Platform Infrastructure Engineer Jobs

We're looking for an Engineering Manager who combines strong technical judgment with people leadership to help build the systems and team practices that keep Asana resilient at scale. This role is a great fit for someone who enjoys turning broad reliability problems into clear priorities, and can balance foundational engineering work with iterative delivery. You'll help shape what Platform Reliability means at Asana while building a team that ships durable systems, strong operational practices, and high-trust partnerships. You will define the reliability roadmap for a rapidly growing global platform, transforming reliability into a core architectural advantage. You'll partner closely with platform engineering, infrastructure, and product teams in Warsaw, Reykjavik and San Francisco to protect Asana under real-world load, improve how traffic and failure modes are handled, and ensure reliability is designed in rather than added later. This is a role for someone who can lead through influence, coach engineers, and raise the bar for execution and collaboration. This role is based in our Warsaw 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 your recruiter can share more about the in-office requirements. We offer a Contract of Employment (UoP) for our employees in Poland. What you'll achieve Build and lead a new Platform Reliability team, hiring and developing engineers while setting a clear standard for collaboration, ownership, technical excellence and growth. Partner with technical leaders to define the roadmap for core reliability systems such as load shedding, rate limiting, circuit breakers, traffic controls, and other platform guardrails. Establish and evangelize best-in-class operating practices for incident response, postmortems, and proactive risk management through SLOs a

We're looking for a Tech Lead to own technical direction for Asana's Platform Reliability Engineering team. This role is for someone who thrives as a technical leader without needing to take on people management. At Asana, Tech Leads own technical execution, architecture, and long-term engineering strategy. You'll lead complex projects, make key technical decisions, and set the standard for engineering quality. You'll guide ICs through technical design and project leadership, and partner with teams across the company. An Engineering Manager handles people leadership – you own the technical direction. Your team will build core platform systems like load shedding, rate limiting, circuit breakers, and traffic controls that protect Asana under real-world load. This is hands-on work – you'll spend significant time designing and building systems alongside the team, while partnering with other platform teams to make reliability something that's built in, not bolted on. Our tech stack includes: AWS, Kubernetes (EKS), MySQL (RDS), OpenSearch, DynamoDB, Redis, Terraform, Datadog, TypeScript, Scala, Go, and Python. (Yeah, we know this sounds like buzzword bingo – but we want this post to actually show up in your searches.) We're especially interested in people who think like backend engineers but obsess over failure modes, capacity planning, and building systems that degrade gracefully under pressure. This role is based in our Warsaw 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 your recruiter can share more about the in-office requirements. We offer a Contract of Employment (UoP) for our employees in Poland. What You'll Achieve: Set technical direction for the team, making sure we're solving the right problems in the right way. Design and build core platform systems – load shedding, ci

Build something people love Wealthsimple is Canada’s leading financial innovator. The company offers a full suite of simple, sophisticated financial products across managed investing, do-it-yourself trading, cryptocurrency, tax filing, spending and saving. Wealthsimple currently serves more than 4 million Canadians and holds over $155 billion in assets under administration. The company was founded in 2014 by a team of financial experts and technology entrepreneurs, and is headquartered in Toronto, Canada. We're proud of what we've built — and we're just getting started. Read our Culture Manual and learn more about how we work . ML Platform & Infrastructure Team The Machine Learning Infrastructure & Platform team builds the foundational architecture powering AI and GenAI initiatives across Wealthsimple. We sit at the intersection of production MLOps and cutting-edge GenAI enablement. As our AI footprint expands rapidly, our priority is evolving our robust MLOps foundations into a scalable, high-performance LLM serving and routing platform. We build self-serve systems that allow Data Scientists and Engineers to host open-source LLMs reliably, optimize inference latencies, manage GPU infrastructure, and benchmark model performance safely in production. The Role We are looking for an experienced MLOps or ML Platform Engineer who is excited to pivot their deep background in model orchestration, serving, and platform tooling toward solving the unique challenges of LLM inference and infrastructure . In this role, you will bridge the gap between traditional MLOps (model lifecycles, pipeline orchestration, serving infrastructure) and modern GenAI stack requirements (vLLM, GPU cluster management, intelligent model routing, and automated Evals). You will take end-to-end ownership of setting the technical direction for operating enterprise-grade LLM systems company-wide. In this role, you will have the opportunity to: Turn MLOps expertise to GenAI: Transition traditiona

Omada Health is on a mission to bend the curve of chronic disease. Job overview: We are seeking a Senior Software Engineer to help design, build, and scale modern data platform capabilities using cloud-native technologies and AI-driven solutions. In this role, you will develop reusable frameworks, platform services, and engineering patterns that enable teams to build reliable, scalable data-products and AI-powered workflows. You will also leverage Generative AI to enhance data discovery, governance, developer productivity, and self-service access to trusted data. Working closely with cross-functional teams, you will help shape a modern data platform that accelerates innovation while ensuring security, reliability, and operational excellence. Your Impact: Design, build, and operate scalable Data & AI platform capabilities for analytics, data science, and Generative AI use cases with strong practices around data quality, lineage, observability, security, and governance. Develop reusable abstractions, templates, services, and workflows that standardize how teams build and manage data pipelines and data products. Partner with Analytics, Applied-AI, Data-engineering and application teams to deliver platform capabilities that support business and clinical decision-making Evaluate and integrate modern data and AI technologies with a focus on scalability, reliability, developer experience, and cost efficiency Apply Generative AI technologies to improve data enablement, documentation, discovery, workflow automation, and platform usability Promote software engineering best practices, including clean code, automated testing, CI/CD, infrastructure-as-code, monitoring, and secure data handling About you: 5+ years of professional software engineering or data engineering experience building scalable data platforms, services, pipelines, or analytics infrastructure Hands-on experience with modern data architectures, including data lakes, lakehouses, warehouses, analytical datast

The Anyscale Technical Program Management (TPM) team is expected to play a critical role executing high impact programs while continuously improving processes to sustainably grow and increase the effectiveness of the Tech organization spanning Design, Engineering and Product teams. As a Technical Program Manager focused on Anyscale’s core product solution, you’ll help lead complex application development in service of enhancing our product platform. In this role, you'll support and help scale the technical solutions that make Anyscale’s products and services possible. As part of the overall development life cycle you’ll plan requirements, identify risks, manage schedules, and communicate clearly with project stakeholders on complex projects with significant bottom line impact. Your Program management contributions will span prioritization, planning of projects and features, stakeholder management, tracking of external commitments while contributing to the organization's technical culture by highlighting and espousing best practices. You’ll learn and grow alongside talented teammates who share your commitment to excellence and appetite for innovative problem-solving. This is a rare opportunity to join in the leadership of a team that will be responsible for building a successful commercial ML/AI oriented solution from the ground up! As part of this role, you will: Help us build, track and ship our Commercial / OSS product Will work closely with the software development and product teams to deliver high quality, scalable products used by customers around the world Collaborate with the product teams and align all the stakeholders to assemble project teams, assign responsibilities, identify appropriate resources needed, and develop schedules to ensure timely completion of projects by meeting project milestones Assess risks, anticipate bottlenecks, provide escalation management, make tradeoffs, balance the business needs versus technical constraints and encourage risk ta

The Infrastructure Engineering team is responsible for building and maintaining a self-service internal development platform that enables MongoDB engineering teams to reliably deploy and operate their own production services and products. We work with numerous engineering teams across the company to understand their infrastructure requirements and development workflows, develop broadly applicable self-service platform services and tooling, continuously monitor how platform services are being utilized, and look for ways to improve developer productivity through automation and education. We are big open source enthusiasts and use a number of open source tools in our stack (contributing upstream whenever possible). Some of the tools we use regularly include Go, AWS, Kubernetes, Crossplane, Terraform, Helm, Drone, Prometheus, and Grafana. However, technology is nothing without a stellar team of engineers that are focused on doing high quality work and working as a team to solve complex distributed computing and platform engineering problems. This is where you come in! We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Our ideal candidate 2+ years of experience managing and mentoring a team of 3+ engineers Has 5+ years of experience owning the design and implementation of large software/infrastructure projects Has built and operated large-scale distributed systems in cloud providers (AWS strongly preferred) Has a strong backend programming background. Fluency in Go is strongly preferred; deep experience with another compiled or strongly-typed backend language is acceptable Pragmatic, detail-oriented, self-motivated, and understands the benefits of collaboration Strong experience operating production Kubernetes clusters, not just deployed to it Has practical experience defining and operating against SLI/SLOs for services they owned Strong experience with observability tooling: metrics, logging, traces, Prometheus, Grafana, OpenTe

The Infrastructure Engineering team is responsible for building and maintaining a self-service internal development platform that enables MongoDB engineering teams to reliably deploy and operate their own production services and products. We work with numerous engineering teams across the company to understand their infrastructure requirements and development workflows, develop broadly applicable self-service platform services and tooling, continuously monitor how platform services are being utilized, and look for ways to improve developer productivity through automation and education. We are big open source enthusiasts and use a number of open source tools in our stack (contributing upstream whenever possible). Some of the tools we use regularly include Go, AWS, Kubernetes, Crossplane, Terraform, Helm, Drone, Prometheus, and Grafana. However, technology is nothing without a stellar team of engineers that are focused on doing high quality work and working as a team to solve complex distributed computing and platform engineering problems. This is where you come in! We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Our ideal candidate Has built and operated large-scale distributed systems in cloud providers (AWS strongly preferred) Has a strong backend programming background. Fluency in Go is strongly preferred; deep experience with another compiled or strongly-typed backend language is acceptable Has experience working with AI coding agents and can demonstrate building high quality context to yield high quality outputs Has experience designing and implementing medium-to-large software projects, including driving design reviews and mentoring less-senior engineers Pragmatic, detail-oriented, self-motivated, and understands the benefits of collaboration Strong experience operating production Kubernetes clusters, not just deployed to it Has practical experience defining and operating against SLI/SLOs for services they owned Str

About us Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor and Clay Bavor . Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. We’re looking for a hands-on IT Infrastructure Engineer to help scale Sierra’s internal systems during a critical period of growth. You’ll be the second member of our IT Engineering team, partnering closely with our IT Lead, GRC Lead, and Platform Engineering team to build and operate the systems that support our company day-to-day. This is an engineering-first role . Our team approaches IT the same way product engineering teams build software: through code, automation, and well-designed systems. We build internal tools, ship integrations, and operate CI/CD-style workflows to manage identity, security, and infrastructure at scale. This is a foundational role with significant ownership. You’ll help design and implement core infrastructure, strengthen securit

About the Team DoorDash’s GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI-powered products, agents, automation, and personalization to production. Our mission is to increase the velocity of business impact from GenAI. A central pillar of that work is running frontier open-weight LLMs and VLMs (such as GLM, Qwen, Kimi, and DeepSeek) ourselves — real-time GPU serving, high-throughput batch inference, and fine-tuning on autoscaling GPUs — delivering large cost and latency wins (for example, a billion embeddings produced roughly 20× cheaper and visual models served roughly 72% cheaper). We also own core platform surfaces including the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, leading the design and architecture of our open-weights model platform spanning inference and fine-tuning: real-time GPU serving, high-throughput batch inference, and model fine-tuning. You’ll set technical direction across model serving and inference engines, fine-tuning and training pipelines, GPU autoscaling and utilization, batch pipelines, backend services, and observability, and mentor engineers as you go. This role is ideal for a senior engineer who enjoys owning ambiguous, high-impact systems and pushing the cost/performance frontier of GPU inference and fine-tuning in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and cost/performance tradeoffs are evolving quickly. You’re excited about this opportunity because you will… Lead the design of infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Own and evolve our open-weights serving stack — real-time GPU endpoints, high-thr

Webflow is the agentic web marketing platform for modern marketing teams, helping organizations build, manage, and optimize high-performing web experiences that drive predictable growth and strengthen brand trust. Building at Webflow will need grit, because we move fast, without ever sacrificing craft or quality. About the Role We’re looking for a S enior Infrastructure Engineer to improve reliability and stability of Webflow’s customer-facing, production infrastructure, serving millions of page views per hour. Our product is used by over 2 million users world-wide across 190 countries, and you’ll help ensure our platform is secure and scalable for these users as tens of thousands of projects are launched on Webflow each month. Location: Remote-first (Argentina) Permanent, full-time employee (this is not a contractor position) Application Information: Application deadline: applications accepted on an ongoing basis until position is closed and filled This posting is for a new position. As an Senior Infrastructure Engineer you will: Own and evolve the cloud platform that Webflow's product and engineering teams depend on, including our compute layer, EKS fleet, serverless infrastructure, networking, and cloud operations across AWS and GCP. Help design and maintain our infrastructure-as-code foundation, evolving the patterns and shared components other teams build on. Design and maintain the networking layer that connects Webflow's services, ensuring reliability, security, and scalability across our cloud environments. Help make observability data the foundation of how we operate, improving the dashboards, alerts, and SLOs for the infrastructure you own so that issues are caught before customers notice, and on-call pages are actionable instead of noisy. Build and maintain AI-powered automation that improves how we manage cloud infrastructure, from policy-as-code and drift detection to LLM-assisted runbook generation. Help define the culture of this growing team as

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role: Join our Infrastructure Engineering team and help ensure the reliability, scalability, and performance of Replit's infrastructure that serves millions of developers worldwide. As a Staff Infrastructure Engineer, you will bridge the gap between development and operations, implementing automation and establishing best practices that enable our platform to scale efficiently while maintaining high availability. We are seeking Staff Infrastructure Engineers who are passionate about building and maintaining resilient systems at scale. Your mission will be to proactively find and analyze reliability problems across our stack, then design and implement software and systems to create step-function improvements. You will design robust monitoring solutions, automate operational tasks, and continuously improve our infrastructure's reliability, all while mentoring and educating the broader engineering team to make reliability a core value at Replit. You Will: Drive Automation and Infrastructure as Code: Architect, build, and improve automation to eliminate toil and operational work. Design and maintain CI/CD pipelines and infrastructure automation using tools like Terraform or Pulumi. Create self-healing systems that can automatically respond to common failure scenarios. Optimize Performance and Infrastructure: Collaborate with core infrastructure and product teams to performance tune and optimize our cloud deployments (Kubernetes, Docker, GCP). Identify and resolve performance bottlenecks, implement capacity planning strategies, and reduce latency across global regions. Elevate Developer Experience: Design and implement improvements to our build, test, and deployment systems to make software delivery faster, safer,

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The API Platform team is responsible for empowering teams to build highly reliable and performant services, backing our payment systems, fraud detection, and a multitude of other products. As an infrastructure team, you will build and expand the service frameworks to make complex systems easy to use, resilient, and scalable. We build powerful interfaces for engineers that depend on these systems—deployment, load balancers, web framework, databases, Kafka, and Kubernetes—while keeping them highly available and performant. We're looking for engineering leaders who drive the technical vision of Stripe's service infrastructure platform for thousands of engineers to use and build on top of, and thrive in a highly autonomous environment with many moving pieces. What you’ll do You will join as a Technical Lead for one of the most impactful teams at Stripe. You will lead a team of engineers, collaborate with infrastructure and product engineering orgs, and advance service-oriented architecture (SOA) adoption at Stripe. By collaborating with the team's technical leaders, you will ensure the software your team builds meets the needs of Stripe and its customers. We are a highly effective team that consistently delivers high-impact results while genuinely caring for one another. We expect you to bring your curiosity and critical thinking skills to this challenging domain. We are looking for individuals with a strong background in designing and deliverin

About the Team DoorDash’s GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI-powered products, agents, automation, and personalization to production. Our mission is to increase the velocity of business impact from GenAI. A central pillar of that work is our evaluation platform — the unified evals backbone that lets teams measure, trace, and trust the quality of LLM and agent systems across the company, powering trace/score ingestion, LLM-as-judge workflows, agent simulations, and LLM observability for the tens of millions of daily requests flowing through our LLM Gateway. We also own core platform surfaces including the Agent Gateway, open-weights model serving and batch inference, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, with a primary focus on our evals and LLM observability platform: the systems that let teams evaluate, trace, and continuously improve the quality of LLM and agent products. You’ll work across evaluation frameworks and SDKs, OpenTelemetry-based trace/score ingestion, LLM-as-judge and offline/online eval pipelines, agent simulations, data pipelines, backend services, and observability. This role is ideal for an engineer who enjoys building reliable measurement and quality primitives in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and evaluation methodologies are evolving quickly. You’re excited about this opportunity because you will… Build the infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Work on our unified evals platform — evaluation SDKs, OpenTelemetry trace/score ingestion, LLM-as-judge, offline and online eval pipelines, and agent simulations — alongside the LLM Gatew

About the Team DoorDash's MDX team sits within Machine Learning Platform and builds the shared foundation that ML engineers across DoorDash, Wolt, and Deliveroo rely on to build and run ML-powered products. We work across the full ML lifecycle: feature engineering, training, evaluation, deployment, serving, and monitoring. Our mission is to increase the velocity and reliability of ML-driven business impact across the company. A central pillar of that work is agentic infrastructure. We are building systems that let agents accelerate and operate the ML workflow itself, including auto research, where agents explore and iterate on modeling ideas, and self-healing systems that detect, diagnose, and remediate failures in ML pipelines and production models with minimal human intervention. About the Role You will join a small, high-leverage team building the agentic layer of DoorDash's ML infrastructure. You'll design and build the systems that let agents accelerate how ML engineers across DoorDash, Wolt, and Deliveroo develop, ship, and operate models. That includes auto research systems that explore and iterate on modeling ideas, and agentic developer support that helps ML engineers move through training, evaluation, deployment, and debugging faster. You'll own well-scoped components end to end, from design through production, working across agent orchestration, tooling and integrations with our ML platform, evaluation of agent behavior, and observability. This role is ideal for an engineer with a strong backend foundation who is excited to apply AI agents to real engineering workflows, learns quickly, and wants to grow into technical leadership in a fast-moving area where model capabilities, tooling, and best practices change month to month. You're excited about this opportunity because you will… Build agentic systems that increase the velocity of ML development across DoorDash, Wolt, and Deliveroo, helping ML engineers get from idea to production model faster. Design an

About Ema Ema builds AI Employees for HR, IT and Finance. Our AI Employees take on the busy work across the employee experience, from recruiting, onboarding and benefits to IT support, invoice processing and payroll, so people can spend their time on work that needs them. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Creaegis, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production. We ship real systems that run real business processes at scale. Who you are You are an experienced Infrastructure Engineer Engineer who owns backend infrastructure end to end. You design multi-tenant, microservices-based systems that other engineering teams build on, and you make deliberate architectural tradeoffs around consistency, latency, scale, and cost. You are comfortable going deep — service mesh internals, database internals, distributed-systems failure modes — and equally comfortable defining the reliability and security contracts an enterprise AI platform depends on. Responsibilities Design, own, and evolve scalable microservices architectures on Kubernetes across GCP, Azure, and AWS, including multi-tenant isolation (namespaces, network policies, per-tenant resource quotas and RBAC). Build core platform and data-plane components in Golang and Python — data ingestion, knowledge-base indexing and vector/graph search, application connectivity, workflow automation, and ML operations — against explicit latency and throughput SLOs. Own service-to-service communication: gRPC/protobuf API contracts, service mesh (Istio/Linkerd), load balancing, retries, timeouts, and circuit breaking. Make and document architectura