our platform across every region of every major cloud provider (AWS, Azure, and GCP) simultaneously. This creates a massive, high-consequence engineering surface area that requires a unique breed of Production Engineer.

In this role, you won’t just run our cloud environments; you will own and evolve the secure infrastructure, access patterns, and guardrails that keep Databricks’ global platform safe and compliant in production. You will be responsible for the "sovereign layer" of our infrastructure, ensuring that our Data Intelligence Platform operates with 100% reliability and security in highly regulated, air-gapped, and sovereign environments. If you are an engineer who views infrastructure as a software problem and thrives on the complexity of global-scale networking, IAM, and automation, this is your team.

The Impact You’ll Have

Security-Focused Cloud Operations

• Design, automate, and operate the IAM, account/subscription, and project lifecycle across AWS, Azure, and GCP, enforcing least-privilege and standardized access patterns at scale.
• Review, implement, and continuously improve cloud identity and access policies (IAM, Okta, Opal) to align with Databricks security standards and audit requirements.

Production Engineering & Automation

• Build and maintain reliable, observable automation and tooling to apply cloud changes (roles, policies, accounts, networking) safely and repeatedly.
• Treat operational and security issues as software problems: eliminate toil, drive root-cause analysis, and codify fixes into infrastructure and tooling.

Security Data Pipelines & Compliance

• Own and improve security and audit logging data pipelines from cloud providers into our internal systems, ensuring timely, accurate data for detection, investigations, and audits.
• Partner with Security, Compliance, and Audit teams to provide evidence, clarifications, and policy updates that keep our environments aligned with evolving standards.

Regulated & Specialized Environments

• Operate and improve specialized, highly regulated environments (e.g., FedRAMP / GovCloud) including release management, patching cadences, and supporting secure access workflows (e.g., SAW).
• Ensure high availability and resiliency for critical security and access infrastructure across these environments.

On-Call & Incident Response

• Participate in a 24x7 on-call rotation for high-severity incidents impacting cloud accounts, IAM, or security data pipelines.
• Act as a key partner to product engineering, security engineering, and field teams during incidents to restore service and harden systems for the future.

What We Look For

• Required: Candidates must be eligible for a Top Secret / Sensitive Compartmented Information (TS/SCI) security clearance.
  • Nice to have: Possession of a current polygraph (Counterintelligence or Full Scope) is highly desired and considered a significant plus.
• Education- BS, MS, or PhD in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• Experience
  • Staff: 8+ years of experience operating and automating large-scale cloud environments, with a track record of driving cross-team infrastructure improvement.
• Cloud & Infrastructure Expertise
  • Deep hands-on experience with at least one major cloud provider (AWS, Azure, or GCP) in areas such as IAM, networking, accounts/subscriptions/projects, and audit logging.
  • Strong background in Infrastructure-as-Code and automation (e.g., Terraform, CloudFormation, or similar) and CI/CD for infrastructure changes.
• Security & Compliance Mindset
  • Proven experience working in or with security-sensitive or regulated environments (e.g., SOC2, FedRAMP, ISO 27001, financial services, public sector) and translating requirements into concrete technical controls.
  • Familiarity with access review processes, policy baselines, and audit evidence for cloud environments.
• Operational Excellence
  • Demonstrated success running high-availability, security-critical services, including on-call responsibilities and incident management.
  • Strong debugging and problem-solving skills across distributed systems, with the ability to navigate ambiguous issues spanning multiple teams and platforms.

Bonus

• Experience with Okta, Opal, or similar identity/access tooling.
• Background operating secure admin workstations (SAW) or comparable hardened access patterns.
• Experience migrating cloud accounts or subscriptions during M&A or large-scale reorganizations.

P-1604

About Databricks

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

The Role

At Databricks, we don’t just build software for the cloud; we are "cloud maximalists." We run our platform across every region of every major cloud provider (AWS, Azure, and GCP) simultaneously, creating a technical surface area that is unique in the industry. As a Software Engineer on our Public Sector team, you will be responsible for the core backend engineering that allows our Data Intelligence Platform for the Public Sector to operate at massive scale within sovereign and air-gapped cloud environments.

We are looking for world-class Software Engineers to join our core Backend Engineering teams. You will design, build, and scale the distributed systems that power one of the largest data and AI infrastructures in the world. You will tackle high-scale infrastructure challenges where "zero-waste" compute efficiency and 100% system resilience are mandatory. From optimizing massive data storage layers to architecting low-latency microservices that must function in disconnected regions, you will own the end-to-end lifecycle of mission-critical code.

The Impact You’ll Have

• Architect Scalable Systems: Design and implement highly available backend services using Scala, Java, Go, C++/C or similar.
• Distributed Systems Engineering: Design and implement highly scalable backend services in Java, Scala, or Go that power our Data Intelligence Platform across sovereign and air-gapped clouds.
• Infrastructure at Scale: Solve complex architectural trade-offs around concurrency, storage, and networking to ensure the platform remains resilient in high-consequence public sector environments.
• Performance Optimization: Drive "zero-waste" compute initiatives, optimizing our engine and services to perform in resource-constrained or specialized regions (e.g., GovCloud).
• Security & Reliability: Partner with Production Engineering to ensure all backend services meet the highest security standards and compliance guardrails while maintaining high availability.

What We Look For

• Required: Candidates must be eligible for a Top Secret / Sensitive Compartmented Information (TS/SCI) security clearance.
  • Nice to have: Possession of a current polygraph (Counterintelligence or Full Scope) is highly desired and considered a significant plus.
• Technical Breadth: BS/MS/PhD in Computer Science or a related field.
• Experience: Staff : 9+ years of professional software development experience.
• Systems Expertise: Deep understanding of Distributed Systems, concurrency, and performance optimization.
• Language Proficiency: Strong production-level experience in at least one of: Java, Scala, Go, C++ or similar.
• Cloud Experience: Experience building and deploying large-scale SaaS or cloud-native applications.

RDQ427R330

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

As an Engineering Manager on the App Framework team, you will be responsible for building the foundational service frameworks and runtime infrastructure that power every microservice at Databricks. The team's goal is to make every service at Databricks fast, reliable, observable, and secure by default, without each team having to solve these problems independently. The team owns the core application platform: multi-language service and RPC frameworks, core libraries, request context propagation, overload protection, and abstractions that extend full platform capabilities to any language. The team’s work is high-leverage - a single improvement we ship benefits thousands of production services and thousands of engineers across the company.

The impact you will have:

• Lead a team of talented engineers building core application platform infrastructure used by every service at Databricks.
• Own and drive the technical roadmap for one or more pillars.
• Drive multi-quarter execution on high-impact platform initiatives.
• Hire great engineers to build an outstanding team.
• Support engineers in their career development by providing clear feedback, as well developing engineering leaders.
• Ensure high technical standards by instituting processes and a culture of engineering excellence.
• Work with engineering and product leadership to build a long-term roadmap and coordinate execution across teams to unblock cross-cutting projects.

What we look for:

• 5+ years of engineering experience building and operating large-scale distributed systems, service frameworks, or platform infrastructure.
• 2+ years of engineering management experience leading strong technical teams.
• Can ensure the team builds high quality and reliable infrastructure. Experience being responsible for testing, quality, and service level agreements of a product. 
• Strong track record of attracting, hiring, and retaining top engineering talent.
• Experience attracting, hiring, and coaching engineers who meet the Databricks hiring standards. Can uplevel existing team by hiring top-notch senior talent, growing leaders and helping struggling members. Can gain the trust of the team and guide their careers.
• Existing experience building and running cloud platforms, or demonstrated ability to quickly learn new concepts in the SaaS space.

COVID-19 Vaccination Requirement

As a federal government contractor, Databricks requires new U.S. employees to be fully vaccinated against COVID-19. Proof of vaccination will be required as a condition of employment. Databricks will make reasonable accommodations based on medical conditions or religious grounds for qualified candidates in accordance with applicable law.

P-1606

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

As one of the first engineers in the NYC Engineering office, you’ll have the opportunity to be part of a small, nimble team that’s innovating to build new products from the ground up. Our goal is to leverage the power of Databricks in data & AI to deliver vertical AI applications for both technical and business users. This will be a true 0-to-1 environment, combining the excitement of a startup with the resources of a tech leader like Databricks.   

The impact you'll have:

• Create novel, never-seen-before interfaces for GenAI agents that manage complex workflows while keeping the human in the loop through inspectability and transparency
• Partner closely with product management, design, and other engineering teams to build intuitive, scalable, and extensible solutions that drive user & business growth
• Lead by example with hands-on full-stack software development to create dynamic, user-centric experiences
• Enable mechanisms that can drive product-led growth, through seamless onboarding and sharing capabilities
• Direct the future of intuitive agentic applications at Databricks, in collaboration with cross-functional teams of innovative software engineers, product managers, and designers
• Establish best practices within the team & Databricks more widely for building valuable, AI products

What we look for:

• 5+ years of experience with HTML, CSS, and JavaScript
• Demonstrated product mindset with the ability to translate ambiguous customer problems into scrappy MVPs and iterate quickly based on data and user feedback.
• You care that AI features feel intuitive, trustworthy, and helpful, not just bolted on to an existing app
• High ownership and bias for action in 0→1 environments: you are comfortable making pragmatic trade-offs, operating with incomplete information, and driving projects from idea through launch and adoption.
• Strong ability to collaborate across product, engineering, and design teams to align technical strategy with company growth objectives.  
• Experience with modern JavaScript frameworks (e.g., React, Angular, or VueJs/Ember)
• 5+ years of experience with server-side web technologies (eg: Node.js, Java, Python, Scala, C#, C++,Go)
• Proven experience building and shipping end-to-end generative AI products, ideally with a significant UI/UX component
• Experience in developing deep product and business knowledge to connect abstract modeling and analysis tasks with business value

P-1606

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

As one of the first engineers in the NYC Engineering office, you’ll have the opportunity to be part of a small, nimble team that’s innovating to build new products from the ground up. Our goal is to leverage the power of Databricks in data & AI to deliver vertical AI applications for both technical and business users. This will be a true 0-to-1 environment, combining the excitement of a startup with the resources of a tech leader like Databricks.   

The impact you'll have:

• Create novel, never-seen-before interfaces for GenAI agents that manage complex workflows while keeping the human in the loop through inspectability and transparency
• Partner closely with product management, design, and other engineering teams to build intuitive, scalable, and extensible solutions that drive user & business growth
• Lead by example with hands-on full-stack software development to create dynamic, user-centric experiences
• Enable mechanisms that can drive product-led growth, through seamless onboarding and sharing capabilities
• Direct the future of intuitive agentic applications at Databricks, in collaboration with cross-functional teams of innovative software engineers, product managers, and designers
• Drive the strategy for building end-to-end AI feature development by designing, building, and maintaining systems that are scalable, reliable, and performant.

What we look for:

• 5+ years of experience with HTML, CSS, and JavaScript
• Demonstrated product mindset with the ability to translate ambiguous customer problems into scrappy MVPs and iterate quickly based on data and user feedback.
• You care that AI features feel intuitive, trustworthy, and helpful, not just bolted on to an existing app
• High ownership and bias for action in 0→1 environments: you are comfortable making pragmatic trade-offs, operating with incomplete information, and driving projects from idea through launch and adoption.
• Strong ability to collaborate across product, engineering, and design teams to align technical strategy with company growth objectives.  
• Experience with modern JavaScript frameworks (e.g., React, Angular, or VueJs/Ember)
• 5+ years of experience with server-side web technologies (eg: Node.js, Java, Python, Scala, C#, C++,Go)
• Proven experience building and shipping end-to-end generative AI products
• Deep familiarity with LLMs and generative AI, including hands-on experience with techniques like retrieval-augmented generation (RAG), prompt design, evaluation, and monitoring AI quality and safety in production.

RDQ427R337

Mission

This person will support Engineering and Product leaders, partnering with them to operationalize their teams' cross-functional strategies. You will serve as a key liaison across various departments—including Sales, Marketing, IT, and other critical functions—to ensure alignment and execution. Additionally, you will drive strategic initiatives and community events that foster collaboration across the Engineering and Product organizations.

The impact you will have:

• Ensure the Engineering leader is prepared for all meetings, with an accurate and forward-looking calendar.
• Effectively prioritize the calendar and schedule meetings in a timely manner.
• Provide timely responses to all stakeholder requests.
• Enhance the efficiency of the Engineering leader's time use, leading to a more productive team and company.
• Execute strategic initiatives well, delivering on defined outcomes.

Responsibilities

• Calendar management - organizes all meetings, including but not limited to team meetings, customer, and internal business partner meetings across international time zones
• Builds and maintains records of all meeting requests and closes out all requests in a timely manner. Keeps to a strong SLA on responding to requests
• Manages offsite meetings, events, and programs in support in support of the SVP and their staff
• Ensures all meeting invites have the appropriate details to have an effective meeting 
• They may be required to support other executive staff members if there's a gap in coverage due to PTO, sickness, maternity leave, or other absences. 

Competencies

• Minimum of 7+ years of applicable executive administrative experience, ideally from a global software organization
• Worked with VPs/SVPs in Engineering and Product in large organizations.
• Worked with VPs managing over 2000+ people in engineering, customer-facing, and/or technical roles
• Ability to work at a fast pace with shifting priorities in a hyper-scaling company
• Experience supporting a high-growth company, and preferably directly supporting an executive staff member 
• High attention to detail, organization, and process abilities 
• Strong calendaring skills (Gmail and Google Calendar experience mandatory)
• Strong teamwork skills, and a confident ability to offer suggestions and improvements to the process and work very collaboratively with others
• Strong relationship management skills, ability to build a personal network throughout the company
• Strong oral and written communication 
• Ability to communicate clearly and effectively with senior leaders and external partners

P-1473

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best Data Intelligence Platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

As one of the first fullstack engineers in the NYC Engineering office, you’ll have the opportunity to be part of a small, nimble team that’s innovating to build new products from the ground up. Our goal is to leverage the power of Databricks in data & AI to deliver vertical AI applications for both technical and business users. This will be a true 0-to-1 environment, combining the excitement of a startup with the resources of a tech leader like Databricks.   

The key challenge you’ll be dealing with is leveraging the latest UX/UI technologies to create simple but powerful interfaces of very complex data and workflows. Your team is taking a UI-first and GenAI-first approach to building products. For example, you may be working in challenges such as:

• Create interfaces for GenAI agents that generate complex workflows while keeping the human in the loop through inspectability and transparency
• Create complex visualizations such as data pipelines, data mappings, customer journey flows, identity graphs, etc
• Enable mechanisms that can drive product-led growth, through seamless onboarding and sharing capabilities
• An interactive environment for collaborative data projects at massive scale with an easy path to production.

What we look for:

• 5+ years of experience with HTML, CSS, and JavaScript.
• Passion for user experience and design and a deep understanding of front-end architecture.
• High velocity focus, able to ship high quality code frequently and with speed 
• Experience building complex workflows and complex analytics visualizations
• Motivated by delivering customer value.
• Experience with modern JavaScript frameworks (e.g., React, Angular, or VueJs/Ember).
• 5+ years of experience with server-side web technologies (eg: Node.js, Java, Python, Scala, C#, C++,Go).
• Good knowledge of SQL.

RDQ126R35

About Databricks
At Databricks, we empower data teams to solve the world’s toughest challenges—from security threat detection to cancer drug development. Our mission is to build the best data and AI infrastructure platform, enabling our customers to focus on innovation.

Our engineering teams push the boundaries of data and AI technology while ensuring our platform operates with the resilience, security, and scale that businesses need to succeed.

About the Role

We are developing a growing ecosystem of applications and partners on the Databricks Data Intelligence Platform. Our team creates frameworks, tools, and best practices to enable seamless integrations, helping developers and partners build impactful solutions.

As a Senior Staff Software Engineer, you will define the vision, architecture, and strategy for this ecosystem. You will play a key role in enabling customers to integrate cutting-edge applications, helping developers thrive on Databricks, and shaping the future of data and AI platforms.

Your Impact

• Define and drive the ecosystem strategy for Databricks, a crucial pillar of our platform growth. Shape how applications and integrations enhance the Databricks experience for developers, partners, and customers.
• Develop frameworks, APIs, and tools that make it seamless for partners and developers to build, integrate, and scale applications within the Databricks ecosystem.
• Enable customers to integrate cutting-edge applications and specialized functionalities, helping them drive competitive differentiation and expand their AI and data capabilities.
• Lead and mentor engineers across teams, providing technical guidance, architectural direction, and career development support. Foster a culture of innovation, best practices, and knowledge sharing.
• Collaborate cross-functionally with product, engineering, and business development teams to align technical roadmaps with strategic business goals.
• Engage with open-source communities and advocate for best practices in application development, data processing, and ecosystem enablement.
• Represent Databricks at industry events and conferences, influencing the broader data and AI landscape while engaging with partners, customers, and developers to shape the future of our platform.

What We’re Looking For

• Deep passion for and knowledge of the broad data and AI industry. Experience contributing to open-source projects and engaging with developer communities is a plus.
• 10+ years of experience building data-intensive applications or systems. Strong expertise in database systems (SQL, NoSQL, OLAP/OLTP) and big data processing (Apache Spark™, Flink). Experience designing high-performance APIs (REST, GraphQL, gRPC) and managing integrations.
• Strong understanding of data security, governance, and compliance frameworks (RBAC, GDPR, HIPAA), as well as cloud infrastructure (AWS, Azure, GCP), Kubernetes, Terraform, and CI/CD pipelines.
• Strong leadership skills with experience driving cross-functional and cross-organizational (e.g. external partners) initiatives.
• Ability to mentor engineers, influence architectural decisions, and advocate for best practices.
• Excellent communication skills to evangelize Databricks' ecosystem vision internally and externally.
• Bias for action and commitment to delivering high-quality solutions.

Join us in shaping the future of the Databricks ecosystem and enabling the next generation of data and AI innovation.

At Databricks, we are building the world’s best data and AI infrastructure platform so our customers can solve the world’s toughest problems. Founded by engineers and deeply customer-obsessed, we take on hard technical challenges across the stack — and we’re only getting started.

The Spark Platform organization builds the core technologies that power Databricks and the Apache Spark ecosystem. Spark Connect is a critical component of Databricks Serverless and a strategic open source investment that shapes the future developer experience of Spark.

We are looking for an Engineering Manager to lead the Spark Connect team. This leader will own the Databricks Spark Connect platform, drive reliability and execution for a critical Serverless component, and lead our open source Spark Connect strategy in Apache Spark. This includes owning the OSS roadmap, partnering across teams, and driving adoption of Spark Connect in the open source ecosystem.

The impact you will have

• Lead the team responsible for Spark Connect, a critical component of Databricks Serverless.
• Own platform reliability, scalability, and operational excellence.
• Drive Databricks’ technical leadership in open source Spark Connect.
• Define and execute the strategy for OSS Spark Connect adoption and ecosystem growth.
• Partner across product, runtime, serverless, and OSS stakeholders to shape roadmap and architecture.
• Hire and grow a strong engineering team with high technical and operational standards.

What we look for

• 10+ years of experience in distributed systems, infrastructure, or data platforms.
• 3+ years of experience managing high-performing engineering teams.
• Strong technical depth and a track record of owning critical production systems.
• Experience leading cross-functional initiatives and influencing technical direction.
• Passion for open source, developer platforms, and large-scale systems.

P-1534

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. 

As an Engineering Manager, you will work with your team to build mission-critical Lakebase services on the Databricks Platform at scale.

Key responsibilities include:

• Drive continuous delivery within a team of experts in storage technology, distributed systems and Rust.
• Manage the development and rollout of storage services that host millions of customer databases across dozens of regions
• Partner with peer engineering teams across Databricks to co-evolve Lakebase services with our global infrastructure.
• Lead operational excellence in 24/7 operation of our system

The impact you will have:

• Hire great engineers to build an outstanding team.
• Support engineers in their career development by providing clear feedback and develop engineering leaders.
• Ensure high technical standards by instituting processes (architecture reviews, testing) and culture (engineering excellence).
• Work with engineering and product leadership to build a long-term roadmap.
• Coordinate execution and collaborate across teams to unblock cross-cutting projects.

What we look for:

• Experience with building and shipping storage systems where correctness and performance are essential
• BS (or higher) in Computer Science, or a related field
• 2+ years of experience building and leading a team of engineers working in a related system
• Experience with build, release and deployment infrastructure technologies such as Spinnaker, Jenkins, Airflow, Docker, Kubernetes, Terraform, Bazel, etc.
• Ability to attract, hire, and coach engineers who meet the Databricks hiring standards - can up level existing team via hiring top-notch senior talent, growing leaders and helping struggling members; can gain trust of the team and guide their careers
• Comfort working on cross-functional projects with the ability to deeply understand product and customer personas

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.

Databricks' AI Runtime (AIR) product provides enterprises with an API for training and fine-tuning deep learning and LLM models with on-demand GPUs. Whether it's a transformer model for drug discovery or a fine-tuned foundation model, customers use this team's training infrastructure to build state-of-the-art frontier models.

As a Senior Engineering Manager, you will lead the team owning both the product experience and the foundational infrastructure of AIR. You'll shape customer-facing capabilities while designing for scalability, extensibility, and performance of GPU training and adjacent areas, collaborating closely across the platform, product, infrastructure, and research organizations.

The impact you will have:

• Lead, mentor, and grow a high-performing engineering team responsible for the Custom Training product and its foundational infrastructure, including distributed training orchestration, cluster lifecycle, fault tolerance, and training efficiency.
• Define and own the product and technical roadmap for AIR, balancing customer experience, functionality, and foundational investments.
• Collaborate closely with product, research, platform, infrastructure teams, and customers to drive end-to-end delivery, from ideation and prioritization to launch and operation.
• Drive architectural decisions and product design for managed GPU training at scale.
• Advocate for customer needs through direct engagement, ensuring engineering decisions translate to clear product impact.
• Build observability and reliability practices for long-running, multi-node training jobs, including checkpoint strategies, failure recovery, and operational runbooks.
• Partner with recruiting to attract, hire, and develop top-tier engineering talent.

What we look for:

• 8+ years of software engineering experience, with 3+ years in engineering management.
• Track record building and operating managed GPU training infrastructure at scale (100s/1000s GPUs).
• Deep familiarity with distributed training frameworks (PyTorch, DeepSpeed, Composer, Megatron-LM) and parallelism strategies (FSDP, tensor/pipeline parallelism).
• Experience with training resilience patterns: checkpointing, elastic training, and automated failure recovery for long-running jobs.
• Understanding of GPU performance fundamentals including NCCL, interconnect topologies, and memory optimization.
• Experience building platform products with clear SLAs where you've owned the customer experience, not just the backend.
• Strong cross-functional leadership across platform, product, and research teams, with the ability to lead through ambiguity and deliver complex projects.
• Excellent collaboration and communication skills across engineering, product, and research organizations.
• BS/MS in Computer Science, Electrical Engineering, or related technical field.

P-1535

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

The Lakebase Platform Reliability team's footprint spans multiple stacks, systems, and stakeholders. They include AI-powered tooling and workflows for customer management, real-time observability during incidents, monitoring and auditing systems that underpin compliance requirements, and customer-facing operational APIs and maintenance workflows. You'll contribute to the wider platform mission: building resource management infrastructure, reliable distributed services, and internal tools that help Databricks engineers operate confidently across clouds and environments.

The impact you will have:

• Hire great engineers to build an outstanding team.
• Support engineers in their career development by providing clear feedback and develop engineering leaders.
• Ensure high technical standards by instituting processes (architecture reviews, testing) and culture (engineering excellence).
• Work with engineering and product leadership to build a long-term roadmap.
• Coordinate execution and collaborate across teams to unblock cross-cutting projects.
• Resource management infrastructure powering the big data and machine learning workloads on the Databricks platform in a scalable, secure, and cloud-agnostic way
• Lead development of reliable, scalable services and client libraries that work with massive amounts of data on the cloud, across geographic regions and Cloud providers
• Build tools to allow Databricks engineers to operate their services across different clouds and environments
• Build services, products and infrastructure at the intersection of machine learning and distributed systems.

What we look for:

• 5+ years of Engineering experience and 2+ years of Engineering Management experience.
• Experience with large-scale distributed services and the processes around testing, monitoring, and SLAs.
• Ability to align multiple stakeholders on competing priorities. 
• Able to balance short-term delivery against long-term stability.
• BS (or higher) in Computer Science, or a related field.

RDQ326R233

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.

Databricks SQL (DBSQL) is a serverless data warehouse on the Databricks Lakehouse Platform that lets you run all your SQL and BI applications at scale. The Databricks SQL Control Plane team builds scalable solutions for managing the multi-tenanted DB SQL service. This team creates and maintains services that allow customers to create a data warehouse, scale it within seconds, and run mission critical workloads at scale. The team is seeking an Engineering Manager to spearhead the development of a new service and architecture for the next generation of our product.

The key responsibilities include:

• Leading a team of talented software engineers to build the next-generation low-latency, multi-tenanted, cloud native data warehousing system 
• Growing the team by hiring strong engineering talent
• Leading and participating in technical, product and design discussions relating to cloud native database systems
• Managing and operating a highly available service in the cloud
• Growing leaders on the team by providing coaching, mentorship and growth opportunities
• Playing a key role in defining the product and engineering roadmap for the team 
• Partnering with other engineering and product leaders on planning, prioritization and staffing.
• Creating a culture of excellence on the team while leading with empathy

What we look for:

• 5+ years experience working in, database systems, data processing or related domains
• Experience building highly available cloud services on AWS, GCP or Azure
• Building, growing and managing high performance teams
• Experience defining and meeting SLOs for highly available systems
• Ability to attract and hire engineers who meet the Databricks hiring standards. 
• Comfort working cross functionality with product management and partners to build products that drive user growth

Preferred

• Experience working Rust

RDQ127R255

At Databricks, we are passionate about enabling data teams to solve the world’s toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world’s best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

The impact you will have 

As the Sr. Manager of Engineering in our newly opened NYC engineering hub, you will be leading teams building multiple products that enable our customers to use innovative ML/AI techniques to add value to their business. You will work closely with product and research on cutting-edge technologies and be responsible for launching and growing new products, playing a key role in defining the future of how AI and data applications are built.

The Databricks AI Gateway is an enterprise control plane for governing, routing, and monitoring LLM endpoints, coding agents, and model serving endpoints on Databricks. AI Gateway lets you standardize, secure, and observe all LLM inference traffic on Databricks, while capturing detailed production data to manage cost, performance, and quality over time.

What we look for

• 8+ years of industry experience building and supporting large-scale data or production applications
• Experience building classic ML or GenAI systems.
• A passion for building and scaling early-stage products
• Ability to adapt in a fast paced environment. 
• Motivated by delivering customer value and impact.
• Experience driving company initiatives towards customer satisfaction.
• BS/MS/PhD in Computer Science or related majors, or equivalent experience.

At Databricks, we are passionate about enabling data teams to solve the world’s toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We build and run the world’s leading data and AI infrastructure platform so customers can transform deep data insights into business outcomes.

Founded by engineers and grounded in customer obsession, we embrace every opportunity to tackle complex technical challenges — from creating next-generation UI/UX for interacting with data to scaling our services across millions of virtual machines. And we're only getting started.

As the Senior Engineering Manager for Customer Experience Intelligence (CXI), you’ll shape how Databricks delivers intelligent, AI-driven customer and Support experiences at scale. This is a high-impact, visible role where you’ll lead a team building the systems that make every customer interaction more seamless, predictive, and trusted. You’ll turn customer and Support signals into real business outcomes — unlocking measurable improvements in deflection, resolution speed, and customer satisfaction — while helping product teams strengthen reliability through actionable insights. Your leadership will ensure AI, automation, and human expertise come together as a single, intelligent ecosystem powering the Databricks customer journey.

This is your opportunity to define how Databricks blends human ingenuity and AI to deliver world-class customer experiences. If you’re passionate about leading teams that turn data and intelligence into action—and impact felt across thousands of customers—this is where your work will truly matter.

The Impact You Will Have:

• Own the entire portfolio across customer self-service, support workflows, and product-health intelligence.
• Own the execution of the team charter by delivering a sequenced, outcome-driven roadmap with explicit tradeoffs between metric movers (deflection, contact rate, MTTM), visible wins, and foundational capabilities.
• Own rollout strategy through staged releases, enablement, and change management.
• Collaborate with Tech Leads to ensure explainability, observability, and safe fallback mechanisms before scaling dependencies.
• Serve as the primary integrator across Support, Product, Enterprise Engineering, Platform, and SME teams.
• Drive governance to eliminate duplication, resolve conflicting sources of truth, and maintain a unified execution thread tied to measurable outcomes.

What we look for:

• BS or higher degree in Computer Science or a related field.
• 10+ years of experience building and operating customer-facing workflows and support automation tools that reduce customer effort and improve resolution time.
• 5+ years of experience leading Engineering teams that build products used daily by Support engineers, SREs, or developers.
• Demonstrated experience delivering AI- or automation-enabled systems
• Experienced influencing across multiple engineering and product organizations.
• Excellent written and verbal skills with the ability to articulate complex strategies clearly and concisely.

RDQ127R176

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

Our engineering teams build highly technical products that fulfill real, important needs in the world. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.

Unity Catalog is our platform native unified and open governance for data and AI. It eliminate silos, simplify governance and accelerate insights at scale. We are looking for a Senior Staff Software Engineer to come tech lead Unity Catalog Runtime Enforcement. We build and harden the runtime enforcement layer for Unity Catalog, ensuring secure, consistent authorization and data access across Databricks compute, engines, and clouds. This reduces incidents and simplifies customer choices by unifying enforcement semantics. 

The impact you will have:

• Lead and grow and engineering team delivering runtime enforcement outcomes in a high-severity, cross-org domain; establish scope, SLAs, and phased roadmaps.
• Establish single-source-of-truth scope, operating model, and durable mechanisms for enforcement.
• Lead multi-year, multi-team initiatives that shape how Databricks enforces Unity Catalog at runtime across compute types and engines.
• Introduce tools to allow greater automation and operability of services.
• Use your deep experience to help prevent and investigate production issues.
• Plan and lead complicated technical projects that work with several teams within the company.
• Contribute as a technical team lead by mentoring others, lead sprint planning, delegating work and assignments to team members and participate in project planning.

What we look for:

• 15+ years industry experience building and supporting large-scale distributed systems.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Extensive experience building and maintaining distributed systems.
• Security first mindset.
• Cross-org leadership in ambiguous, incident-heavy environments; disciplined rollout and ops maturity.
• Motivated by delivering customer value and impact.
• Experience driving company initiatives towards customer satisfaction.
• BS/MS/PhD in Computer Science or related majors, or equivalent experience.
•  

RDQ127R176

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

Our engineering teams build highly technical products that fulfill real, important needs in the world. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.

Unity Catalog is our platform native unified and open governance for data and AI. It eliminate silos, simplify governance and accelerate insights at scale. We are looking for a Senior Staff Software Engineer to come tech lead Unity Catalog Runtime Enforcement. We build and harden the runtime enforcement layer for Unity Catalog, ensuring secure, consistent authorization and data access across Databricks compute, engines, and clouds. This reduces incidents and simplifies customer choices by unifying enforcement semantics. 

The impact you will have:

• Lead and grow and engineering team delivering runtime enforcement outcomes in a high-severity, cross-org domain; establish scope, SLAs, and phased roadmaps.
• Establish single-source-of-truth scope, operating model, and durable mechanisms for enforcement.
• Lead multi-year, multi-team initiatives that shape how Databricks enforces Unity Catalog at runtime across compute types and engines.
• Introduce tools to allow greater automation and operability of services.
• Use your deep experience to help prevent and investigate production issues.
• Plan and lead complicated technical projects that work with several teams within the company.
• Contribute as a technical team lead by mentoring others, lead sprint planning, delegating work and assignments to team members and participate in project planning.

What we look for:

• 15+ years industry experience building and supporting large-scale distributed systems.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Extensive experience building and maintaining distributed systems.
• Security first mindset.
• Cross-org leadership in ambiguous, incident-heavy environments; disciplined rollout and ops maturity.
• Motivated by delivering customer value and impact.
• Experience driving company initiatives towards customer satisfaction.
• BS/MS/PhD in Computer Science or related majors, or equivalent experience.
•  

RDQ127R176

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

Our engineering teams build highly technical products that fulfill real, important needs in the world. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.

Unity Catalog is our platform native unified and open governance for data and AI. It eliminate silos, simplify governance and accelerate insights at scale. We are looking for a Senior Staff Software Engineer to come tech lead Unity Catalog Runtime Enforcement. We build and harden the runtime enforcement layer for Unity Catalog, ensuring secure, consistent authorization and data access across Databricks compute, engines, and clouds. This reduces incidents and simplifies customer choices by unifying enforcement semantics. 

The impact you will have:

• Lead and grow and engineering team delivering runtime enforcement outcomes in a high-severity, cross-org domain; establish scope, SLAs, and phased roadmaps.
• Establish single-source-of-truth scope, operating model, and durable mechanisms for enforcement.
• Lead multi-year, multi-team initiatives that shape how Databricks enforces Unity Catalog at runtime across compute types and engines.
• Introduce tools to allow greater automation and operability of services.
• Use your deep experience to help prevent and investigate production issues.
• Plan and lead complicated technical projects that work with several teams within the company.
• Contribute as a technical team lead by mentoring others, lead sprint planning, delegating work and assignments to team members and participate in project planning.

What we look for:

• 15+ years industry experience building and supporting large-scale distributed systems.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Extensive experience building and maintaining distributed systems.
• Security first mindset.
• Cross-org leadership in ambiguous, incident-heavy environments; disciplined rollout and ops maturity.
• Motivated by delivering customer value and impact.
• Experience driving company initiatives towards customer satisfaction.
• BS/MS/PhD in Computer Science or related majors, or equivalent experience.
•  

RDQ127R176

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

Our engineering teams build highly technical products that fulfill real, important needs in the world. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.

Unity Catalog is our platform native unified and open governance for data and AI. It eliminate silos, simplify governance and accelerate insights at scale. We are looking for a Senior Staff Software Engineer to come tech lead Unity Catalog Runtime Enforcement. We build and harden the runtime enforcement layer for Unity Catalog, ensuring secure, consistent authorization and data access across Databricks compute, engines, and clouds. This reduces incidents and simplifies customer choices by unifying enforcement semantics. 

The impact you will have:

• Lead and grow and engineering team delivering runtime enforcement outcomes in a high-severity, cross-org domain; establish scope, SLAs, and phased roadmaps.
• Establish single-source-of-truth scope, operating model, and durable mechanisms for enforcement.
• Lead multi-year, multi-team initiatives that shape how Databricks enforces Unity Catalog at runtime across compute types and engines.
• Introduce tools to allow greater automation and operability of services.
• Use your deep experience to help prevent and investigate production issues.
• Plan and lead complicated technical projects that work with several teams within the company.
• Contribute as a technical team lead by mentoring others, lead sprint planning, delegating work and assignments to team members and participate in project planning.

What we look for:

• 15+ years industry experience building and supporting large-scale distributed systems.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Extensive experience building and maintaining distributed systems.
• Security first mindset.
• Cross-org leadership in ambiguous, incident-heavy environments; disciplined rollout and ops maturity.
• Motivated by delivering customer value and impact.
• Experience driving company initiatives towards customer satisfaction.
• BS/MS/PhD in Computer Science or related majors, or equivalent experience.
•  

RDQ127R176

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

Our engineering teams build highly technical products that fulfill real, important needs in the world. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.

Unity Catalog is our platform native unified and open governance for data and AI. It eliminate silos, simplify governance and accelerate insights at scale. We are looking for a Senior Staff Software Engineer to come tech lead Unity Catalog Runtime Enforcement. We build and harden the runtime enforcement layer for Unity Catalog, ensuring secure, consistent authorization and data access across Databricks compute, engines, and clouds. This reduces incidents and simplifies customer choices by unifying enforcement semantics. 

The impact you will have:

• Lead and grow and engineering team delivering runtime enforcement outcomes in a high-severity, cross-org domain; establish scope, SLAs, and phased roadmaps.
• Establish single-source-of-truth scope, operating model, and durable mechanisms for enforcement.
• Lead multi-year, multi-team initiatives that shape how Databricks enforces Unity Catalog at runtime across compute types and engines.
• Introduce tools to allow greater automation and operability of services.
• Use your deep experience to help prevent and investigate production issues.
• Plan and lead complicated technical projects that work with several teams within the company.
• Contribute as a technical team lead by mentoring others, lead sprint planning, delegating work and assignments to team members and participate in project planning.

What we look for:

• 15+ years industry experience building and supporting large-scale distributed systems.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Extensive experience building and maintaining distributed systems.
• Security first mindset.
• Cross-org leadership in ambiguous, incident-heavy environments; disciplined rollout and ops maturity.
• Motivated by delivering customer value and impact.
• Experience driving company initiatives towards customer satisfaction.
• BS/MS/PhD in Computer Science or related majors, or equivalent experience.
•  

P-1514

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

Founded by engineers, Databricks has started a multi-year journey to build the best Lakehouse Platform. For this we are building on top of a great foundation but our goal is to go further to build dramatically better products. We want to revisit every component to provide our customers with the fastest, easiest to use and most secure data platform for all their data workloads.

As a software engineer, you will join as a founding member of not only the London site, but really as a founding team for our multi-year journey to achieve our Lakehouse vision. You will be involved in the entire development cycle and exemplify all core Databricks values.

The impact you will have:

Our backend teams span many domains across our essential service platforms. For instance, you might work on challenges such as:

• Problems that span from product to infrastructure including: distributed systems, at-scale service architecture and monitoring, workflow orchestration, and developer experience.
• Build reliable, secure and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, GCS, Azure Blob Store.
• Develop product features that empower our customers to easily store and access their data.
• Solve reliability problems related to Lakebase.
• Actively find causes of downtime and systematically improve or remove root causes.
• Help the org define SLIs, meet SLOs, and drive long-term reliability improvements.

What we look for:

• BS degree (or higher) in Computer Science, or a related field.
• 8+ years of production level experience in one of: Java, Scala, C++, or similar language.
• Experience developing large-scale distributed systems.
• Experience working on a SaaS platform or with Service-Oriented Architectures.
• Knowledge of SQL.

P-1428

At Databricks, we are passionate about enabling data and AI teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

As part of the AI Platform team, you’ll build the substrate that powers everything from data apps, AI agents, model training, model serving, and Vector Search.  You’ll be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure — with deep ties to research, product, and real-world enterprise use cases.  Databricks Mosaic AI is one of our fastest-growing businesses, helping thousands of our customers democratize AI within their organizations. We’re building the infrastructure that powers the next generation of AI. 

We’re hiring across multiple teams in our AI Engineering org, including:  

The impact you will have:

• Build LLM infrastructure powering trillions of tokens per week for customers through partner models (OpenAI, Anthropic, Gemini) and self hosted models (Qwen, GPT-OSS, Llama)
• Improve reliability, latency, and efficiency of distributed AI workloads
• Collaborate with platform, infra, and ML teams to deliver seamless end-to-end experiences
• Shape how developers and data scientists build and interact with AI on Databricks

What we look for:

• 8+ years of experience in backend or infrastructure engineering
• Strong programming skills in Scala, Go, or Python
• Experience with distributed systems, scalable APIs, or cloud-native infrastructure
• Familiarity with service-oriented architecture, deployment pipelines, and system observability
• Strong product and ownership mindset — you care about building the right solution, not just any solution

Bonus points for:

• Experience with real-time serving, ML infrastructure, or GPU orchestration
• Exposure to platforms like SageMaker, Vertex AI, or Azure ML
• Contributions to OSS projects like MLflow, PyTorch, Ray, vLLM, SGLang
• Built developer platforms or internal tools supporting AI workflows

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. 

Foundation Model Serving is the API Product for hosting and serving frontier AI model inference for open source models like Llama, Qwen, and GPT OSS as well as proprietary models like Claude and OpenAI GPT. For this role, no prior ML or AI experience is necessary. We’re looking for engineers who have owned high scale operational sensitive systems like customer facing APIs, Edge Gateways, ML Inference, or similar services and have an interest in getting deep building LLM APIs and runtimes at scale.

As a Staff Engineer, you’ll play a critical role in shaping both the product experience and core infrastructure. You will design and build systems that enable high-throughput, low-latency inference on GPU workloads with frontier models, influence architectural direction, and collaborate closely across platform, product, infrastructure, and research teams to deliver a world-class foundation model API product.

The impact you will have:

• Design and implement core systems and APIs that power Databricks Foundation Model Serving, ensuring scalability, reliability, and operational excellence.
• Partner with product and engineering leadership to define the technical roadmap and long-term architecture for serving workloads.
• Drive architectural decisions and trade-offs to optimize performance, throughput, autoscaling, and operational efficiency for GPU serving workloads.
• Contribute directly to key components across the serving infrastructure — from working in systems like vLLM and SGLang to creating token based rate limiters and optimizers — ensuring smooth and efficient operations at scale.
• Collaborate cross-functionally with product, platform, and research teams to translate customer needs into reliable and performant systems.
• Establish best practices for code quality, testing, and operational readiness, and mentor other engineers through design reviews and technical guidance.
• Represent the team in cross-organizational technical discussions and influence Databricks’ broader AI platform strategy.

What we look for:

• 10+ years of experience building and operating large-scale distributed systems.
• Experience leading high-scale operationally sensitive backend systems.
• A track record of up-leveling teams engineering excellence.
• Strong foundation in algorithms, data structures, and system design as applied to large-scale, low-latency serving systems.
• Proven ability to deliver technically complex, high-impact initiatives that create measurable customer or business value.
• Strong communication skills and ability to collaborate across teams in fast-moving environments.
• Strategic and product-oriented mindset with the ability to align technical execution with long-term vision.
• Passion for mentoring, growing engineers, and fostering technical excellence.

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. 

Databricks’ Model Serving product provides enterprises with a unified, scalable, and governed platform to deploy and manage AI/ML models — from traditional ML to fine-tuned and proprietary large language models. It offers real-time, low-latency inference, governance, monitoring, and lineage. As AI adoption accelerates, Model Serving is a core pillar of the Databricks platform, enabling customers to operationalize models at scale with strong SLAs and cost efficiency.

As a Staff Engineer, you’ll play a critical role in shaping both the product experience and the foundational infrastructure of Model Serving. You will design and build systems that enable high-throughput, low-latency inference across CPU and GPU workloads, influence architectural direction, and collaborate closely across platform, product, infrastructure, and research teams to deliver a world-class serving platform.

The impact you will have:

• Design and implement core systems and APIs that power Databricks Model Serving, ensuring scalability, reliability, and operational excellence.
• Partner with product and engineering leadership to define the technical roadmap and long-term architecture for serving workloads.
• Drive architectural decisions and trade-offs to optimize performance, throughput, autoscaling, and operational efficiency for CPU and GPU serving workloads.
• Contribute directly to key components across the serving infrastructure — from model container builds and deployment workflows to runtime systems like routing, caching, observability, and intelligent autoscaling — ensuring smooth and efficient operations at scale.
• Collaborate cross-functionally with product, platform, and research teams to translate customer needs into reliable and performant systems.
• Lead technical initiatives that improve latency, availability, and cost-effectiveness across both customer-facing and foundational serving layers.
• Establish best practices for code quality, testing, and operational readiness, and mentor other engineers through design reviews and technical guidance.
• Represent the team in cross-organizational technical discussions and influence Databricks’ broader AI platform strategy.

What we look for:

• 10+ years of experience building and operating large-scale distributed systems.
• Deep expertise in model serving, inference systems, and related infrastructure (e.g., routing, scheduling, autoscaling, and observability).
• Strong foundation in algorithms, data structures, and system design as applied to large-scale, low-latency serving systems.
• Proven ability to deliver technically complex, high-impact initiatives that create measurable customer or business value.
• Experience leading architecture for large-scale, performance-sensitive CPU/GPU inference systems.
• Strong communication skills and ability to collaborate across teams in fast-moving environments.
• Strategic and product-oriented mindset with the ability to align technical execution with long-term vision.
• Passion for mentoring, growing engineers, and fostering technical excellence.

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. 

Databricks’ Model Serving product provides enterprises with a unified, scalable, and governed platform to deploy and manage AI/ML models — from traditional ML to fine-tuned and proprietary large language models. It offers real-time, low-latency inference, governance, monitoring, and lineage. As AI adoption accelerates, Model Serving is a core pillar of the Databricks platform, enabling customers to operationalize models at scale with strong SLAs and cost efficiency.

As a Senior Engineer, you’ll play a critical role in shaping both the product experience and the foundational infrastructure of Model Serving. You will design and build systems that enable high-throughput, low-latency inference across CPU and GPU workloads, influence architectural direction, and collaborate closely across platform, product, infrastructure, and research teams to deliver a world-class serving platform.

The impact you will have:

• Design and implement core systems and APIs that power Databricks Model Serving, ensuring scalability, reliability, and operational excellence.
• Drive architectural decisions and trade-offs to optimize performance, throughput, autoscaling, and operational efficiency for CPU and GPU serving workloads.
• Contribute directly to key components across the serving infrastructure — from model container builds and deployment workflows to runtime systems like routing, caching, observability, and intelligent autoscaling — ensuring smooth and efficient operations at scale.
• Collaborate cross-functionally with product, platform, and research teams to translate customer needs into reliable and performant systems.
• Lead technical initiatives that improve latency, availability, and cost-effectiveness across both customer-facing and foundational serving layers.
• Establish best practices for code quality, testing, and operational readiness, and mentor other engineers through design reviews and technical guidance.

What we look for:

• 5+ years of experience building and operating large-scale distributed systems.
• Experience in model serving, inference systems, or related infrastructure (e.g., routing, scheduling, autoscaling, and observability).
• Strong foundation in algorithms, data structures, and system design as applied to large-scale, low-latency serving systems.
• Proven ability to deliver technically complex, high-impact initiatives that create measurable customer or business value.
• Experience building architecture for large-scale, performance-sensitive CPU/GPU inference systems.
• Strong communication skills and ability to collaborate across teams in fast-moving environments.
• Customer-focused mindset with the ability to align implementation details with product goals.
• Passion for mentoring, growing engineers, and fostering technical excellence.

P-1428

At Databricks, we are passionate about enabling data and AI teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

As part of the AI Platform team, you’ll build the substrate that powers everything from data apps, AI agents, model training, model serving, and vector search.  You’ll be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure — with deep ties to research, product, and real-world enterprise use cases.  Databricks Mosaic AI is one of our fastest-growing businesses helping thousands of our customers democratize AI within their organizations. We’re building the infrastructure that powers the next generation of AI. 

We’re hiring across multiple teams in our AI Engineering org including:  

The impact you will have:

• Build infrastructure that powers our flagship offerings like  MLflow, AI Gateway, Databricks Apps, Agent Framework, Agent Bricks, and Foundation Model APIs, to state a few.
• Improve reliability, latency, and efficiency of distributed AI workloads
• Collaborate with platform, infra, and ML teams to deliver seamless end-to-end experiences
• Shape how developers and data scientists build and interact with AI on Databricks

What we look for:

• 5+ years of experience in backend or infrastructure engineering
• Strong programming skills in Scala, Go, or Python
• Experience with distributed systems, scalable APIs, or cloud-native infrastructure
• Familiarity with service-oriented architecture, deployment pipelines, and system observability
• Strong product and ownership mindset — you care about building the right solution, not just any solution

Bonus points for:

• Experience with real-time serving, ML infrastructure, or GPU orchestration
• Exposure to platforms like SageMaker, Vertex AI, or Azure ML
• Contributions to OSS projects like MLflow, PyTorch, or Ray
• Built developer platforms or internal tools supporting AI workflows

RDQ426R299

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

The Logging Platform team plays a critical role in building scalable and efficient logging solutions that power observability across all Databricks services. As a Staff Software Engineer, you will drive the next generation of our logging infrastructure, enabling engineers across the company to gain deep insights into system behavior, troubleshoot issues efficiently, and optimize performance at scale.

The impact you'll have:

• Build the future of logging at Databricks by designing and scaling our next-generation logging platform that processes petabytes of logs daily.
• Develop and optimize log delivery pipelines to support low-latency, high-throughput log ingestion and querying, ensuring seamless observability across all Databricks services.
• Enhance log accessibility and usability, developing tools that enable engineers to efficiently search, analyze, and derive insights from logs.
• Collaborate with teams across Databricks to define best practices for structured logging, standardizing formats and improving the developer experience.
• Improve reliability and cost-efficiency by optimizing log retention, indexing, and query performance to reduce operational overhead.
• Mentor and uplevel engineers, fostering a culture of technical excellence within the team and broader observability community.

What we look for:

• BS (or higher) in Computer Science, or a related field.
• 7+ years of production-level experience in one of: Scala, Rust, Go, Python, Java, C++, or similar languages.
• Deep experience in software development, in large-scale distributed systems.
• Experience driving complex projects involving multiple teams and stakeholders.
• Familiarity with log collection, health monitoring, and observability tools.

RDQ426R299

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.

Our engineering teams build technical products that fulfill real, important needs in the world. We always push the boundaries of data and AI technology, while simultaneously operating with the security and scale that is important to making customers successful on our platform.

We develop and operate one of the largest-scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.

As a software engineer in the Observability team, you will develop observability solutions that provide insights into the health and performance of our products and infrastructure.

The impact you'll have:

• You will build the next generation of observability platforms that support billions of active time series and process petabytes of logs daily.
• You will manage infrastructure across nearly a hundred cloud regions, enabling all Databricks engineers and customers to monitor the reliability of our product.
• You will develop advanced workflows that accelerate incident diagnosis for Bricksters, allowing engineers to quickly derive insights from logs and metrics. You will leverage powerful capabilities of Databricks’ own data intelligence platform to push the boundaries of troubleshooting practices in the industry.
• You will uplevel monitoring and reliability practices across Databricks engineering, developing opinionated tools that set common standards for managing structured logs, metrics, alerts, dashboards, and oncall rotations.
• Mentor and uplevel engineers, fostering a culture of technical excellence within the team and broader observability community.

What we look for:

• • BS (or higher) in Computer Science, or a related field.
  • 15+ years of production-level experience in one of: Go, Python, Java, Scala, Rust, C++, or similar languages.
  • Experience in software development, in large-scale distributed systems.
  • Experience driving large projects involving multiple teams
  • Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes.
  • Familiarity with observability infrastructure, monitoring patterns, and reliability practices.

RDQ426R299

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.

Our engineering teams build technical products that fulfill real, important needs in the world. We always push the boundaries of data and AI technology, while simultaneously operating with the security and scale that is important to making customers successful on our platform.

We develop and operate one of the largest-scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.

As a software engineer in the Observability team, you will develop observability solutions that provide insights into the health and performance of our products and infrastructure.

The impact you'll have:

• You will build the next generation of observability platforms that support billions of active time series and process petabytes of logs daily.
• You will manage infrastructure across nearly a hundred cloud regions, enabling all Databricks engineers and customers to monitor the reliability of our product.
• You will develop advanced workflows that accelerate incident diagnosis for Bricksters, allowing engineers to quickly derive insights from logs and metrics. You will leverage powerful capabilities of Databricks’ own data intelligence platform to push the boundaries of troubleshooting practices in the industry.
• You will uplevel monitoring and reliability practices across Databricks engineering, developing opinionated tools that set common standards for managing structured logs, metrics, alerts, dashboards, and oncall rotations.
• Mentor and uplevel engineers, fostering a culture of technical excellence within the team and broader observability community.

What we look for:

• • BS (or higher) in Computer Science, or a related field.
  • 7+ years of production-level experience in one of: Go, Python, Java, Scala, Rust, C++, or similar languages.
  • Experience in software development, in large-scale distributed systems.
  • Experience driving large projects involving multiple teams
  • Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes.
  • Familiarity with observability infrastructure, monitoring patterns, and reliability practices.

RDQ127R9

At Databricks, we are obsessed with Data + AI to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions.

Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, CA to a global organization with over 6500 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest-growing SaaS companies in the world.

The Money team's mission at Databricks is to maximize the value that our customers derive from their investments in data projects. We accomplish this through innovative commercialization strategies and cutting-edge engineering. Our team ensures timely, accurate, and customizable billing and usage data, alongside budgeting, forecasting, and cost optimization tools. We provide a seamless and consistent billing experience for all our customers, whether they are large enterprises or individual developers, across different pricing plans and cloud providers (AWS, GCP & Azure).

As a Sr. Staff Software Engineer on the Money team, you will be closely involved in the entire billing process, including usage ingestion, metering, pricing, credits, promotions, payments, usage reporting, and cost center and budgeting. Your role is crucial in democratizing data by bringing Databricks products to market.  By collaborating with marketing, product teams, commercialization experts, data scientists, IT, and customer support, you will standardize billing experiences across major cloud providers, offering our customers a unified "sky computation" experience. This role involves utilizing the latest Databricks products and tools within the ecosystem.

The impact you will have:

• Design and manage the Money systems and services, commercializing all Databricks products and offerings.
• Develop innovative primitives that enable  and support various pricing strategies such as Pay-As-You-Go, commissions, credits, trials, and promotions.
• Enhance engineering and infrastructure efficiency, reliability, accuracy, and response times, including CI/CD processes, test frameworks, data quality assurance, end-to-end reconciliation, and anomaly detection.
• Collaborate with commercialization experts to develop and implement innovative pricing strategies and plans.
• Use AI and LLMs to innovate in cost insight, prediction, and optimization across various cloud providers.
• You will become an expert at using the Databricks Data + AI tools
• Provide leadership in long-term vision and requirements development for Databricks products, in partnership with our engineering teams.
• Represent Databricks at academic and industrial conferences & events.

What we look for:

• BS or higher degree in Computer Science or a related field.
• 9+ years of experience building large projects similar to those described, including near real-time large data processing and distributed service infrastructure management.
• Proven track record of building, shipping, and managing reliable, distributed services and data pipelines at scale.
• Demonstrated leadership skills and the ability to lead across functional and organizational boundaries.
• A proactive approach and a passion for delivering high-quality solutions

RDQ127R51 

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. 

Databricks’ Model Serving product provides enterprises with a unified, scalable, and governed platform to deploy and manage AI/ML models — from traditional ML to fine-tuned and proprietary large language models. It offers real-time, low-latency inference, governance, monitoring, and lineage. As AI adoption accelerates, Model Serving is a core pillar of the Databricks platform, enabling customers to operationalize models at scale with strong SLAs and cost efficiency.

As a Senior Engineering Manager, you will lead the team owning both the product experience and the foundational infrastructure of Model Serving — shaping customer-facing capabilities while designing for scalability, extensibility, and performance across both CPU and GPU inference — and collaborate closely across the platform, product, infrastructure, and research organizations.

The impact you will have:

• Lead, mentor, and grow a high-performing engineering team responsible for both the customer-facing Model Serving product and its foundational infrastructure — covering runtime, APIs, scaling, reliability, and integrations.
• Define and own the product and technical roadmap for Model Serving, balancing customer experience, functionality, and foundational investments across deployment, inference, monitoring, and scaling.
• Collaborate closely with product, research, platform, and infrastructure teams to drive end-to-end delivery — from ideation and prioritization to launch and operation.
• Ensure Model Serving meets stringent SLAs, SLOs, and performance and reliability goals, continuously improving operational efficiency and customer experience.
• Drive architectural decisions and product design around latency, throughput, autoscaling, GPU/CPU placement, and cost optimization.
• Advocate for customer needs through direct engagement, ensuring engineering decisions translate to clear product impact.
• Promote best practices in code quality, testing, observability, and operational readiness.
• Foster a culture of excellence, inclusion, and continuous improvement across the team.
• Partner with recruiting to attract, hire, and develop top-tier engineering talent.

What we look for:

• 5+ years of experience in technical leadership or management.
• Proven track record building and operating large-scale distributed systems, preferably real-time or low-latency APIs.
• Deep understanding of real-time serving systems.
• Experience driving architectural design and operational excellence for production systems with measurable SLAs and SLOs.
• Familiarity with CPU/GPU performance optimization, concurrency, caching, and scalability concepts.
• Excellent collaboration and communication skills across engineering, product, and research organizations.
• Ability to lead teams through ambiguity and deliver complex, cross-functional projects.
• BS in Computer Science (Masters or PhD Preferred).

(P-1286)

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. 

Networking Infrastructure is a core part of the platform that powers all our data and AI products. The platform also powers key enterprise security features used by customers across all our products to build connectivity solutions to cloud resources and prevent data exfiltration. 

We are seeking experienced Senior Software Engineers with large-scale distributed system experience to join the Networking Infrastructure team. You will design and automate the networking foundations for large-scale compute clusters across all the major cloud providers, connecting millions of VMs running on Databricks. You will lead the design and development of secure and scalable connectivity that powers all the data / AI workloads. You will work closely with cross-functional teams, including product management, operations, and other engineering teams, to ensure the delivery of robust, scalable, and efficient networking systems. This is an excellent opportunity for a hands-on leader who thrives in a fast-paced environment and is passionate about solving novel multicloud and distributed systems challenges.

What we look for:

• 5+ years of production-level experience in one of: Python, Java, Scala, C++, or a similar language
• 4+ years of experience developing large-scale distributed systems from scratch
• Experience working on a SaaS platform or with Service-Oriented Architectures.
• Extensive experience working on large-scale compute clusters, network connectivity, and automation.

(P-1286)

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. 

Networking Infrastructure is a core part of the platform that powers all our data and AI products. The platform also powers key enterprise security features used by customers across all our products to build connectivity solutions to cloud resources and prevent data exfiltration. 

We are seeking experienced Senior Software Engineers with large-scale distributed system experience to join the Networking Infrastructure team. You will design and automate the networking foundations for large-scale compute clusters across all the major cloud providers, connecting millions of VMs running on Databricks. You will lead the design and development of secure and scalable connectivity that powers all the data / AI workloads. You will work closely with cross-functional teams, including product management, operations, and other engineering teams, to ensure the delivery of robust, scalable, and efficient networking systems. This is an excellent opportunity for a hands-on leader who thrives in a fast-paced environment and is passionate about solving novel multicloud and distributed systems challenges.

What we look for:

• 5+ years of production-level experience in one of: Python, Java, Scala, C++, or a similar language
• 4+ years of experience developing large-scale distributed systems from scratch
• Experience working on a SaaS platform or with Service-Oriented Architectures.
• Extensive experience working on large-scale compute clusters, network connectivity, and automation.

RDQ127R133

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.

The Performance Engineering team works closely with multiple teams across the company to evaluate the performance of products and features, identify performance bottlenecks, and partner with engineers to solve performance and scalability issues. This implies, among other things, setting performance targets for various software releases, guiding teams to develop performance benchmarks, running competitive benchmark analysis for different Databricks products, doing deep dive analysis to identify performance issues and fix them. As the Sr. Engineering Manager, you will build partnerships with various engineering organizations, drive performance and scalability projects across these teams to deliver the fastest and most cost effective solutions in the market.

Key Responsibilities

• Technical Leadership: You will lead and guide the team to Identify performance limitations of the entire stack based on telemetry, customer signals, PoCs, and competitive benchmarks, that will result in the best performing system across the industry, when resolved.  
• Team Development: You will oversee sustained recruitment of top-tier talent, fostering a well-organized and synergistic team structure, and collaborating effectively with internal and external stakeholders
• Cross-Functional Collaboration: Work closely with product and infrastructure teams to align strategy, execution, and roadmap in alignment with organizational goals and priorities.

What We Look For

• 5+ years experience in the performance analysis discipline. Ability to identify performance issues, root cause problems, and be able to come up with potential solutions. 
• Ability to build strong working relationships with developers and field engineers to facilitate triaging and mitigation of performance problems.
• At least  3 years of experience in managing top-tier engineering teams
• BS in Computer Science (Masters or higher level of education preferred)
• Expertise in attracting, hiring and coaching engineers, who will meet the Databricks hiring standards. Experience up-leveling teams via hiring top-notch talent and growing existing team members.

RDQ426R230

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer-obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

In this role, you will lead the Notebook Dataplane team, which is responsible for running user code in the Notebook. We are undergoing an exciting architecture transformation to run stateful user code as a service for the product teams, providing a reliable and low-latency service for the Serverless products. A strategic investment area for the company. As the Engineering Manager, you will play a critical role in driving the technical vision, architecture, and execution for the service. You will lead a team of  software engineers and recruit new team members to realize the vision.

The impact you will have:

• Define and drive the stateful user code execution service vision.
• Partner with serverless platform teams to build the service.
• Own the roadmap and execution, ensuring all team deliverables are met with high quality and on schedule.
• Define team best practices for engineering excellence, including design reviews, code quality, testing strategies, and performance optimizations.
• Collaborate cross-functionally with teams across the stack.

What we look for:

• 10+ years of software engineering experience, with a strong track record of technical leadership and impact.
• 3+ years of engineering management experience.
• Experience designing, building, and operating scalable SaaS platforms.
• Expertise in distributed systems, cloud platforms (AWS, Azure, GCP), and modern web application architectures.
• Strong system-level skills. Experience with containers and K8S is highly desirable.
• Strong ability to collaborate across product, engineering, and business teams to align technical strategy with company growth objectives.
• Passion for the data intelligence space.

Why join us:

• Work on high-impact, high-visibility initiatives that directly contribute to Databricks' growth trajectory.
• Lead and mentor a talented team of engineers solving challenging, customer-centric problems.
• Drive innovation in a fast-paced, data-driven environment where your work helps shape the future of Databricks.

If you are passionate about building seamless, scalable experiences that fuel product-led growth, we would love to hear from you!

RDQ226R533

At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

We are the “AI/BI” team responsible for making Databricks the best product for business users to create, find and consume data insights. We work on 4 key pillars Dashboards, Genie, Databricks One and Unity Catalog Business semantics. UC Business semantics allow users to define business metrics and agent metadata in centrally governed systems for trusted access. Databricks One offers users a simplified experience tailored for non technical users to find and consume data insights. Genie lets users talk to their data with state of the art text-to-SQL and Dashboards lets users run their day to day business.

We're seeking a dedicated Engineering Leader who will help grow the Data visualization and UC Business Semantics teams.These teams will be tackling a number of challenging fullstack problem spaces, including: making visualizations easy to consume, enabling dashboards to be highly interactive, creating compelling augmented analytics experiences, providing best in class low/no code authoring, and increasing the analytical expressivity of our business semantics products.

You will report directly to the Senior Manager of Engineering.

The main responsibilities include:

• You will lead a talented engineering team of full stack engineers and SMEs focused on one of the above initiatives.
• You will oversee sustained recruitment of top-tier talent, and developing talent on the team.
• You will build processes to implement product vision and strategy, according to organizational goals and priorities.
• You will build software that is not just high quality, but easy to operate.
• You will manage technical debt, including long-term technical architecture decisions, and balance product roadmap.

What we look for:

• Great at hiring and developing talent
• Great at creating efficient processes that increase velocity and quality
• 2+ years of experience in managing teams that build and operate systems in a SaaS environment
• 5+ years of experience with distributed systems and building platforms and services and best in class application experience which serve multiple product teams and customers
• Have experience in scaling engineering teams from 5 to 20+
• Team player that will work with other departments (PM, CS) and engineering teams.
• BS or higher in Computer Science, or a related field
• Strong track record of attracting, hiring, and retaining top engineering talent
• Experience managing distributed teams across multiple locations.
• Adaptability and resilience in a fast-paced, rapidly evolving tech environment

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. 

Databricks’ Model Serving product provides enterprises with a unified, scalable, and governed platform to deploy and manage AI/ML models — from traditional ML to fine-tuned and proprietary large language models. It offers real-time, low-latency inference, governance, monitoring, and lineage. As AI adoption accelerates, Model Serving is a core pillar of the Databricks platform, enabling customers to operationalize models at scale with strong SLAs and cost efficiency.

As a Staff Engineer, you’ll play a critical role in shaping both the product experience and the foundational infrastructure of Model Serving. You will design and build systems that enable high-throughput, low-latency inference across CPU and GPU workloads, influence architectural direction, and collaborate closely across platform, product, infrastructure, and research teams to deliver a world-class serving platform.

The impact you will have:

• Design and implement core systems and APIs that power Databricks Model Serving, ensuring scalability, reliability, and operational excellence.
• Partner with product and engineering leadership to define the technical roadmap and long-term architecture for serving workloads.
• Drive architectural decisions and trade-offs to optimize performance, throughput, autoscaling, and operational efficiency for CPU and GPU serving workloads.
• Contribute directly to key components across the serving infrastructure — from model container builds and deployment workflows to runtime systems like routing, caching, observability, and intelligent autoscaling — ensuring smooth and efficient operations at scale.
• Collaborate cross-functionally with product, platform, and research teams to translate customer needs into reliable and performant systems.
• Lead technical initiatives that improve latency, availability, and cost-effectiveness across both customer-facing and foundational serving layers.
• Establish best practices for code quality, testing, and operational readiness, and mentor other engineers through design reviews and technical guidance.
• Represent the team in cross-organizational technical discussions and influence Databricks’ broader AI platform strategy.

What we look for:

• 10+ years of experience building and operating large-scale distributed systems.
• Deep expertise in model serving, inference systems, and related infrastructure (e.g., routing, scheduling, autoscaling, and observability).
• Strong foundation in algorithms, data structures, and system design as applied to large-scale, low-latency serving systems.
• Proven ability to deliver technically complex, high-impact initiatives that create measurable customer or business value.
• Experience leading architecture for large-scale, performance-sensitive CPU/GPU inference systems.
• Strong communication skills and ability to collaborate across teams in fast-moving environments.
• Strategic and product-oriented mindset with the ability to align technical execution with long-term vision.
• Passion for mentoring, growing engineers, and fostering technical excellence.

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. 

Foundation Model Serving is the API Product for hosting and serving frontier AI model inference for open source models like Llama, Qwen, and GPT OSS as well as proprietary models like Claude and OpenAI GPT. For this role, no prior ML or AI experience is necessary. We’re looking for engineers who have owned high scale operational sensitive systems like customer facing APIs, Edge Gateways, ML Inference, or similar services and have an interest in getting deep building LLM APIs and runtimes at scale.

As a Staff Engineer, you’ll play a critical role in shaping both the product experience and core infrastructure. You will design and build systems that enable high-throughput, low-latency inference on GPU workloads with frontier models, influence architectural direction, and collaborate closely across platform, product, infrastructure, and research teams to deliver a world-class foundation model API product.

The impact you will have:

• Design and implement core systems and APIs that power Databricks Foundation Model Serving, ensuring scalability, reliability, and operational excellence.
• Partner with product and engineering leadership to define the technical roadmap and long-term architecture for serving workloads.
• Drive architectural decisions and trade-offs to optimize performance, throughput, autoscaling, and operational efficiency for GPU serving workloads.
• Contribute directly to key components across the serving infrastructure — from working in systems like vLLM and SGLang to creating token based rate limiters and optimizers — ensuring smooth and efficient operations at scale.
• Collaborate cross-functionally with product, platform, and research teams to translate customer needs into reliable and performant systems.
• Establish best practices for code quality, testing, and operational readiness, and mentor other engineers through design reviews and technical guidance.
• Represent the team in cross-organizational technical discussions and influence Databricks’ broader AI platform strategy.

What we look for:

• 10+ years of experience building and operating large-scale distributed systems.
• Experience leading high-scale operationally sensitive backend systems.
• A track record of up-leveling teams engineering excellence.
• Strong foundation in algorithms, data structures, and system design as applied to large-scale, low-latency serving systems.
• Proven ability to deliver technically complex, high-impact initiatives that create measurable customer or business value.
• Strong communication skills and ability to collaborate across teams in fast-moving environments.
• Strategic and product-oriented mindset with the ability to align technical execution with long-term vision.
• Passion for mentoring, growing engineers, and fostering technical excellence.

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. 

Databricks’ Model Serving product provides enterprises with a unified, scalable, and governed platform to deploy and manage AI/ML models — from traditional ML to fine-tuned and proprietary large language models. It offers real-time, low-latency inference, governance, monitoring, and lineage. As AI adoption accelerates, Model Serving is a core pillar of the Databricks platform, enabling customers to operationalize models at scale with strong SLAs and cost efficiency.

As a Senior Engineer, you’ll play a critical role in shaping both the product experience and the foundational infrastructure of Model Serving. You will design and build systems that enable high-throughput, low-latency inference across CPU and GPU workloads, influence architectural direction, and collaborate closely across platform, product, infrastructure, and research teams to deliver a world-class serving platform.

The impact you will have:

• Design and implement core systems and APIs that power Databricks Model Serving, ensuring scalability, reliability, and operational excellence.
• Drive architectural decisions and trade-offs to optimize performance, throughput, autoscaling, and operational efficiency for CPU and GPU serving workloads.
• Contribute directly to key components across the serving infrastructure — from model container builds and deployment workflows to runtime systems like routing, caching, observability, and intelligent autoscaling — ensuring smooth and efficient operations at scale.
• Collaborate cross-functionally with product, platform, and research teams to translate customer needs into reliable and performant systems.
• Lead technical initiatives that improve latency, availability, and cost-effectiveness across both customer-facing and foundational serving layers.
• Establish best practices for code quality, testing, and operational readiness, and mentor other engineers through design reviews and technical guidance.

What we look for:

• 5+ years of experience building and operating large-scale distributed systems.
• Experience in model serving, inference systems, or related infrastructure (e.g., routing, scheduling, autoscaling, and observability).
• Strong foundation in algorithms, data structures, and system design as applied to large-scale, low-latency serving systems.
• Proven ability to deliver technically complex, high-impact initiatives that create measurable customer or business value.
• Experience building architecture for large-scale, performance-sensitive CPU/GPU inference systems.
• Strong communication skills and ability to collaborate across teams in fast-moving environments.
• Customer-focused mindset with the ability to align implementation details with product goals.
• Passion for mentoring, growing engineers, and fostering technical excellence.

RDQ426R193

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.

Search plays a foundational role in this mission. Whether through keyword-based retrieval, semantic similarity via vector embeddings, or hybrid approaches that combine both, our Search technologies help customers find, discover, and understand information across massive, complex datasets. These capabilities power everything from Retrieval Augmented Generation (RAG), AI assistants, and recommendation systems to enterprise knowledge management, in-product search, and data exploration.

As a Senior Engineering Manager for Search, you’ll play a critical role in building and scaling our next-generation Search product — spanning Vector Search, Keyword Search, and Search Quality. You’ll drive the design and evolution of a highly-performant, cost-efficient, and developer-friendly Search stack that enables customers to build AI applications with accuracy, speed, and scale. Beyond hands-on contributions, you’ll help define the long-term vision, mentor senior engineers, collaborate across teams, and lead strategic efforts that expand the technical and business impact of Search at Databricks.

The impact you will have:

• Lead a team of talented software engineers to design, build, and operate the next-generation cloud-native Search services.
• Drive innovation across Vector Search, Keyword Search, and Hybrid Search capabilities to improve relevance, latency, and cost efficiency.
• Build a strong partnership with product and research teams to define the roadmap for Search Quality, including ranking models and evaluation frameworks.
• Manage and operate large-scale, highly-available services in the cloud.
• Grow and mentor engineers and emerging leaders through coaching, feedback, and development opportunities.
• Shape and execute the long-term product and engineering strategy for Search.
• Partner cross-functionally with teams across Databricks to ensure the Search platform serves as a core enabler for AI and data applications.
• Foster a culture of technical excellence, accountability, and empathy.

What we look for:

• • 5+ years of experience in search, database systems, or AI/ML infrastructure.
  • Proven track record of building and scaling highly-available cloud services.
  • Strong leadership experience — building, growing, and managing high-performing engineering teams.
  • Experience defining and meeting SLOs for distributed, production-grade systems.
  • Solid understanding of search and indexing systems (e.g., Elasticsearch, Lucene, or vector databases).
  • Familiarity with database internals or large-scale data processing systems.
  • BS in Computer Science (Masters or PhD Preferred).

RDQ426R268

Databricks builds and operates some of the largest scale software systems on the planet. Every action and every operation performed on Databricks depends on reliable serving of identity information (users, groups, service principals). This puts Identity services into the critical path of everything else at Databricks and imposes the highest requirements for availability, scalability and performance.

As a Sr. Manager, Engineering on the Identity Platform team, you will build and operate highly available and scalable services that manage identities across multiple products in Databricks, allowing it to seamlessly scale and run across various geographic regions and clouds, and make Databricks the go-to product for big data processing in the cloud.

The impact you will have:

• You will hire great engineers to build an outstanding team
• You will support engineers in their career development by providing clear feedback, as well developing engineering leaders
• You will ensure high technical standards by instituting processes (architecture reviews, testing) and culture (engineering excellence)
• You will work with engineering and product leadership to build a long-term roadmap
• You will coordinate execution and collaborate across teams to unblock cross-cutting projects

What we look for:

• Great at hiring and developing talent, especially leadership
• Great at creating efficient processes that increase velocity and quality
• Managed teams that build and operate high-volume distributed systems in a SaaS environment
• 5+ years of experience with distributed systems and building services on top of containers
• Have experience scaling engineering teams from 5 to 20+
• Team player that will work with other departments (PM, CS) and engineering teams.
• BS or higher in Computer Science, or a related field

RDQ225R488

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. 

The Workspace Platform team is on an ambitious mission to scale our customer base 100x and support the future of agentic AI workloads. Our goal is to build a unified, consistent, and foundational Shared Platform for the entire Databricks Workspace experience.

As a Senior Engineering Manager on the Workspace Platform team, you will lead the development of unified infrastructure powering critical customer-facing capabilities across multiple Databricks products, including Content Discovery (akin to Google Search), Content Organization (akin to Google Drive), Collaborative code editing, and Repository management (akin to Github). This is a high-impact, exciting opportunity to guide a team of ~20 software engineers in creating platform features, intuitive workspace experiences, and partner integrations that are essential to Databricks' expansion and user adoption.

The impact you will have:

• Strategy & Vision: Define and drive the technical strategy for the Workspace Platform, including building over 16 shared capabilities that underpin the entire Databricks experience.
• Execution Ownership: Own the roadmap, execution, and delivery for the platform, ensuring all team deliverables meet the highest standards of quality and timeliness.
• Engineering Excellence: Establish and enforce team best practices for engineering excellence, including design reviews, code quality, testing strategies, and performance optimizations for high-volume distributed systems.
• Cross-Functional Collaboration: Partner closely with teams across the organization, including those developing vertical product experiences (Lakehouse Platform, SQL Warehouse, AI/BI Dashboards, UC Platform) and core infrastructure, to ensure seamless integration and innovation.

What we look for:

• Experience: 15+ years of software engineering experience with a strong track record of technical leadership and impact.
• Management: 5+ years of engineering management experience, including experience managing other managers.
• Scaling: Proven experience scaling engineering teams from 10 to 30+ engineers.
• Platform Expertise: Experience leading platform teams and backend developers in a SaaS environment.
• Technical Depth:
• Experience designing and building scalable distributed systems.
• Familiarity with building services on top of containerization technologies.
• Expertise in distributed systems, major cloud platforms (AWS, Azure, GCP), and modern web application architectures.
• Collaboration: Strong ability to collaborate across product, engineering, and business teams to align technical strategy with core company growth objectives.
• Passion: A passion for building and scaling robust, high-performance platforms.

P-1405

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. Databricks Mosaic AI offers a unique data-centric approach to building enterprise-quality, Machine Learning and Generative AI solutions, enabling organizations to securely and cost-effectively own and host ML and Generative AI models, augmented or trained with their enterprise data. And we're only getting started in Bengaluru , India - across 10 new teams that we're setting up from scratch !

The Partner Ecosystem team’s mission at Databricks is to enrich and win customer workloads through seamless integrations with strategic partners, while also widening the partner ecosystem to include new partners and data applications. This team enables seamless connectivity between Databricks and a vast range of partner applications through SQLDrivers. This vital data integration work powers the majority of the company’s Data Warehousing revenue by allowing customers to effortlessly connect their applications to Databricks SQL. In addition to that, through products like Databricks Partner Connect, we are simplifying the discovery and integration process, allowing you to seamlessly incorporate your preferred tools directly within the Databricks platform. 

We are seeking an experienced Senior Engineer to join our Partner Ecosystem team. In this role, you will design, develop, and maintain SQL drivers that power the majority of the data warehousing traffic and critical infrastructure components that power our partner integrations. You'll focus on optimizing SQLDrivers for performance, improved reliability and telemetry to offer seamless connectivity to our partners and enterprise customers, while also maintaining open source repositories and actively engaging with the developer community. You will collaborate with cross-functional teams to define technical requirements, architect solutions, and implement robust systems that enable our partners to connect seamlessly to the Databricks platform, ultimately driving Data Warehousing revenue and customer satisfaction.

The impact you'll have:

As a Senior Software Engineer working on the Partner Ecosystem team, you will get to build and evolve a set of highly performant and resilient Databricks SQL connectors for partners and enterprise customers enabling them to connect to Databricks SQL seamlessly and derive meaningful insights from data. In addition to that, you will get to evolve our Partner Connect offering, helping grow the elite partner ecosystem within Databricks.You will achieve this by being customer obsessed, raising the bar on open source community engagement, being hands-on in building the product, closely collaborating with the product team. You’ll work on challenges such as:

• Building reliable SQL connectors
• Engage and grow the open source community around SQL connectors
• Work closely with the SQL server teams, delivering new features to the SQL connectors, as per customer needs.
• Work closely with product team to shape the future of Partner Connect, thus growing the partner ecosystem around Databricks

What We Look For

• BTech (or higher) in Computer Science, or a related field
• 7+ years of production level experience in one of: Java, Python, Go, or similar language
• Comfortable working towards a multi-quarter vision with incremental deliverables
• Proven track record in architecting, developing, deploying, and operating highly performant systems
• Experience with open source communities through maintaining or contributing to open source repositories
• Demonstrated ability to lead engineering projects across functional and organizational boundaries
• Ability to navigate ambiguity and work with stakeholders to bring clarity and design innovative solutions to complex problems

RDQ126R106

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

As a Sr. Staff Software Engineer you will be part of the executive leadership team on the Data Platform org. You will leverage bleeding-edge AI developer tools and techniques to help build the Data Intelligence Platform that will allow us to automate decision-making across Databricks. You will achieve this in collaboration with prominent Tech Leads, Databricks Product Teams, Data Science, and many more. You will define the future of a variety of tools spanning logging, orchestration, data transformation, metric store, governance platforms, and data consumption layers, just to name a few.

The impact you will have:

• Design and run the cross-company Data Intelligence Platform, which contains every business and product metric used to run Databricks. You’ll play a key role in developing the right balance of data protection and ease of shareability for the Data Intelligence Platform as we transition to a public company.
• Develop tooling and infrastructure to efficiently manage and run Databricks on Databricks at scale, across multiple clouds, geographies, and deployment types. This includes CI/CD processes, test frameworks for pipelines and data quality, and infrastructure-as-code tooling.
• Partner with other prominent tech leaders to develop and influence technical direction and capabilities of our Databricks product.
• Be customer 0 and a trusted advisor to product leadership.
• Represent Databricks at academic and industrial conferences & events.

What we look for:

• AI first mindset - Your personal productivity is augmented with AI to drive high-impact, technically complex initiatives and code that delivers clear value.
• BS/MS/PhD in Computer Science or related majors, or equivalent experience.
• 15+ years of industry experience building and operating large-scale distributed systems.
• 6+ years of experience providing technical leadership on planet-scale production data systems 
• Experience leading architecture efforts for performance-sensitive systems (e.g., latency-critical services, multi-tenant platforms, large-scale indexing pipelines).
• Strong communication skills and the ability to operate effectively in fast-paced, cross-functional environments.
• A strategic mindset with the ability to align engineering execution with longer-term product and company goals.
• Passion for mentoring and developing other engineers.

RDQ225R487

Job Description

Databricks is looking for a Senior Manager, Infrastructure Data Science to shape the future of Databricks infrastructure through data science. You will tackle some of the most complex challenges related to capacity planning, performance optimization, reliability engineering, infrastructure efficiency, and customer experience.  You will lead a team of data scientists and work directly in partnership with engineering leaders to empower them with data-driven insights and solutions. 

At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions.

Founded in 2013 by the original creators of Apache Spark, Databricks has grown from a tiny corner office in Berkeley, CA to a global organization with over 7000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest-growing SaaS companies in the world.

Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security, and scale that is critical to making customers successful on our platform.

The impact you will have:

• Thought leadership and strategic guidance on infrastructure planning, balancing current needs with future growth projections to ensure scalability and cost-effectiveness.
• Promote a data-driven approach to infrastructure decisions, influencing stakeholders across engineering, and support to leverage data science insights for high-impact, aligned strategies.
• Implement data-driven solutions to identify, predict, and mitigate infrastructure risks and failures, reducing downtime and improving system reliability and performance, directly impacting end-user satisfaction and operational continuity.
• Spearhead analyses to improve resource utilization efficiency, identifying and eliminating inefficiencies across infrastructure usage, resulting in cost savings and optimized performance.
• Establish data frameworks that empower support teams to troubleshoot and resolve product issues faster, decreasing response times and enhancing customer experience and support quality.
• Mentor and manage a team of data scientists, instilling best practices in data science, engineering, and fostering a collaborative environment focused on innovative, scalable infrastructure solutions.

What we look for:

• 10+ years of infrastructure data science, machine learning, advanced analytics experience in high velocity, high-growth companies
• 5+ years of management experience hiring and developing teams
• Experience developing data science, analytics, and machine learning and AI products and capabilities in a cloud environment
• Knowledge of statistics and rigorous analytical techniques
• Experience with data visualization tools, knowledge of data engineering, data modeling, and big data technologies
• Leadership skills and experience to lead across functional and organizational lines
• Strong communication skills to explain and evangelize analytics and data science to executives and the senior management team
• Bias to action and passion for delivering high-quality data solutions
• A passion for problem-solving and comfort with ambiguity
• MS or Ph.D. in quantitative fields (Statistics, Math, CS or Engineering)