Infrastructure Team Manager Jobs

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Security Engineering is the engineering function inside the Plaid security org that focuses on developing the industry-leading security systems and infrastructure. Security Engineering owns most of Plaid’s security-related infrastructure: secure data storage, key management systems, internal identity platform, internal authentication systems, internal permission management, and internal authorization service. We develop solutions across data encryption, key management, access control, and data loss prevention to protect sensitive consumer data. We believe in the Zero Trust security model and are always looking for ways to improve our authentication and access control platforms. About the role You will develop security capabilities to secure Plaid infrastructure and to secure sensitive data access. You will own, maintain, and build Plaid’s security infrastructure and services like Key Management System and Secure Token Service. You will consult with product engineers to ensure Plaid services meet security standards. You will help educate and support other engineering teams to improve security in their own products and services. You will assist with Plaid’s incident response and security awareness pro

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 Are you passionate about engineering quality, efficiency, and increasing the impact of engineers around you? Software Engineers at Palantir build software that transforms how the world’s most important organizations use data. As an engineer focused on Frontend Developer Productivity, you’ll work within our Frontend Infrastructure group to identify, develop, and drive investments to improve the velocity and quality of our engineering. Our frontend infrastructure group covers our entire frontend development stack, from the developer experience in the IDE to the final user experience in the browser. Across the group, we are responsible for developing and maintaining: • The build and CI system for a large frontend monorepo with millions of lines of code and hundreds of active developers. • Core infrastructure required to develop and serve our frontends, including feature flags, internationalization, and commit previews. • A GraphQL API for declarative data loading, spanning many underlying services. • Blueprint, the open source UI framework used by all of Palantir's applications and thousands of developers around the world. • A variety of tools and VSCode extensions that improve developer experience across the company. With an ambitious roadmap ahead of us, you'll have the opportunity to make a lasting difference on application development at Palantir.

About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About the role At Mixpanel, we believe design excellence is a competitive moat. In a world where AI makes it easier than ever to ship, we believe the quality of the experience — how it feels, how it builds trust, how it handles complexity with grace — that separates good products from great ones. As a Staff Design Engineer at Mixpanel, you'll sit within the design organization and lead the transformation of our design system from a component library into something far more important: the infrastructure that powers how we design, build, and ship in an AI-native world. You'll encode our craft, standards, and vision directly into the systems, tools, and workflows that every designer, engineer, and AI agent in our org builds on. This isn't a maintenance or systems stewardship role. It's a transformative one. You'll work at the frontier of what design and engineering collaboration looks like when AI writes most of the code, agents prototype from intent, and the design system is less a library and more a living foundation for everything we ship. You'll be the designer who ships production code. The engineer who holds an uncompromising craft bar. The person who sees the future of how Mixpanel will look and behave in an AI-native world, and builds the infrastructure to make it real. What you'll do Build the infrastructure for an AI-native design practice Translate Mixpanel's design standards, principles, and taste into systems that live in the code. Build a token system, component library, documentation, and guidelines that AI agents, AI coding tools, and AI prototyping workflows can reliably build on. Evolve ou

Most PMs write specs and wait for feedback. You'll be deploying AI agents with real customers across APAC, then turning what you learn into product direction that actually matters. The Company Sendbird is on a mission to build the AI workforce of tomorrow. For over a decade, we built the infrastructure behind conversations—chat, voice, video, messaging APIs—and became the #1 CPaaS platform for in-app communications. 4,000+ brands trust us. 7 billion messages flow through our platform every month. 300 million monthly active users. We powered conversations for DoorDash, Match Group, Noom, Yahoo Sports, Rakuten, and thousands of others. We were good at what we did. Really good. We also saw it early: AI would fundamentally reshape how businesses talk to customers. The infrastructure we'd spent a decade building would become commoditized. The value would move up the stack—into intelligence, into experience, into outcomes. We had a choice: protect what we built, or reinvent ourselves. We chose reinvention. In December 2024, we made the full strategic pivot to AI-first customer experience. By February 2025, we'd launched our AI agent for enterprise CX—built on a decade of conversation data, now with intelligence on top. And in November 2025, we rebranded to delight.ai. The name says it all. AI's real promise isn't efficiency or cost savings. It's giving customers back something they lost—the feeling of being truly understood and cared for. Not satisfied. Delighted. The Product Delight.ai is the AI concierge for customer experience. Most AI agents forget you the moment the conversation ends. Ours doesn't. Delight.ai builds memory over time, learns preferences, and connects context across every channel—chat, SMS, email, voice, WhatsApp—without losing the thread. We're building AI that makes customers feel understood, seen, and remembered. Why Forward Deployed Product Manager Enterprise AI isn't won in the roadmap, it's won in the field. Businesses across APAC are trying to f

Sendbird is building AI agents for customer experience. Our platform already powers billions of conversations every month across chat, voice, video, and messaging APIs. We are now using that foundation to build agents that understand customer context, reason over business data, and take reliable action in production. We are looking for a Machine Learning Engineer to research, build, and productionize new capabilities for those agents. This role sits at the intersection of agent product development, applied AI research, and production engineering. You will work on systems that enterprise customers depend on every day, not demos or isolated prototypes. About Sendbird and delight.ai Sendbird has spent more than a decade building communication infrastructure for in-app chat, voice, video, and messaging APIs. More than 4,000 brands use our platform, including DoorDash, Match Group, Noom, Yahoo Sports, and Rakuten. Our systems support more than 7 billion messages every month. In 2024, we made a strategic shift toward AI-first customer experience. In 2025, we launched our enterprise AI agent product, delight.ai. Delight.ai helps businesses deliver customer support and engagement that is faster, more contextual, and more personal. Unlike simple FAQ bots, our agents are built to remember customer context, use tools, retrieve relevant knowledge, connect across channels, and handle real customer workflows with accuracy and control. The Role As a Machine Learning Engineer, you will design, build, evaluate, and ship new capabilities for our AI agents. You will work across agent architecture, retrieval, memory, planning, tool use, workflow automation, voice, evaluation, data pipelines, model adaptation, inference, and production integration. This is a hands-on engineering role for someone who can turn AI research and product ideas into reliable customer-facing features. Some problems will require training, fine-tuning, or adapting models. Others will require better retrieval, bet

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. Smartsheet is hiring a Senior Machine Learning Operations Engineer to architect our machine learning production lifecycle. Your mission is to maintain and deploy ML models to a scalable, reliable, and secure production environment. You will design and maintain the infrastructure, automation, and monitoring systems that ensure our AI products are high-performing and cost-effective. You will report to our Director, Analytics Engineering & Data Governance and work from our Bangalore, India office. You Will: Model and Pipeline Automation Automate the deployment and retraining of ML models, from training through to production inference, by building and managing complete CI/CD/CT (Continuous Training) pipelines, adhering to MLOps best practices. Build, fine-tune, or use pre-trained LLMs, deep learning models or traditional machine learning models. Evaluate and recommend AI or ML solutions for the product using any combination of vendor solutions and/or custom-built models. Governance & Compliance Implement model versioning, lineage tracking, and auditing to ensure compliance with security and ethical standards. Performance Monitoring Continuously monitor the health and performance of production machine learning models, proactively identifying and correcting model drift, staleness, and performance degradation. Incorporate user feedback for iterative improvements and manage necessary model retraining cycles. Cross-Functional Collaboration Act as the "glue" between Data Scientists (who build models

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. Job Description/ Responsibilities: Designing, developing and maintaining stable and reliable AI/ML Ops platforms / pipelines Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time. Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production. Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow. Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data Technology Eva

Security at most companies is reactive. A checkbox for auditors. A speed bump for engineers. A department that says no. That's not what we're building. The Company Sendbird is the #1 CPaaS platform for in-app communications — an enterprise-grade infrastructure company that gives businesses the APIs and SDKs to embed real-time chat, voice, and video directly into their own products. Over 4,000 brands trust us. Seven billion messages flow through our platform every month. 300 million monthly active users. We powered conversations for DoorDash, Match Group, Noom, Yahoo Sports, Rakuten, and thousands more. We were good at what we did. Really good. So we asked what comes next. With decades of leadership in communications infrastructure, the answer was clear: AI. In February 2025, we launched our AI agent for enterprise CX. Later that year, we introduced Delight.ai — and the name says everything about what we believe. AI's real promise isn't efficiency. It isn't cost savings. It's restoring what customer experience lost somewhere along the way: the feeling of being understood, of being genuinely cared for. We don't want customers to feel satisfied. We want them to feel delighted. The Product Delight.ai is the AI concierge for customer experience. Most AI agents forget you the moment the conversation ends. Ours doesn't. Delight.ai builds memory over time, learns preferences, and connects context across every channel—chat, SMS, email, voice, WhatsApp—without losing the thread. We're building AI that makes customers feel understood, seen, and remembered. Why Head of IT & Security We're an AI company handling enterprise-grade conversations at global scale, and our customers trust us with data that matters. That trust isn't a nice-to-have. It's a competitive differentiator. It's why DoorDash and Match Group chose us. It's why we've earned certifications that our competitors are still chasing. Security here means being a partner to the business, not a blocker. It mea

Most PMs sit behind a roadmap. You'll be in the room where the AI actually gets deployed, then back at HQ making sure what you learned changes the product. The Company Sendbird is on a mission to build the AI workforce of tomorrow. For over a decade, we built the infrastructure behind conversations, chat, voice, video, messaging APIs, and became the #1 CPaaS platform for in-app communications. 4,000+ brands trust us. 7 billion messages flow through our platform every month. 300 million monthly active users. We powered conversations for DoorDash, Match Group, Noom, Yahoo Sports, Rakuten, and thousands of others. We were good at what we did. Really good. We also saw it early: AI would fundamentally reshape how businesses talk to customers. The infrastructure we'd spent a decade building would become commoditized. The value would move up the stack, into intelligence, into experience, into outcomes. We had a choice: protect what we built, or reinvent ourselves. We chose reinvention. In December 2024, we made the full strategic pivot to AI-first customer experience. By February 2025, we'd launched our AI agent for enterprise CX, built on a decade of conversation data, now with intelligence on top. And in November 2025, we rebranded to Delight.ai. The name says it all. AI's real promise isn't efficiency or cost savings. It's giving customers back something they lost, the feeling of being truly understood and cared for. Not satisfied. Delighted. The Product Delight.ai is the AI concierge for customer experience. Most AI agents forget you the moment the conversation ends. Ours doesn't. Delight.ai builds memory over time, learns preferences, and connects context across every channel, chat, SMS, email, voice, WhatsApp, without losing the thread. We're building AI that makes customers feel understood, seen, and remembered. Why Forward Deployed Product Manager Enterprise AI deployments don't fail because the technology is wrong. They fail because no one bridges th

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The role We are looking for a Staff Cryptography Engineer to help lead SoFi’s enterprise readiness for post-quantum cryptography and long-term cryptographic resilience. This role sits within our Security Assurance organization and will partner closely with security, engineering, infrastructure, product, and business stakeholders to assess, modernize, and strengthen cryptographic controls across the enterprise. This is a highly cross-functional and strategic role. The ideal candidate brings deep applied cryptography expertise, strong engineering and architecture judgment, and the ability to drive complex security initiatives in ambiguous environments. You will help build SoFi’s cryptographic inventory, identify where cryptographic keys, protocols, algorithms, certificates, and libraries are used, and guide teams through the implementation of quantum-resistant and crypto-agile solutions. What you’ll do Lead efforts to assess and improve SoFi’s enterprise cryptographic posture, with a focus on post-quantum cryptography preparedness and crypto-agility. Build and maintain an inventory of cryptographic assets, including keys, certificates, algorithms, protocols, libraries, services, and business-critical systems. Partner with product, engineering, infrastructure, cloud, and security teams to identify cryptographi

We are looking for a Director of Engineering to lead our AI Platform organization. This group builds the foundational systems powering every AI experience across Asana. In this role, you will lead four key teams through their engineering managers: Context (search, retrieval, and knowledge extraction across the Asana Work Graph), LLM Foundations (model serving, inference infrastructure, provider strategy, and evaluation systems), and AI Efficiency (our center of excellence for cost, quality, and performance standards across all AI workloads). Collaborating with engineering managers and senior technical leaders, you will drive the end-to-end strategy, execution, and architecture that define how humans and AI work together at Asana to build trusted, reliable, high-value product workflows for enterprise customers worldwide. Your mission is to make Asana’s AI platform the most reliable, economical, and performant foundation in the industry for agentic enterprise software, giving Asana the leverage to ship AI products faster than anyone else. This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Drive Strategy & Execution Across the AI Teammates Pillar: Lead the multi-year vision and technical strategy for Asana’s AI platform, covering retrieval and agent context, model serving and inference, model portfolio strategy, and evaluation systems. Optimize AI Infrastructure Costs: Own cost-per-execution as a primary engineering metric, managing model selection, routing, open-weight versus frontier trade-offs, inference optimization, caching, and prompt efficiency to protect product margins at scale.

As a Senior Product Manager for Serverless at Datadog, you will define and deliver products that help developers monitor and operate serverless applications at scale. You’ll own the strategy and execution for Datadog’s AWS Serverless observability offering, building experiences that provide visibility into distributed systems and simplify debugging and operations. This role sits at the intersection of cloud infrastructure, developer experience, and AI-powered workflows, and is ideal for a PM who thrives in highly technical product areas. You will work cross-functionally and with external partners to shape how customers build and run modern serverless applications. 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 Datadog’s AWS Serverless observability products, including Lambda, Fargate, and Step Functions Define how developers monitor, debug, and operate serverless systems across distributed environments Partner with engineering and design to deliver end-to-end product capabilities from concept through launch and iteration Collaborate with AWS product teams to align roadmaps and deliver joint solutions for shared customers Engage with customers to understand serverless adoption patterns and validate product direction Define and track success metrics such as adoption, usage, and impact on developer workflows Who You Are: 5+ years of product management experience building technical products in areas such as cloud infrastructure, developer platforms, or observability Strong understanding of distributed systems, cloud-native architectures, and modern application development practices Familiarity with serverless technologies, containers, Kubernetes, or microservices environments Comfortable working closely with engineers and discu

Please note that the job is only available from the locations outlined. We are looking for a Senior Software Engineer to help us take REDAPL, our Referential Data Platform, to the next level. REDAPL is Datadog's main platform for tracking our customers' infrastructure resources and relationships. The platform enables products where customers can understand, keep track of, and gain insights into their infrastructure related to performance, cost, security, and more. Many Datadog products use REDAPL today such Cloud Security Posture Management, Resource Catalog, Cloud Cost Management, and Service Catalog and others - REDAPL ingests more than 4.5mil updates/second. As a Senior Engineer, you will drive, lead and collaborate on projects both inside and outside the platform. You can expect to contribute to key technical decisions relating to our data ingestion, processing, and query pipelines. 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: Build a query engine that supports efficient relationship traversals for our most demanding workloads. Contribute to design and drive high-priority, high-visibility projects to increase the platform's value, resilience, and scalability across multiple teams. Lead and guide other engineers through architectural platform decisions Identify potential system risks and trends in reliability and design solutions to address them Provide input on prioritizing engineering-led initiatives in short- and long-term planning and roadmaps Collaborate with internal product teams to understand their requirements and how we plan for their product growth as they integrate and depend on REDAPL Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent experience You

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

As a Senior Platform Product Manager focused on AI SDLC Trusted Throughput, you will define and drive the product strategy for enabling safe, reliable software delivery at AI-native scale across Datadog’s Internal Developer Platform. As AI accelerates development velocity and system complexity, you will help evolve SDLC systems from human-supervised workflows to platforms with built-in safety, observability, and correctness guarantees. You will partner closely with engineering, security, and developer platform teams to improve deployment reliability, operational visibility, and governance while enabling both engineers and AI agents to move quickly with confidence. This role offers the opportunity to shape foundational developer infrastructure and influence how AI-powered software delivery operates across Datadog. 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 product strategy, roadmap, and execution for AI-native SDLC throughput and reliability initiatives across Datadog’s Internal Developer Platform Define and drive platform outcomes aligned to DORA metrics, balancing deployment velocity with reliability, change failure reduction, and operational safety Partner with engineering, infrastructure, security, and developer experience teams to build automated validation, auditability, and risk-scoring capabilities into deployment workflows Deliver actionable SDLC observability and diagnostic capabilities that connect executive-level metrics to operational signals across the software delivery lifecycle Drive systems that monitor and validate AI-generated or AI-attributed changes to ensure correctness, compliance, and trustworthy automation Serve as a cross-functional product leader across SDLC Foundations, Security Engineering, and compl