Production Cleaning Specialist Jobs

As organizations rapidly adopt AI applications and agentic systems, security teams need visibility and control over how these technologies are being used. Datadog's AI & Data Security product helps customers discover, secure, and govern AI usage across their environments ensuring sensitive data is properly managed from model training through production. As a Product Manager II for AI & Data Security, you will own capabilities for AI discovery, posture management, and data security; giving customers complete visibility into their AI applications, agents, and enabling ecosystem, with prioritized actions to operate AI systems securely. You'll partner with engineering, design, security research, and GTM teams to define and ship platform capabilities that help organizations adopt AI at scale. 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 the roadmap for AI & Data Security capabilities, including AI and data discovery & posture management. Define how security teams can assess and manage the security posture of AI-enabled systems, including configuration risks, sensitive data exposure, and policy violations. Work closely with engineers and designers to deliver new product capabilities end-to-end, from early concept through launch and iteration. Partner with Datadog security researchers to identify emerging risks in AI systems and translate them into actionable product features. Engage with customers to understand how they are adopting AI and validate solutions that help them operate these systems securely. Collaborate with go-to-market teams to enable adoption and communicate the value of AI security capabilities to customers. Who You Are: You have 3+ years of product management experience building technical products, ideally in security,

As organizations rapidly adopt AI applications and agentic systems, security teams need visibility and control over how these technologies are being used. Datadog's AI & Data Security product helps customers discover, secure, and govern AI usage across their environments ensuring sensitive data is properly managed from model training through production. As a Product Manager II for AI & Data Security, you will own capabilities for AI discovery, posture management, and data security; giving customers complete visibility into their AI applications, agents, and enabling ecosystem, with prioritized actions to operate AI systems securely. You'll partner with engineering, design, security research, and GTM teams to define and ship platform capabilities that help organizations adopt AI at scale. 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 the roadmap for AI & Data Security capabilities, including AI and data discovery & posture management. Define how security teams can assess and manage the security posture of AI-enabled systems, including configuration risks, sensitive data exposure, and policy violations. Work closely with engineers and designers to deliver new product capabilities end-to-end, from early concept through launch and iteration. Partner with Datadog security researchers to identify emerging risks in AI systems and translate them into actionable product features. Engage with customers to understand how they are adopting AI and validate solutions that help them operate these systems securely. Collaborate with go-to-market teams to enable adoption and communicate the value of AI security capabilities to customers. Who You Are: You have 3+ years of product management experience building technical products, ideally in security,

As a Network Engineer II on the Office Technology team, you will implement and support office network solutions across Datadog’s global offices. You will own well-scoped deployment and upgrade work, troubleshoot connectivity issues across LAN, WAN, and Wi-Fi, and partner with senior engineers on larger designs and cross-office initiatives. You will collaborate closely with vendors, Facilities, AV, IT Support, Security, and Infrastructure teams to keep Datadog offices connected, reliable, and observable. This is an IC2 role with a mix of project work and day-to-day operations. You will take ownership of clearly defined areas of the office network stack, execute production changes with care, and grow your ability to design, automate, and improve office network services with support from senior engineers. You will also use AI-assisted tools responsibly to improve troubleshooting, documentation, automation, knowledge discovery, and operational follow-through. 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: Deploy and configure network solutions for new and existing offices, including switches, wireless access points, routers, and firewalls Own scoped portions of office rollouts and upgrade projects, from planning through execution and validation Partner with ISPs, cabling providers, hardware vendors, and internal teams to turn up new services and resolve issues Troubleshoot LAN, WAN, and Wi-Fi issues using structured debugging methods, packet capture, logs, and performance data Manage routing, VLAN, firewall, and wireless configurations following team standards and change-management processes Contribute to repeatable deployment patterns through templates, documentation, scripting, or infrastructure-as-code Monitor office netwo

As the Senior Product Manager for the Actions & Automations team, you will own the ecosystem that enables customers, partners, and Datadog teams to build, deploy, and operate AI agents on Datadog. You will drive the strategy and execution for the platform capabilities, developer experience, integrations, and extensibility model that make Datadog the best place to build agents that understand and act on production systems. Modern engineering organizations are entering a new era where software is not only monitored and operated by humans, but increasingly by AI-powered agents. As agentic workflows reshape how teams build, operate, secure, and troubleshoot systems, customers need a platform for creating specialized agents, connecting them to business and engineering systems, governing their behavior, and extending them to solve unique organizational problems. You will define and build the ecosystem that makes this possible. Agent Builder sits at the intersection of Datadog's products, AI capabilities, and ecosystem strategy. You will have the opportunity to work across the breadth of the Datadog platform, partner with teams throughout the company, and help establish Datadog as the foundation for operational AI. 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: Define the vision, strategy, and roadmap for Datadog's Agent Builder platform and ecosystem. Own the core platform capabilities that enable customers and partners to create, customize, deploy, and manage AI agents. Drive the extensibility model for agents, including integrations, tools, actions, context sources, APIs, SDKs, and developer workflows. Shape how agents perform actions across Datadog products and third-party systems. Partner closely with AI, platform, infrastructure, and product tea

As a Senior Product Manager for AI & Data Security at Datadog, you will define and deliver capabilities that help organizations securely adopt and scale AI across their applications and infrastructure. You’ll focus on building products that provide visibility into AI systems and data usage, assess security posture, and enable teams to manage risk across the AI lifecycle. This role sits at the intersection of security, AI, and cloud platforms, and is ideal for a PM who thrives in emerging, ambiguous problem spaces. You will work cross-functionally to shape how customers discover, understand, and secure AI-powered systems in production. 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 drive the roadmap for AI & Data Security capabilities, including data security posture management and data loss prevention Define how customers assess and manage the security posture of AI systems, including risks related to configuration, data exposure, and policy compliance Partner with engineering and design to deliver end-to-end product capabilities, from concept through launch and iteration Collaborate with security research teams to identify emerging risks in AI systems and translate them into actionable product features Engage with customers to understand AI adoption patterns and validate solutions that enable secure, scalable operations Define and track success metrics such as product adoption, usage, and impact on customer security workflows Who You Are: &l

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

MongoDB is hiring a Staff Product Marketing Manager to build and own our go-to-market narrative for the Public Sector vertical, with a focus on Federal Government and the broader public sector market. This is a foundational hire for MongoDB’s Industry Verticals product marketing function: you will define how MongoDB’s unified data platform, spanning cloud, on-premises, and hybrid database deployments with integrated, production-ready AI capabilities, shows up for government buyers. You’ll turn a major compliance milestone into a durable competitive differentiator: developing the positioning, messaging, and sales-ready content that helps government agencies, systems integrators, and cloud/public-sector resellers understand why MongoDB is the right data platform for mission-critical, regulated workloads. You do not need prior government or public-sector work experience to succeed in this role — you need to be an excellent product marketer who can get fluent in a new domain quickly and partner closely with the compliance, product, and sales experts who already are. This role can be based in one of our MongoDB hub offices in the U.S. or remotely in the U.S. What you’ll do Own positioning and messaging for MongoDB’s Public Sector go-to-market, leading the federal GTM and launch related activities Translate MongoDB’s data platform capabilities — document database, search, vector search, stream processing, and integrated AI — into mission-relevant outcomes and value propositions for government buyers and the systems integrators who serve them Partner with Compliance, Security, Industry Solutions and Product teams to accurately represent related certification requirements in external-facing content, staying current as MongoDB pursues additional authorizations (e.g., DoD Impact Levels) Build the public sector sales enablement toolkit: battlecards, pitch decks, discovery guides, ROI/value models, and competitive intelligence tailored to federal buying processes and procuremen

As Engineering Manager for Threat Detection, you will lead a high-performing team that powers Datadog's detection program. Threat Detection is the organization responsible for keeping Datadog ahead of an evolving threat environment: closing coverage gaps faster, raising the bar on signal quality, and shipping detections that hold up under the scale and complexity of cloud-native infrastructure. Your team will combine direct detection expertise, platform engineering, and applied AI to ship detections at a pace and scale traditional rule-writing alone cannot match. Examples of what your team will work on include detection-authoring agents, the detection platform that powers every rule in production, coverage analysis, alert triage and response automation, and the evaluation infrastructure that holds these systems to a high bar of fidelity. Detection authorship is a shared responsibility across the organization, and your team will contribute both by building the systems that scale our authoring capacity and by writing detections directly when their domain expertise is the right tool. You will partner closely with our Security Incident & Response Team (SIRT), Cyber Threat Intelligence (CTI), AI Engineering teams, and Datadog's broader Security organization. This is a high-impact leadership role: you will grow a team of security and software engineers responsible for building and executing our detection and AI strategy. 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 strategy, roadmap, and execution of Datadog Security's shift to AI-accelerated detection and response. Drive development of high-fidelity detections as a shared responsibility across the organization, ensuring your team's systems and direct contributions raise the bar on coverage and

As a Research Engineer on our team, you will partner with Research Scientists to turn research ideas into working systems, building the data, tooling, and infrastructure that enable rapid iteration, trustworthy evaluation, and a smooth path from prototype to production. 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: Build and operate multimodal data pipelines, training and evaluation infrastructure, benchmarks, and internal tooling Implement models, run experiments at scale, and profile for reliability, performance, and cost Build simulation environments and replay infrastructure for agent training and evaluation Orchestrate distributed training and distributed RL with Ray, including scheduling, scaling, and failure recovery Establish rigorous automated benchmarks and regression tests for world model predictions, agent performance, and simulation fidelity Collaborate with Research Scientists, Product, and Engineeri

Staff Forward Deployed Engineers (FDE) sit at the intersection of enterprise customer environments and a fast-moving internal product. They are senior technical leaders who own ambiguous, high-impact problems that span customer engagements, product direction, and engineering execution. They are accountable not only for getting customers to production, but for using what is learned in the field to shape reusable product capabilities, technical strategy, and delivery quality across multiple teams. This role is best suited for engineers who want to combine hands-on technical depth with broad influence: defining or changing strategy when customer reality reveals a gap, guiding technical decisions across teams, and translating field insight into durable product and engineering improvements. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Responsibilities Customer and business impact Own the most complex customer engagements and technical workstreams, especially where the problem, solution, or path to production is ambiguous Build deep understanding of customer architecture, business goals, constraints, and definition of success, and use that understanding to shape the technical approach rather than only execute within a predefined one Act as a trusted technical counterpart to customer’s engineering leaders, internal product and engineering leaders, and executive stakeholders when navigating complex tradeoffs, risks, and priorities Technical leadership and execution Lead architectural design for customer-facing solutions and platform capabilities within the FDE domain, balancing hands-on implementation with technical decision-making across multiple teams Take ambiguous, high-level problems and turn them into clear technical direction, implementation plans, milestones, and ownership boundaries that enable execution at quality and speed Continue to write and review production-quality code, troubleshoot complex failures, and set

Staff Forward Deployed Engineers (FDE) sit at the intersection of enterprise customer environments and a fast-moving internal product. They are senior technical leaders who own ambiguous, high-impact problems that span customer engagements, product direction, and engineering execution. They are accountable not only for getting customers to production, but for using what is learned in the field to shape reusable product capabilities, technical strategy, and delivery quality across multiple teams. This role is best suited for engineers who want to combine hands-on technical depth with broad influence: defining or changing strategy when customer reality reveals a gap, guiding technical decisions across teams, and translating field insight into durable product and engineering improvements. We are looking to speak to candidates who are based in New York City, NY for our hybrid working model. Responsibilities Customer and business impact Own the most complex customer engagements and technical workstreams, especially where the problem, solution, or path to production is ambiguous Build deep understanding of customer architecture, business goals, constraints, and definition of success, and use that understanding to shape the technical approach rather than only execute within a predefined one Act as a trusted technical counterpart to customer’s engineering leaders, internal product and engineering leaders, and executive stakeholders when navigating complex tradeoffs, risks, and priorities Technical leadership and execution Lead architectural design for customer-facing solutions and platform capabilities within the FDE domain, balancing hands-on implementation with technical decision-making across multiple t

Platform Engineering is the department within SRE that is responsible for a range of critical infrastructure and operational functions that support the broader engineering organization. Among these are our multi-cloud-provider Kubernetes infrastructure, networking, load balancing (including our public-facing edge and internal service mesh), and observability and alerting systems. The Deployments team designs and maintains our continuous delivery infrastructure, ensuring reliable code deployment from development through production for all engineering teams. This infrastructure is primarily composed of Argo Workflows and ArgoCD. The team also provides tooling that enables clear system ownership and facilitates self-service onboarding for development teams. We are looking to speak to candidates who can work East Coast hours. The ideal candidate should Have 6+ years of experience in software development and operating distributed systems Proficiency in Python, Go, or a similar language Proven experience building and operating large-scale continuous integration and continuous deployment (CI/CD) pipelines Possess a customer-focused mindset Value efficiency in processes and operations Prefer automation over manual process (“allergic to ops work”). We are a small team of software engineers with a strong bias towards software solutions to avoid toil Experience using and extending containerization technologies, particularly Kubernetes, to enhance application agility, optimize resource utilization, and accelerate time-to-market Expertise in cloud infrastructure platforms, including AWS, Google Cloud Platform (GCP), or Azure Understanding of Linux operating system internals and networking concepts (e.g., TCP/IP, DNS, TLS, routing) Expectations Contribute to developing a world-class continuous deployment experience, enabling the rapid and reliable shipment of MongoDB products This includes, but is not limited to, contributing to open-source projects, or engineering software-based

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 Senior 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 work 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 5+ years of experience building production-quality systems software 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, with a strong desire to collaborate with colleagues Strong time management skills and the ability to realistically assess project complexity B.Sc. in Computer Science or a related field, or equivalent practical experience, with strong competencies in data structures, algorithms, and software design/architecture. Interest in the theory and practice of high-availability, security-critical systems Position Expectations Design, implement, and operate production

Platform Engineering is the department within SRE that is responsible for a range of critical infrastructure and operational functions that support the broader engineering organization. Among these are our multi-cloud-provider Kubernetes infrastructure, networking, load balancing (including our public-facing edge and internal service mesh), and observability and alerting systems. The Deployments team designs and maintains our continuous delivery infrastructure, ensuring reliable code deployment from development through production for all engineering teams. This infrastructure is primarily composed of Argo Workflows and ArgoCD. The team also provides tooling that enables clear system ownership and facilitates self-service onboarding for development teams. We are looking to speak to candidates who can work East Coast hours. The ideal candidate should Have 6+ years of experience in software development and operating distributed systems Proficiency in Python, Go, or a similar language Proven experience building and operating large-scale continuous integration and continuous deployment (CI/CD) pipelines Possess a customer-focused mindset Value efficiency in processes and operations Prefer automation over manual process (“allergic to ops work”). We are a small team of software engineers with a strong bias towards software solutions to avoid toil Experience using and extending containerization technologies, particularly Kubernetes, to enhance application agility, optimize resource utilization, and accelerate time-to-market Expertise in cloud infrastructure platforms, including AWS, Google Cloud Platform (GCP), or Azure Understanding of Linux operating system internals and networking concepts (e.g., TCP/IP, DNS, TLS, routing) Expectations Contribute to developing a world-class continuous deployment experience, enabling the rapid and reliable shipment of MongoDB products This includes, but is not limited to, contributing to open-source projects, or engineering software-based

MongoDB’s Replication Team builds the infrastructure that enables high availability, fault tolerance, automatic failover, and tunable consistency. As an engineer on the team, you will design and implement distributed-systems features that protect data and keep applications available under demanding operating conditions. You will work primarily in C++ on core database code, partner with engineers across MongoDB, and help shape features that are central to major MongoDB releases. This is an opportunity to apply distributed-systems fundamentals to a widely used database while solving challenging problems in correctness, performance, and operability. We're looking to speak with candidates based in New York City for our in-office working model. What you will do Design and implement replication features based on the Raft consensus protocol Improve failover behavior, availability, correctness, and performance across the replication system Write production-quality C++ and the unit, integration, and system tests needed to demonstrate correctness Use JavaScript and Python where appropriate to extend test coverage and validate end-to-end behavior Diagnose test failures, investigate bugs, and drive issues through root-cause analysis and resolution Measure the performance impact of code changes and prevent or resolve regressions Collaborate with partner engineering teams and stakeholders on large, cross-functional initiatives Investigate distributed-systems issues raised by customers and Technical Support, communicate findings clearly, and help deliver durable fixes Participate in code reviews, design reviews, and technical discussions that improve the quality of the team’s work Interview candidates and mentor junior engineers and interns What you bring Required At least five years of experience programming, debugging, and performance-tuning distributed or highly concurrent software systems Strong systems fundamentals, including multithreaded programming, concurrency, debugging,