Manager I Engineering Source Code Integration Manager Jobs

Source Code Integration enables Product teams at Datadog to develop features that leverage our customers’ source code. This brings the platform closer to developers, as it helps them relate their telemetry to code to run automated investigations, debug their services with stack traces and profiles, scan their code for security issues, or make proactive fixes, among others. The team owns all the platform services, infrastructure and integrations required to access and synchronize our customer repositories in a secure, reliable and efficient manner. We are looking for a hands-on technical leader to drive the growth of our platform, as Datadog shifts left and becomes more developer-friendly and AI-ready. In this role you will lead the growth of our platform to support an increasing number of high profile features and teams, and work with a team of engineers of varied experience levels to shape our roadmap and deliver impactful solutions at scale. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Lead and cultivate a team of engineers of diverse experience levels, including performance management and career development Lead technical and strategical discussions to better understand the challenges and opportunities faced by our team and our stakeholders Own and drive the relationships with product teams and major stakeholders, balancing competing requests with long term investments, and prioritizing impact across the whole platform Run a lightweight process to pace and track what we work on. Support the progressive delivery of high quality work through demos and frequent iteration Stay in touch with your team’s systems, and roll up your sleeves when needed to unblock your team by writing code or troubleshooting issue

The Documentation team creates engaging and informative technical content, particularly our public product documentation: Datadog Docs . This is an opportunity for a Documentation Manager to help us deliver high quality technical documentation and lead one of our growing documentation teams. Our team is hands-on with the technologies that Datadog monitors, and collaborates with technical and product teams to create technical documentation for our APIs, SDKs, developer and security tools, and community developed integrations — thousands of pages of content! This role is remote in North America. What You’ll Do: Manage 3-5 technical writer direct reports, overseeing their day-to-day, helping them make and manage effective content project plans, formally supporting their growth and development, and fostering an environment that encourages positive engagement and performance. Partner with our Product and Engineering teams to create and maintain public documentation for users, developers, and SREs, helping them succeed with Datadog products, features, SDKs, APIs, and developer tools. Experiment with the product, dig into source code, and interview subject matter experts to research technical details for documentation. Collaborate with our contributor community and greater Documentation team to develop and improve documentation standards and processes. Who You Are: You have 5-10 years experience researching and developing documentation for technical topics, like databases, APIs, cloud infrastructure, and performance and security monitoring. You have 2-5 years experience managing a small team of technical writers, coaching their performance, guiding their career journey, and breaking down complex projects into achievable plans. You have publicly available technical writing samples. You are comfortable reading at least two programming languages (e.g. Ruby, Python, Go, bash). You have written or managed documentation as code, and are familiar with modern infrastructure such a

The Security Libraries team owns the customer-side integrations behind Datadog’s run-time security products — App & API Protection , Workload Protection , and Code Security — shipping and maintaining security capabilities across seven open-source language libraries ( .NET , Java , Go , Node.js , Python , Ruby , PHP ) and a set of HTTP proxy integrations (Envoy, NGINX, and HAProxy), running inside thousands of production clusters worldwide. Recent work spans exploit prevention (RASP), WAF detections, API Security, code security (IAST and SCA), and AI-assisted onboarding. As Engineering Manager, you’ll lead part of this polyglot team, setting the technical bar and team culture while driving the pace at which new detections and AI-assisted capabilities reach customers. This is a hands-on role: you’ll balance people leadership, product and roadmap ownership, and the operational health of code that runs in production at massive scale, with room to grow into more of Datadog’s security portfolio over time. 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, grow, and develop a team of roughly 4-8 library engineers — coaching, giving direct feedback, and empowering senior ICs as technical leaders Own team delivery and productivity: planning, milestones, reviews, and the on-call rotation Set product direction with Product Management and balance priorities across App & API Protection, Workload Protection, and Code Security Stay technically close to the work — apply strong technical judgment, contribute code where it matters most, and keep quality and architecture high Build strong relationships and drive alignment across the language teams and product, backend, and frontend partners Shape team identity and culture, and own accountability when problems oc

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Modal is the cloud platform built for AI. We're used by the world's leading AI labs, startups, and researchers to run compute-intensive workloads: training runs, inference, sandboxed code execution, and more. We're hiring a Community Manager in SF to make Modal a fixture in the AI developer community. You'll bring developers together through meetups, hackathons, and events of our own, and build the kind of community that keeps showing up. You know how to rinse and repeat the process, but always with a creative bend. In this role, you will: Co-host developer meetups with partners in our ecosystem. Find the right speakers, build the relationships, and run the events together. Prior examples: High Performance Inference for Open LLMs , Voice AI Builders Night , RL with Modal and Prime Intellect , FDE Happy Hour . Sponsor hackathons that attract highly technical enginee

This Engineering Manager will lead the Data Visualizations Explorations team within the Graphing organization, setting product direction, and coaching and developing team members. They will staff and drive projects that build end to end experiences for Datadog’s core users: observability engineers. This includes extending the capabilities of core widgets like Hostmap and Geomap Visualizations and finding innovative ways to leverage existing Datadog data sources. This role also involves close partnerships with other product teams to deeply understand customer needs and deliver compelling data experiences. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Work with Product Management and Design to plan and staff projects for the Data Visualization Explorations team Coach and develop engineers at various levels Ensure strong cross-team communication and design best practices around project management, code review, architecture patterns, and more. Proactively anticipate cross-team dependencies and blockers to goals. Identify opportunities to appropriately reuse or customize features across dashboards, notebooks, and product pages. Deeply understand the needs of our customers and other Datadog products we work with. Participate in customer conversations, review product briefs, read feature requests, and coach team members to adopt these practices as well. Define and maintain high standards for operations practices, including bug triage and remediation, incident response, and gathering and analyzing performance telemetry for our widgets. Who You Are: At least 2 years of people management experience in a software engineering or similar setting Strong TypeScript/JavaScript skills, including familiarity with front

Observability Pipelines (OP) is Datadog's on-premise, vendor-agnostic telemetry pipeline product. As an Engineering Manager on the team, you'll own people management and engineering execution for one of OP's core missions, spanning areas like Integrations (ingesting from and routing to the many source and destination systems customers rely on), streaming insights, cost control, or pipeline capabilities, reliability and scalability. You'll partner directly with Product to help shape the roadmap, and work closely with your peer EMs and senior ICs to define how OP operates and grows. This is an opportunity to build your management craft while having real influence over the technical direction of a fast-growing product area. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Own people management and engineering execution Establish a strong operating rhythm for the team Drive high standards for on-call rotations and incident response Partner with Product on the roadmap, balancing product priorities with technical realities Lead, coach, and grow the careers of engineers on your team Who You Are: Experienced managing engineers directly, comfortable owning a team’s operating rhythm end-to-end, from planning through execution and stakeholder communication to incident and on-call ownership Have a technical background in distributed systems and data infrastructure Have experience with on-premises or customer-installed software concepts A product-minded partner to have on the team — you enjoy working with Product on strategy Experience with high-performance or Rust-based data pipeline systems Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications o

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role We're looking for an Engineering Manager to lead a team of highly experienced engineers building the infrastructure that powers Modal's serverless GPU platform. This is a hands-on leadership role — expect to split your time between technical contribution and people management depending on what the team needs. You'll set direction, remove blockers, and build a strong engineering culture as your team tackles hard problems in distributed computing, large-scale data handling, and performance optimization. Who You Are You're an experienced engineering leader who stays close to the work and builds alongside your team when it counts. You earn trust through technical depth, not title. You communicate clearly, help strong engineers move fast without cutting corners, and stay calm and pragmatic under pressure. You care as much about how your team gets to an answer as the answ

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We’re looking for an Engineering Manager to lead a group of highly experienced engineers. This is a hands-on leadership role where you’ll spend roughly half your time on technical contribution and half on people management, depending on the need. You’ll work closely with the team to set direction, remove blockers, and foster a strong engineering culture as they tackle complex systems challenges in distributed computing, large-scale data handling, and performance optimization. Who You Are: We think you are an experienced engineering leader who thrives close to the work and enjoys building alongside their team when needed. You earn trust through technical depth, communicate with clarity, and help great engineers move fast and make sound decisions. You thrive in a fast paced environment, you are pragmatic, calm under pressure, and focused on impact. Requirements: At l

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders About the Role We're hiring the first Account Managers at Modal. You'll report to the Regional Director of Account Management and be a founding member of the team. This function does not exist yet. There is no playbook, no territory map, no established motion. You'll own a book of business from day one and build the motion at the same time — from fast-moving AI startups to large enterprise teams running critical infrastructure on Modal. This is a commercial role with a revenue target. You'll be measured on retention and expansion across your accounts. While you won't be delivering the technical recommendations and implementation, the work is technical by nature. Our customers are engineers running GPU workloads, inference, and batch jobs in production, and you need to hold your own in those conversations. The profile we're hiring is a technical account manager. You've worked at companies that are deepl

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We’re looking for business operations managers to join the team. This person will work closely with folks across marketing, sales, operations, and finance across a variety of initiatives to help scale the business in our next phase of growth. You'll be a generalist who gets in the weeds on all the business and operational aspects of a high-growth startup. In this role, you will: Drive in-depth quantitative analyses to inform our pricing and packaging strategy. Help spin up our deal desk and streamline enterprise deals. Support the exec team on various finance functions, from investor relations to large cloud vendor negotiations to identifying cost optimization opportunities. Implement new tools and processes to enable the GTM org to grow rapidly. Get creative on a spectrum of ad-hoc projects like securing new office space in Manhattan. Requirements: We are looking

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role: Ray aims to provide a universal API for building distributed applications (e.g. a machine learning pipeline of feature engineering, model training, and evaluation). Data is usually a core element connecting these different stages, and therefore plays a critical role in Ray’s usability, performance, and stability. We are looking for strong engineers to build, optimize, and scale Ray’s Datasets library and data processing capabilities in general. About the Ray Data team: The Ray Data team currently develops and maintains the Ray Datasets library, which is already powering critical production use cases (e.g. large scale data compaction at Amazon , and ML pipeline at Alibaba ). Ray Datasets is a Python library built on top of Apache Arrow and Ray Core (Ray’s C++ backend), and the Ray Data team interacts closely with Ray Core components including the scheduler and the memory & I/O subsystems. The Ray Data team also works closely with Ray’s ML libraries including Train, RLlib, and Serve. A snapshot of projects you will work on: - Performance of Ray Datasets at large scale (leveraging Arrow primitives, optimizing Ray object manager, etc.) - Integration with ML training and data sources - Stability an

AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. About the Role: As a Manager, Enterprise Sales, you will lead and scale our enterprise sales team, driving strategic revenue growth with a consultative, customer-first approach. You will oversee complex deal cycles, coach Enterprise Account Executives, and build the motion that wins high-impact, multi-stakeholder deals in a rapidly evolving AI landscape. What You’ll Do Lead, mentor, and develop a team of Enterprise Account Executives, fostering a culture of performance, strategic thinking, and collaboration Own and guide the full enterprise sales cycle, from targeted outbound and discovery to multi-threaded navigation, negotiation, and close Build and refine enterprise sales playbooks, qualification frameworks, and forecasting models that increase accuracy and velocity Collaborate cross-functionally with Product, Marketing, and Engineering to align on go-to-market strategy, unblock en

AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. About the Role We're seeking a Revenue Operations Manager with a strong track record, a builder's mindset, and a bias for action to join our in-person team in New York or SF. This is a high-impact, hands-on role. You'll own the entire revenue operations function, from top-of-funnel lead routing through deal close and commission administration. You'll work closely with our Head of Finance & People Ops and sales leadership to build the systems, dashboards, and processes that scale our go-to-market motion. What You'll Do: Own the lead routing process from inbound and partnering with marketing to ensure proper attribution Run effective territory management & strategy for Geo based decisioning Support & strategise every aspect of revenue operations in your territory Own the strategy for capacity forecasting, inputs, throughputs & outputs being the conduit back to finance in

About the Team The Technical Success team is responsible for ensuring developers and enterprises are successful in building scalable production applications with the OpenAI API platform. We guide and support customers to achieve maximum benefits, value, and adoption from deploying our highly-capable models. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role We are looking for a technically savvy and business-minded AI Deployment Engineer to deeply partner with our most strategic and high-impact platform customers, guiding them through application ideation, development, delivery, and scale to accelerate and maximize the value of what they build with our platform. You will have the opportunity to work on the most novel and creative use cases being built on our API, serving as a critical partner for collecting and delivering high fidelity feedback to Product and Research teams. This role is based in Tokyo, Japan. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees In this role, you will: Deeply embed with our most strategic platform customers, serving as their technical thought partner in ideating and building novel applications on our API. Proactively provide guidance to our customers on how to maximize business impact from their applications, accelerating their time to value. Experiment and prototype solutions with and for your customers. Forge and manage relationships with our customers’ leadership and stakeholders to ensure their application’s successful deployment and scale. Contribute to our open-source developer and enterprise resources. Scale the AI Deployment Engineering function through sharing knowledge, codifying best practices, and publishing notebooks to our internal and external repositories. Validate, synthesize, and deliver high-signal feedback to the Product and Research teams. Use your expertise i

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. The Snowhouse Foundation team builds our globally distributed data warehouse. We manage a vast array of petabyte scale data sets that are continuously ingested, processed and replicated from across all Snowflake environments and external data sources. Snowhouse powers all of Snowflake’s core business, engineering and data science needs and provides customers with full visibility into their account activities, usage, and resource consumption from all their global environments. The team is investing in multiple critical areas, including a pipeline authoring platform, high performance/high efficiency data export, ingestion and data layout. Our team is also responsible for a fundamental product for Snowflake’s customers: the Snowflake system database/application that provides customers with all usage insights they need to reason about their global Snowflake footprint as well as 1st party business logic such as ML powered functions and Budgeting applications. AS A PRINCIPAL SOFTWARE ENGINEER IN SNOWHOUSE FOUNDATION, YOU WILL: Design and implement innovative highly available distributed platforms and pipelines and enhance the overall Snowflake data infrastructure Lead and drive projects from idea formulation to design, implementation and successful productionization. Collaborate