Model Behavior Engineer Jobs

The AI platform is responsible for all AI infrastructure across Datadog. Our mission is to provide tools and platforms that enable data scientists and engineers to conduct large-scale training and inference with ease. We support products such as Bits AI , LLMObs and all our AI research . As an engineering manager for the Evaluation & Annotation team, you’ll join a new and fast growing team and organization. You will support building and scaling the team, define our technical vision and help shape the roadmap. Your team will lead the charge on multiple critical technical challenges: AI model evaluation both offline and online, designing tooling and processes around human annotation, and establishing the standard around synthetics and AI generated datasets. You’ll work closely with sister teams in the AI platform organization ensuring a seamless AI development cycle. You’ll also partner with the Applied AI org and with Datadog infrastructure & tooling teams to build out systems from the ground up. 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: Manage and grow the Evaluation & Annotation team, directly managing 4-6 engineers Define our technical roadmap in alignment with AI platform goals and the Applied AI team roadmap. Work with our core platform teams to tailor Datadog's storage and data pipelines to our needs Create a strong team culture aligned with our engineering standards and our customer focus Participate in hands-on work: Code reviews, design reviews and some coding Who You Are: A Software Engineer at heart with a previous experience leading software engineering teams, as a tech lead or people manager Excellent leader with strong interpersonal skills, and the

Datadog's Technical Solutions (TS) organization is one of the largest organizations in the company — spanning Sales Engineers, Technical Account Managers, Enterprise Customer Success Managers, Technical Support Engineers, and Solutions Architects who work with prospects and customers across every stage of their journey with Datadog. Technical Solutions Operations (TSO) exists to make that organization faster, smarter, and more scalable. We build the systems, analytics & programs that give TS teams more leverage — and we measure our success by the business outcomes we drive, not the projects we complete. The programs this team runs touch every function in TS, and the operating model you build will define how that scales. We're looking for a Director of Technical Program Management to lead the TSO Program Management team. This role sits at the intersection of strategy and execution: you'll own the programs that shape how TS operates at scale, lead a team of technical program managers, and serve as a peer to the Directors and VPs who run the teams you support. Your counterparts are leaders overseeing hundreds of customer-facing technical professionals, and your role is to successfully interface with each organization with proactive solutions on how your team can help them be more effective. This is a rare opportunity to lead a function where the output isn't a deliverable, it's organizational capability. If you want to build something that compounds across an entire organization, this is the role. 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 Run the PMO as a business impact function. Own the PMO operating model end-to-end, including intake, prioritization, scoping, execution, and impact measurement — with every program directly linked to measurable bu

Datadog is seeking a strategic, visionary, and results-oriented Senior Director, Growth Marketing – Organic Growth (SEO/GEO/PLG) to lead our organic acquisition strategy across traditional search engines and emerging AI/LLM platforms. This leader will own the vision, strategy, and operating model responsible for driving measurable growth in organic traffic and inbound pipeline through content programs, off-page authority, and AI/LLM discoverability initiatives. In this role, you will lead a team of organic growth specialists, while partnering closely with Website Experience, Product Marketing, and Engineering teams. You will define Datadog's long-term organic growth strategy, establish investment priorities, and ensure the organization is positioned to win across an increasingly complex discovery ecosystem. 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: Own Datadog’s content-led SEO/GEO/PLG strategy, defining the topics, formats, and ecosystems that drive measurable growth in traffic and pipeline Lead, coach, and develop a high-performing team Identify and prioritize high-impact content opportunities across product areas and influence cross-functional teams to bring that content to life Map and optimize Datadog’s presence across the full ecosystem of LLM-ingested content (e.g., YouTube, Reddit, review sites) to improve AI-driven discoverability Design and execute a comprehensive off-page strategy, including link acquisition, digital PR, and authority-building initiatives Partner closely with the Website Experience team, who owns technical SEO, to ensure content is effectively surfaced, indexed, and performant Create and contribute to high-impact content (e.g., flagship pieces, new formats, or experimental channels), setting the standard for qualit

Datadog's integrations are the connective tissue between our platform and the technologies our customers run in the real world. As a Sr. PM on the Agent Integrations team, you will own the vision, prioritization, and execution for 100+ integrations that run directly inside the Datadog Agent from foundational infrastructure (MySQL, Kafka, Kubernetes) to the rapidly growing landscape of self-hosted AI and on-premise enterprise technologies. This is a high-impact, breadth-first role at the intersection of infrastructure observability and the frontier of AI-native workloads. At Datadog, we place value in our office culture; the relationships it builds, the creativity it brings, and the collaboration of being together. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Own the Agent Integrations roadmap. Determine which new integrations to build and which existing ones to improve, balancing customer demand, business impact, and engineering capacity across a catalog of 100+ technologies. Drive the expanding AI integration surface. Lead product strategy for self-hosted AI workloads, including LLM inference frameworks (e.g., Hugging Face TGI, BentoML), AI agents, MCP servers, and model orchestration tools, so Datadog customers can monitor every layer of their AI stack. Expand on-prem and hybrid coverage. Prioritize and execute new integrations for on-prem technologies including storage systems, HPC schedulers, network devices, and legacy enterprise platforms where customers run critical workloads. Build observability for ERP systems. Define and drive Datadog's strategy for monitoring enterprise ERP platforms (SAP, Oracle EBS/Fusion, Microsoft Dynamics) covering performance, job execution health, and integration layer telemetry so enterprise customers can observe their ERP stack alongside the rest of their infrastructure. Analyze adoption and customer feedback at scale. Use data from multiple sources to

Datadog is looking for a Senior Product Manager to help lead the evolution of our fleet and lifecycle management capability, the product surface that gives customers visibility into, and control over, the observability software running across their infrastructure. This capability manages the deployment lifecycle for core observability agents and OpenTelemetry collectors running on customer hosts and containers. The Senior PM will expand the scope of fleet capability to additional Datadog software components, making it the single place customers go to see everything running in their environment, at any version, in any deployment model, and to manage it remotely and safely at scale, for both human operators and, increasingly, AI agents acting on their behalf. This is a high-visibility, cross-functional role. You'll partner with multiple engineering teams and be responsible for defining and delivering a coherent, unified fleet experience across UI, API, and MCP for customers. 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 Own and evolve the product vision and roadmap for a unified fleet and lifecycle management capability spanning multiple product lines and deployment models. Define what "managed" means for each new software component as it's brought into fleet, balancing consistency of experience with the realities of each component's operational model. Drive a phased expansion plan, sequencing new components into fleet based on customer value, technical complexity, and dependency readiness. Partner closely with engineering leads across several teams to align on shared architecture principles to support disparate software components. Represent the voice of the customer for a capability that must work equally well for human operators using a UI and for AI

Come join the Server Ingress Security team, where we are rearchitecting MongoDB Server’s ingress networking to make MongoDB clusters even more secure. This new team is building the Atlas Network Protection layer, a set of performant, security-critical services that harden MongoDB's pre-authentication attack surface and provides the ability to respond rapidly to emergent threats. We are looking for talented Staff Engineers to join the team and be founding members, where you will play a crucial role in our multi-year roadmap. Our team champions a strong culture of inclusivity, diversity, and collaboration. If you want to be a key technical leader on a collaborative team that applies security and systems engineering fundamentals to protect a popular database at scale, join us! We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model. Candidate Profile 10+ years of experience building production-quality systems software with a large user base, robust design structure, and rigorous code quality Experience with large backend/compiled codebases and performance-sensitive software, preferably in Rust Bonus points for experience working hands-on in security-sensitive or networking-adjacent domains Strong systems fundamentals, including multi-threaded programming and performance profiling. Bonus points for: Understanding of network protocols, TLS, and connection lifecycle management. Familiarity with security concepts such as attack surface reduction, input validation, memory safety, and defense-in-depth architectures. Excellent verbal and written technical communication skills for communicating to a wide variety of audiences ranging from junior engineers to executive stakeholder Strong mentorship skills, and excitement about leveling up your peers and teammates through coaching, feedback, and enablement Strong time management skills and the ability to realistically assess project complexity B.Sc. in Computer Science or a related

The data management software market is transforming how organisations build and run applications. MongoDB is the leading developer data platform and the first database provider to IPO in more than 20 years. Join us at the forefront of data and application development. MongoDB Technical Services Engineers combine deep technical expertise with exceptional problem-solving and customer-service skills. You’ll advise customers and resolve complex challenges across MongoDB Core, drivers, Atlas, Cloud Manager, cloud platforms, and infrastructure. We’re looking for candidates based in Dublin to join our vibrant office and collaborative in-office team. This is a five-day role with one of the following schedules: Tuesday–Saturday, Sunday–Thursday, or a five-day pattern covering both Saturday and Sunday. Under our hybrid model, employees on weekend schedules are expected to work from the office two days per week. Cool things you’ll do You’ll help customers troubleshoot complex issues and run critical MongoDB workloads with confidence. You’ll: Solve customer challenges across architecture, performance, recovery, and security Lead investigations from diagnosis to resolution, providing clear, actionable guidance Partner with Product Management and Engineering to advocate for customers and improve MongoDB Build tools, documentation, and training while mentoring peers and raising technical excellence What you need We value curiosity, adaptability, strong technical foundations, and a genuine desire to help customers. You should bring many of the following: 5–6 years of experience in technical support, systems engineering, database administration, SRE, or a related field Experience running complex, mission-critical production database systems Strong Linux and systems engineering skills, including performance, memory, I/O, storage, networking, security, clustering, and troubleshooting A solid understanding of networking concepts and protocols, including DNS, TCP/IP, and SSL/TLS Ability

We are seeking a highly skilled Staff IT Product Manager for Internal AI to drive the strategy, delivery, and adoption of AI-powered solutions across our enterprise IT landscape. This role will be pivotal in shaping how AI transforms our internal operations, from service delivery and knowledge management to automation and decision support. The ideal candidate has a proven track record of managing enterprise-scale AI/ML products, collaborating across IT and business functions, and delivering measurable impact. We are looking to speak to candidates who are based in San Francisco, CA or Palo Alto, CA for our hybrid working model. Key Responsibilities AI Product Strategy & Roadmap Define and execute the internal AI product strategy aligned with enterprise IT and business goals Own multiple product lines in the internal AI product space Prioritize high-value use cases across IT functions (helpdesk, infrastructure, security, applications, enterprise data) Balance quick wins (AI copilots) with longer-term bold initiatives (AI-driven automation and decision-making) Experience in implementing AI solutions for enterprises our size and scale. This should include enabling agentic platforms for organizations and bringing to the table the best practices, pitfalls and learnings from such experiences Product Management Execution Embrace the product mindset and own the lifecycle of AI products—from ideation, critical user journey definition, requirements gathering, vendor evaluation, prototyping, and implementation to scaling in production Define and manage product backlogs, roadmaps, and success metrics Drive adoption and ensure AI solutions are delivering measurable outcomes (efficiency, cost savings, user experience) Stakeholder Engagement Partner with IT leaders (Applications, Infrastructure, Security, Service Desk) to identify pain points and AI opportunities Collaborate with business stakeholders to ensure alignment and secure sponsorship for AI initiatives Communica

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

About the team Our Technical Services (TS) team members use their exceptional problem solving and customer service skills in conjunction with their deep technical experience to advise customers and to solve their complex MongoDB problems. The Curriculum Engineer will work closely with this team and the rest of the TS Enablement program in order to create and maintain technical education modules for both new and upskilling team members to perform their support tasks at the highest levels. Responsibilities include designing,creating and delivering interactive internal training modules in cooperation with technical leaders and subject matter experts. We are looking to speak to candidates who are based in Vancouver for our hybrid working model. Responsibilities Develop, maintain, and continually improve internal training materials (videos, slides, reference materials, evaluations, etc.) Identify technical and procedural training needs across the team Help foster a culture of continual learning, skill sharing through live training, coaching and mentoring Build out the training curriculum, module hierarchy and training policies Foster subject-matter expert contributions to the creation and review of technical content Establish and report on training KPIs and success metrics Create environments and technical exercises for hands-on engineering workshops Improve practices and tooling related to the training content lifecycle Evaluate and recommend the most effective delivery methods for training Suggest the appropriate cadence to keep key skills fresh as well as supporting new product and feature readiness across the organization Work with a globally distributed team across multiple time zones Requirements Experience developing and delivering technical education/training Experience consolidating and presenting technical concepts from subject-matter experts Familiarity with course development methodologies Proven success in creating, delivering and man

The Data Engineering team is responsible for building ETL pipelines that populate the Internal Data Platform, which drives analytics that help the company run more efficiently. Our team builds highly performant and scalable processes that extract massive datasets and makes those datasets available for querying in an optimal way. We are looking to speak to candidates who are based in Gurgaon for our hybrid working model. What you’ll do Guide the Data Engineering team on building highly performance ETL pipelines using Spark and other Big Data technologies Help design the architecture of our Internal Data Platform to support the implementation of a robust medallion architecture Provide thought leadership on ways to achieve infrastructure cost savings on Cloud hyperscalers Design and build AI agents that can help automate many of the common development and support tasks that the team performs Work with Security and Compliance teams to ensure that datasets have appropriate permissions and regulations in place Work with our Data Platform, and Governance sibling teams to make data scalable, consumable, and discoverable We’re looking for someone with 10+ years experience working on enterprise data lakes/warehouses 5+ years of Spark and Python experience 5+ years of direct hands-on experience working with AWS or GCP Thorough AI knowledge, particularly with codegen tools and agentic frameworks Hive, Iceberg, Glue, or other technologies that expose big data as tables Familiarity with different big data file types such as Parquet, Avro, and JSON Exposure to real-time or streaming data technologies is a plus Success Measures In 3 months, you'll have a thorough understanding of the architecture of MongoDB’s internal Data and AI ecosystem In 6 months, you'll have owned the delivery of a large project from start (scoping, design) to finish (delivery) In 12 months, you'll have designed new features, led development work, and become a go-to expert on parts of the system About MongoDB

MongoDB Technical Services Engineers use their exceptional problem solving and customer service skills, along with their deep technical experience, to advise customers and to solve their complex MongoDB problems. Technical Service Engineers are experts in the entire MongoDB ecosystem - database server, drivers, cloud and infrastructure. This also includes services such as Atlas (database as a service), or Cloud Manager (which helps customers with automation, backup and monitoring of their MongoDB systems). Our engineers combine their MongoDB expertise with passion, initiative, teamwork and a great sense of humor to achieve exceptional results for our customers. We are looking to speak to candidates who are based in Mexico City for our hybrid working model. Cool things you’ll do MongoDB is on a mission to change the way people think about databases. Along the way, our customers encounter questions and issues about how our approach to databases works for their use case. In Technical Services, it's our job to help these people. You'll be working alongside our largest customers, solving their complex issues - resolving questions on architecture, performance, recovery, security, and everything in between. You'll be an expert resource on standard methodologies in running MongoDB at scale, whatever that scale may be. You'll be an advocate for customers' needs - working with our product management and development teams on their behalf. And you'll contribute to internal projects, including software development of support tools for performance, benchmarking, and diagnostics. In addition, you will also be responsible for mentoring and ramping new team members and taking initiatives in building knowledge of new product lines within the MongoDB ecosystem. What you need We consider all candidates with an eye for those who are self taught, insatiably curious, and multi-faceted. It’s important for candidates to check off these boxes: Systems engineering experience, including Linux

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

We’re hiring a Senior Technical Product Marketing Manager to lead positioning, messaging, and product adoption across our AI and agentic context solutions. This is a high-impact role for a technical marketer who thinks and acts like a builder. Most AI systems don't fail because the model is bad—they fail because they lack a crucial, contextual foundation. MongoDB owns a piece of nearly every step in that chain. This role requires deep technical expertise across the context stack—including VoyageAI embedding and reranking models, MCP Server, and the coding agent ecosystem (Claude Code, Cursor, GitHub Copilot, Gemini CLI, Codex, etc.)—combined with product marketing instincts to deeply understand the market and translate technical depth into crisp, differentiated messaging for distinct user and buyer personas. The ideal candidate has experience building and shipping AI-enabled products and using developer tools in their day-to-day workflows. Individuals with prior experience in technical sales, developer relations, or software development are encouraged to apply. The ideal candidate is a voracious consumer of AI research and pays close attention to shifting patterns in how software and AI applications are built and consumed. This individual is confident in communicating with technical practitioners and non-technical decision makers in one-to-few and one-to-many engagements for internal and external audiences. You will leverage your technical depth to craft clear, compelling, and highly differentiated messaging by working backward from customer requirements. We are looking to speak to candidates who are based in Dublin for our hybrid working model. What You’ll Do Drive Strategy & Execution: Act as the strategic owner for MongoDB’s context engineering portfolio—MCP Server, Agent Skills, VoyageAI, and more— aligning roadmap and go-to-market with MongoDB’s long-term business goals, in collaboration with Product Management, Engineering, Developer Relations, Partn

As a Staff Technical Program Manager, you will partner with key Engineering, Product, Product Design, Marketing, and Analytics stakeholders to deliver Observability features and platform capabilities for MongoDB. As a seasoned program leader, you will be responsible for one of our most mission-critical programs this fiscal year, and own executive level communication related to the program. We are looking to speak to candidates who are based in Dublin for our hybrid working model. The right candidate for this role will be: Experienced with 10+ years of working in an engineering organization leading complex cross-functional technical programs Experienced with 5 years of Software development background, with Cloud storage and compute products Experience with Service Oriented Architecture and Cloud Infrastructure Able to leverage their knowledge and experience to influence technical discussions, summarizing outcomes and next steps Skilled at communicating across a diverse set of engineers and stakeholders Hyper-organized and capable of coordinating across multiple independent work streams and organizations A role model for effective execution practices, driven by an attuned sense of priority and urgency Able to leverage their experience in program delivery to influence improvements to our tools, operations, and architecture Trained in working with project tracking software (e.g. Jira, Rally, MS Project) Familiar with MongoDB or a comparable technology Interested in business automation work such as scripting in Python, Google Apps Script and Slack. Position Expectations: Leverage technical acumen and analytical skills to drive engineering programs forward and maximize business value delivery Recognize patterns in a sea of information and take action accordingly Design, maintain, and improve the processes and tools that power program delivery Build strategic partnerships with Product and Engineering stakeholders Expand knowledge into new domains as called upon Act as a me