Lead Software Development Engineer Ii Data Jobs

This role is part of Datadog’s Security Agent team, which powers critical security capabilities across Workload Protection, Vulnerability Management, Cloud Security products, and other emerging security offerings. As a Staff Software Engineer, you will lead the design and development of low-level Linux instrumentation and runtime security technologies that help customers detect threats, monitor system activity, and protect cloud-native workloads at scale. You will work on complex technical challenges involving eBPF, Linux kernel internals, performance-sensitive systems, and large-scale data collection while influencing technical direction across multiple product teams. This role offers significant ownership, broad organizational impact, and the opportunity to shape the future of Datadog’s security platform. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead the architecture and development of security agent capabilities that power runtime threat detection and workload protection across Datadog Security products. Design and build reusable eBPF-based monitoring functionality for process, file, and network visibility within Linux environments. Drive end-to-end delivery of new features, from technical strategy and design through implementation, testing, and rollout. Establish and evolve testing methodologies that improve platform coverage, detection quality, reliability, and performance. Partner with product, security, infrastructure, and engineering teams to deliver shared platform capabilities used across multiple Datadog products. Provide technical leadership by influencing engineering direction, mentoring peers, and helping resolve complex cross-functional challenges. Who You Are: You have significant experience building software in Linux environments,

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Inference organization serves Claude to millions of users and enterprise customers with the speed, reliability, and efficiency that frontier AI demands. We build across GPUs, TPUs, and Trainium, and the complexity of our development environment grows with every platform we add. We're looking for a Staff engineer to be the technical lead for Inference Developer Productivity: the team that makes every engineer in the org dramatically more effective at building, testing, and shipping inference software. This is a senior IC role with broad technical ownership. You'll set technical direction for the team's toolchains, workflows, and feedback loops, and you'll be the one making the hard calls on architecture, prioritization, and tradeoffs across heterogeneous accelerator platforms. You'll pair with the team's Engineering Manager, who owns hiring and people development, while you own the technical roadmap and drive the work. You'll also partner closely with Anthropic's central Infrastructure org, where company-wide developer productivity lives, to make sure Inference's multi-accelerator reality is well served without duplicating effort. This role is for someone who has been the technical anchor on a platform or infrastructure team before, who thinks in systems and feedback loops, and who gets real satisfaction from the moment another engineer stops fighting their environment and starts shipping. Key responsibilities Set technical direction for Inference Developer Productivity, owning the architecture and roadmap for toolchains, dev environments, and CI/CD across GPU (CUDA), TPU, and Trainium platforms Be the techni

RDQ427R351 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 Staff Engineer 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. Check out our recent blog post: Decoupled by Design: Billion-Scale AI Search The impact you will have: Drive the architecture and evolution of the Search product, delivering scalable, low-latency, and high-quality retrieval across massive multimodal datasets. Identify and solve challenges in indexing, storage, query execution, and ranking — blending innovations in vector search, keyword search, and hybrid retrieval techniques. Partner with infrastructure, product, and research teams to shape APIs and developer experiences that

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Corporate Systems Engineering builds and operates the software platforms, integrations, and automations that power Smartsheet’s core business functions across Finance, Sales/GTM, and People & Culture. Our team owns mission-critical systems and workflows that enable how the company hires, sells, bills, pays, reports, and scales. We operate at the intersection of software engineering, enterprise platforms, and business-critical data, treating internal systems with the same rigor, reliability, and product mindset as customer-facing software. The Automation team builds human-to-system and system-to-system automations that reduce manual effort and friction across the business. We combine cloud-native services, agentic AI, and workflow orchestration to enable employees to interact with enterprise systems through intelligent, secure, and auditable automation. As a Senior Software Engineer I (Automation), you will lead the design, build, and operation of systems and workflows that directly support business execution at scale. You will own complex technical initiatives, partner with Product Managers and stakeholders on technical roadmaps, and mentor junior engineers. This full-time position reports to the Sr. Director, Development and can be located in our Bellevue, WA office, or you may work remotely from anywhere in the US where Smartsheet is a registered employer. You Will: Architect AI Agents: Take a leading role in designing Agentic Workflows using AWS Step Functions and Bedrock Agents that reason

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Senior Software Engineer, you will lead the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders. You will: Lead the design and implementation of scalable backend systems and distributed architectures for Federal customers. Manage the full lifecycle of feature development from requirement definition to deployment on classified networks. Direct the orchestration of asynchronous agent fleets to meet mission requirements. Lead customer engagements to translate mission needs into technical requirements. Own the communication with stakeholders to ensure implementation meets defined acceptance criteria. Conduct technical reviews and identify risks within machine learning infrastructure and model serving. Drive the platform roadmap by providing technical specifications for Federal product offerings. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and contai

P-1385 We are hiring a Senior Staff Software Engineer for Databricks' Engineering team reporting to an Engineering Leader. You will be part of the Databricks engineering organization, working with teams that develop Databricks products and features for thousands of enterprises worldwide. Key Characteristics As an executive engineering individual contributor at Databricks, you will have full ownership of the product or infrastructure direction in a major area, driving it from initial development to scalable solutions with clear business impact. You will serve as a force multiplier by elevating stability, reliability, and organizational processes, while bringing deep expertise in large-scale distributed systems. You will mentor senior engineers, contribute to recruiting, and lead high-impact company projects, often tackling complex problems beyond their comfort zone. Job Description 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 own missions. 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. The Impact You Will Have Solve real business needs at large scale by applying your software engineering. Deliver a highly scalable, available, and fault-tolerant engine processing hundreds of TB of data daily across thousands of customers Low level systems debugging, performance measurement & optimizat

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Forward Deployed Software Engineers (FDSEs) understand our customers’ greatest pain points and design end-to-end solutions to address them. FDSEs solicit constant feedback on their work from both customers and colleagues, improving our products over time with rapid iteration cycles. FDSEs deploy ground breaking technical solutions to solve our customers’ hardest problems. Projects often start with a nebulous question like “Why are we losing customers?” or “How can we more effectively identify instances of money laundering?” FDSEs lead the way in developing a solution, from high-level system design and prototyping to application development and data integration. As an FDSE, you leverage everything around you: Palantir products, open source technologies, and anything you and your team can build to drive real impact. You work with customers around the globe, where you gain rare insight into the world’s most important industries and institutions. We help our customers detect insider trading, improve disaster relief, fight healthcare fraud, and more. Each mission presents different challenges, from the regulatory environment to the nature of the data to the user population. You will work to accommodate all aspects of an environment to drive real technical outcomes for our customers. Whether you aspire to be an entrepreneur or an engineering leader, we believe Palantir is the best place — with the best colleagues — to learn how. You’ll learn how to unpack a problem and understand the costs and consequences of its solution. You’ll learn new technologies and languages, and even develop them yourself. You’ll work autonomously and make decisions independently,

P-150 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 Staff Software Engineer for Search Quality, you will drive the technical direction of ranking, relevance, evaluation, and quality initiatives across Databricks’ next-generation Search product. You’ll design and build the systems, models, and evaluation frameworks that ensure our Search stack delivers accurate, high-quality results across diverse multimodal datasets and query patterns. You’ll work across research, product, and infra to push the frontier of retrieval quality for enterprise AI applications — blending traditional information retrieval techniques, representation learning, and neural ranking. Beyond hands-on contributions, you will help define our long-term vision for relevance and quality, mentor senior engineers, and lead strategic efforts that raise the accuracy, reliability, and product impact of Search across Databricks. Check out our recent blog post: Reranking in Databricks AI Search for Faster, Smarter Retrieval in RAG Agents The impact you will have: Lead the technical vision for Search Quality, shaping the ranking architecture, relevance modeling stack, and evaluation systems that power Datab

P-1403 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. Ingesting data into the Lakehouse is a strategic area of investment for Databricks and a key enabler for Data and AI workflows. Lakeflow Connect is looking to solve this problem by providing ready-to-use, point-and-click connectors for a wide variety of sources, including enterprise applications (like Salesforce, Workday, ServiceNow, SharePoint), databases (e.g., SQL Server), cloud storage, message queues, and local files. In addition to being an important part of Lakeflow and Data Engineering, Connect is also a key platform capability. Every surface in Databricks (Dashboards, Notebooks, SQL, AI) requires ingestion capabilities and the lead for this role will need to work closely with other products to embed Connect into these surfaces. We are looking for engineers with experience in core Database internals to join our Lakeflow Connect team. A key part of Connect is to extract data from OLTP systems while imposing minimal load on production systems. To do this efficiently we are building systems that use techniques such as incremental data capture, log parsing, etc. We are looking for engineers who continue to be hands on and are looking to make a large impact on an important problem for the company. The Impact you will have: Solve real business needs at large scale by applying your software engineering. Deliver a highly scalable, available, and fault-tolerant engine processing hundreds of TB of data daily across thousands of customers Low level systems debugging, performance measurement & optimization on large production clusters. Build architecture design, influence product roadmap, and ta

P-375 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. Ingesting data into the Lakehouse is a strategic area of investment for Databricks and a key enabler for Data and AI workflows. Lakeflow Connect is looking to solve this problem by providing ready-to-use, point-and-click connectors for a wide variety of sources, including enterprise applications (like Salesforce, Workday, ServiceNow, SharePoint), databases (e.g., SQL Server), cloud storage, message queues, and local files. In addition to being an important part of Lakeflow and Data Engineering, Connect is also a key platform capability. Every surface in Databricks (Dashboards, Notebooks, SQL, AI) requires ingestion capabilities and the lead for this role will need to work closely with other products to embed Connect into these surfaces. We are looking for engineers with experience in core Database internals to join our Lakeflow Connect team. A key part of Connect is to extract data from OLTP systems while imposing minimal load on production systems. To do this efficiently we are building systems that use techniques such as incremental data capture, log parsing, etc. We are looking for engineers who continue to be hands on and are looking to make a large impact on an important problem for the company. The Impact you will have: Solve real business needs at large scale by applying your software engineering. Deliver a highly scalable, available, and fault-tolerant engine processing hundreds of TB of data daily across thousands of customers Low level systems debugging, performance measurement & optimization on large production clusters. Build architecture design, influence product roadmap, and tak

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Forward Deployed Software Engineers (FDSEs) understand our customers’ greatest pain points and design end-to-end solutions to address them. FDSEs solicit constant feedback on their work from both customers and colleagues, improving our products over time with rapid iteration cycles. FDSEs deploy ground breaking technical solutions to solve our customers’ hardest problems. Projects often start with a nebulous question like “Why are we losing customers?” or “How can we more effectively identify instances of money laundering?” FDSEs lead the way in developing a solution, from high-level system design and prototyping to application development and data integration. As an FDSE, you leverage everything around you: Palantir products, open source technologies, and anything you and your team can build to drive real impact. You work with customers around the globe, where you gain rare insight into the world’s most important industries and institutions. We help our customers detect insider trading, improve disaster relief, fight healthcare fraud, and more. Each mission presents different challenges, from the regulatory environment to the nature of the data to the user population. You will work to accommodate all aspects of an environment to drive real technical outcomes for our customers. Whether you aspire to be an entrepreneur or an engineering leader, we believe Palantir is the best place — with the best colleagues — to learn how. You’ll learn how to unpack a problem and understand the costs and consequences of its solution. You’ll learn new technologies and languages, and even develop them yourself. You’ll work autonomously and make decisions independently,

Who we are 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 AI-powered Assistant serves as the initial point of contact for customers seeking assistance on how to use our platform effectively. The Customer Engagement and Docs platform team's objective is to help customers resolve their problems faster using AI / LLMs. We provide customers with precise and comprehensive solutions to their problems or build experiences to facilitate a seamless escalation to a support agent when necessary. As a Staff Engineer, you will operate at the intersection of Product development and Machine Learning. Responsibilities include gaining a deep understanding of user behavior; identifying factors contributing to problems; leveraging Product, Machine Learning (ML) and Large Language Models (LLMs) to analyze intricate technical use cases within a secure enterprise environment and eventually providing a path to resolving them. The impact you will have: Lead design, development, and deployment of systems for Evaluation, Answer retrieval and Quality improvement for helping customers. Lead architectural decisions to ensure performance, reliability, and accuracy of the knowledge systems. Drive best practices for engineering excellence, including design reviews, code quality, testing strategies, and performance optimizations. Deliver high-quality, production-ready code and serv

P-1408 The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products . Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Some of them can have hundreds of millions of assets. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. As our Search product continues to evolve, we are seeking a Staff Engineer to lead enhancements to our Search Quality. In 2025, we will focus on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale. Key Responsibilities Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience. Contribute to building a robust framework for evaluating search ranking improvements - both offline and online. What We’re Looking For BS+ (M.S. or PhD preferred) in Computer Science, or a related field. 10+ years experience developing search relevance systems at scale in production or in high-impact research environments. Experience applying LLM to search relevance Experience in one or more of the following: Query understanding NLP Text mining Recommendations Personalization Discovery Conversational AI Strong understanding of computer science fundamentals. Contributions to well-used open-source projects. Why Join Us? At Databricks,

P-1408 The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products. Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Some of them can have hundreds of millions of assets. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. As our Search product continues to evolve, we are seeking a Staff Engineer to lead enhancements to our Search Quality. In 2026, we will focus on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale. Key Responsibilities Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience. Contribute to building a robust framework for evaluating search ranking improvements - both offline and online. What We’re Looking For BS+ (M.S. or PhD preferred) in Computer Science, or a related field. 10+ years experience developing search relevance systems at scale in production or in high-impact research environments. Experience applying LLM to search relevance Experience in one or more of the following: Query understanding NLP Text mining Recommendations Personalization Discovery Conversational AI Strong understanding of computer science fundamentals. Contributions to well-used open-source projects. Why Join Us? At Databricks, w

P-1403 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. Ingesting data into the Lakehouse is a strategic area of investment for Databricks and a key enabler for Data and AI workflows. Lakeflow Connect is looking to solve this problem by providing ready-to-use, point-and-click connectors for a wide variety of sources, including enterprise applications (like Salesforce, Workday, ServiceNow, SharePoint), databases (e.g., SQL Server), cloud storage, message queues, and local files. In addition to being an important part of Lakeflow and Data Engineering, Connect is also a key platform capability. Every surface in Databricks (Dashboards, Notebooks, SQL, AI) requires ingestion capabilities and the lead for this role will need to work closely with other products to embed Connect into these surfaces. We are looking for engineers with experience in core Database internals to join our Lakeflow Connect team. A key part of Connect is to extract data from OLTP systems while imposing minimal load on production systems. To do this efficiently we are building systems that use techniques such as incremental data capture, log parsing, etc. We are looking for engineers who continue to be hands on and are looking to make a large impact on an important problem for the company. The Impact you will have: Solve real business needs at large scale by applying your software engineering. Deliver a highly scalable, available, and fault-tolerant engine processing hundreds of TB of data daily across thousands of customers Low level systems debugging, performance measurement & optimization on large production clusters. Build architecture design, influence product roadmap, and ta