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Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. Welcome to the video-first world From your everyday PowerPoint presentations to Hollywood movies, AI will transform the way we create and consume content. Today, people want to watch and listen, not read — both at home and at work. If you’re reading this and nodding, check out our brand video . Despite the clear preference for video, communication and knowledge sharing in the business environment are still dominated by text, largely because high-quality video production remains complex and challenging to scale—until now… Meet Synthesia We're on a mission to make video easy for everyone. Born in an AI lab, our AI video communications platform simplifies the entire video production process, making it easy for everyone, regardless of skill level, to create, collaborate, and share high-quality videos. Whether it's for delivering essential training to employees and customers or marketing products and services, Synthesia enables large organizations to communicate and share knowledge through video quickly and efficiently. We’re trusted by leading brands such as Heineken, Zoom, Xerox, McDonald’s, and more. Read stories from happy customers and what 1,200+ people say on G2 . In 2023, we were one of 7 European companies t

Backend Engineer (Senior Level) - SDE IV We're looking for a Senior Backend Engineer to lead the architecture and evolution of backend services that deploy and serve machine learning models in production. You'll work closely with ML Engineers, Platform, and Product teams to build scalable, reliable systems and drive technical direction across multiple teams. What You’ll Do Design and drive the long-term architecture of backend services for biometrics and ML model serving. Collaborate with core platform and backend teams on organization-wide architectural initiatives. Partner with business and engineering teams to design and deliver cross-cutting platform capabilities. Lead architectural reviews, mentor engineers, and promote engineering best practices. Build and maintain backend services for deploying and serving ML models Monitor service reliability, performance, and scalability in production Deploy and operate services on AWS using ECS + Fargate, SageMaker, or EC2 + Kubernetes Support real-time and batch inference workflows Contribute to CI/CD pipelines and deployment automation What We’re Looking For Strong expertise in backend development using Java and working knowledge of Python. Experience mentoring engineers and driving architectural decisions. Working knowledge of Python, especially for ML-related workflows Hands-on experience with AWS (e.g., DynamoDB, ECS, EC2, Redis, S3, SageMaker) Familiarity with Terraform or other infrastructure-as-code tools, and experience with CI/CD and production monitoring Experience with observability tools (Datadog, New Relic, etc.) Experience with containers and orchestration (Docker, ECS, etc.) Understanding of how ML models are deployed and served in production Experience with Kubernetes Nice to Have Experience with MLOps or ML platform engineering. Experience with asynchronous programming and event-driven systems. Jumio Values: IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation Equal Opportunities :

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We’re looking for a Senior Software Engineer to join our Network Engineering team to accelerate building and scaling our innovative systems that support our growing identity platform. In this role, you will build the next-generation infrastructure that underpins all systems at CLEAR. The ideal candidate for this role will approach challenges with an eye toward reliability, simplicity, and scalability. What You'll Do: Develop and maintain a streamlined process for engineers to effortlessly build and deploy scalable and reliable software-defined networking solutions on AWS. Enhance our compute platform (Kubernetes) by integrating new functionalities and features, focusing on AWS networking services and concepts such as VPCs, Route Tables, Security Groups (SGs), ALBs/ELBs, and Route53, as well as implementing Kubernetes networking solutions like service mesh (Istio) to optimize service communication and management. Collaborate across engineering teams to advocate for and implement best practices in observability, utilizing tools like Splunk or Datadog to ensure robust network monitoring. Act as a product owner for our infrastructure, collecting feedback and requirements from engineering teams to address pain points and develop solutions, particularly in the realm of AWS networking and cloud-native design principles. What you're great at: 6+ years of extensive experience in infrastructure and platform development, particularly in software-defined networking and AWS cloud services. Proficient in writing production-grade softwar

Overview: Qsight is a high-growth division of Guidepoint focused on building data intelligence solutions for the healthcare sector. Qsight leverages proprietary datasets and rigorous analysis of alternative data sources to generate actionable insights for top-tier institutional investors, medical device manufacturers, and pharmaceutical companies. The Qsight team develops market intelligence products designed to be highly relevant, accurate, and scalable – delivering superior insights to a diverse, global client base. We are seeking an experienced, motivated Tehnical Operations Engineer to join our growing team. This is a multiple-hats role focused on SaaS/platform operations and tier-2 support for client-facing systems. You will own the administration and reliability of key tools, troubleshoot and resolve escalations with clear documentation, and build lightweight automation and reporting to reduce manual work as we scale. You will partner closely with Customer Success, Product, and Engineering to proactively monitor, support, and improve critical systems. Through practical, creative problem-solving, you will strengthen reliability, accelerate time to resolution, and increase operational visibility. Day to day, you will triage and resolve client technical questions, manage vendor license administration and renewals, and produce reporting that informs operational decisions. This role is a launchpad toward an SRE/Platform Engineering track as you grow into deeper automation, reliability engineering, and systems design work. This is a hybrid position based out of our Toronto office. What You’ll Do: Platform Support Own routine ops and configuration changes for critical SaaS platforms – Including Tableau, Freshdesk, Datadog, and our own client facing and internal portals Configure and maintain Freshdesk portals, routing, SLAs, permissions, integrations, etc. based on business requirements. Automate manual operations with Python, PowerAutomate, and shell scri

Senior Infrastructure Architect — Enterprise Observability and Automation Description - Job Summary Senior individual contributor responsible for the architecture, implementation, and operational ownership of enterprise observability, monitoring, and automation platforms across HP's global IT environment. This role modernizes infrastructure visibility capabilities while ensuring operational stability, security, and compliance. Serves as a technical and operational bridge between infrastructure engineering, cybersecurity, SOX/compliance stakeholders, automation teams, and external technology partners — leading complex initiatives such as platform migrations, enterprise integrations, and governance enablement. Responsibilities Enterprise Observability and Monitoring Application owner and senior technical authority for enterprise monitoring and logging platforms (Datadog, Splunk), including platform governance, roadmap alignment, and operational oversight. Lead enterprise-scale monitoring platform migrations, including architecture design, agent strategy, data ingestion models, vendor coordination, and deployment across 5,000+ servers. Define standards for alerting, dashboards, observability data quality, and integration with ITSM platforms (ServiceNow). Design and manage multi-org Datadog architecture, including org structure, RBAC, SSO/SAML, secrets management, and cybersecurity compliance. Oversee SNMP-based monitoring of storage and network devices, including device profiling, syslog/event integration, and NetFlow collection. SOX Compliance and IT Governance SOX control owner for enterprise monitoring applications — approve monthly reviews, participate in internal/external audits (EY), and maintain ITGC/SOX compliance. Provide audit evidence, walkthrough docu

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We’re looking for an early career Software Engineer to join our Infrastructure team to accelerate building and scaling our innovative systems that support our growing identity platform. In this role, you will build the next-generation infrastructure that underpins all systems at CLEAR. The ideal candidate for this role will approach challenges with an eye toward reliability, simplicity, and scalability. What You'll Do: Develop and maintain a streamlined process for engineers to effortlessly build and deploy scalable and reliable software-defined networking solutions on AWS. Enhance our compute platform (Kubernetes) with new functionalities and features, focusing on AWS networking services and concepts such as VPCs, Route Tables, Security Groups (SGs), ALBs/ELBs, and Route53, optimize service communication and management. Collaborate across engineering teams to advocate for and implement best practices in observability, utilizing tools like Splunk or Datadog to ensure robust network monitoring. Act as a product owner for our infrastructure, collecting feedback and requirements from engineering teams to address pain points and develop solutions, particularly in the realm of AWS networking and cloud-native design principles. What you're great at: 0-2 years of experience in infrastructure and platform development and AWS cloud services. Proficient in Python, with understanding of Kubernetes and container orchestration tools like EKS and ECS. Understand AWS networking services, including VPC design, SGs, NATGWs, ALBs/ELBs, Rout

About the Role Amplitude's Cloud Platform team builds the systems that every Amplitude engineer relies on every day to ship code — and we're rebuilding them for the AI era. As a Senior Platform Engineer, you'll own medium-to-high-complexity platform projects end-to-end and help shape a platform where AI agents are first-class users alongside humans: kicking off deploys, opening pull requests against infrastructure, and triaging incidents, so a single engineer can get the throughput of a team. You'll partner with Staff engineers and product teams to make Kubernetes effortless across the engineering org, building self-service automation and scalable AWS infrastructure that lets product teams ship faster, safer, and with less cognitive load. If you're excited about building the systems that other engineers will rely on every day, this role is for you. Key Responsibilities Lead high-impact platform projects — design and ship capabilities that move the needle on developer experience, reliability, or security, and set the bar for quality, testing, and safe deployment practices. Build the AI-augmented platform. Design tooling and workflows that help engineers get more out of AI-assisted development — think infra primitives that are easy to reason about, automated review, and policy-as-code that keeps the guardrails strong as AI shifts how code gets written. Own Infrastructure-as-Code for Kubernetes, AWS, and GCP using Terraform, Helm, Kustomize, and emerging tooling — and make it consumable enough that an LLM can safely PR against it. Evolve our CI/CD backbone (Argo CD / Workflows / Rollouts, GitHub Actions) to make deploys faster, safer, and easier to reason about. Instrument and operate. Drive observability with Datadog and Amplitude, own dashboards and SLOs, and use the data to push reliability forward. Participate in on-call, lead incident response when needed, and turn postmortems into durable platform improvements. Reduce toil and tech debt with pragmatic remediation

We are fueled by a moral imperative to advance mankind, and it all begins with our people, our product, and our purpose. Passion isn’t something we turn on and off; it’s woven into everything we do. If you thrive in high-challenge environments, are inspired by exceptional teammates, and are driven to grow beyond what you thought possible, MX is where you belong. Come build the future with us. Join an award-winning company that isn’t just shaping the financial industry, but transforming it in ways that create meaningful, lasting impact for millions of people. At MX, reliability is a product. Our infrastructure powers financial applications used by millions of people and processes billions of transactions for major financial institutions, and customers feel every second of downtime. We're building a new observability function that runs the way we run incident response: the system does the heavy lifting, and people handle judgment, customers, and the exceptions. As a Senior Observability Engineer, you build and operate an observability control plane. You scaffold baselines, score coverage, and turn every real incident into the detection the platform should have caught. This is a multiplier role: you raise the bar for every team through standards and automation instead of building each team's dashboards by hand. We call it the shepherd model. You shepherd Datadog and partner with our product engineering teams so they observe the right signals for their products. Service owners get real signal instead of noise, and leadership gets coverage and health as a program metric. This role shares the team pager. Observability and incident response run one on-call roster. You take shifts with the rest of the team and act as Incident Commander when an incident needs one. It is core to the role, not an afterthought. Engineering at MX runs hybrid infrastructure (AWS and bare metal) with services in Ruby, Go, and Java, messaging over NATS and RabbitMQ, and data on PostgreSQL an

About the role: We are seeking a Senior Backend Engineer with deep backend engineering expertise and proficiency in one or more major programming languages (e.g., Python, Java, Go, Rust, or Kotlin), along with a strong understanding of AI models and agents. As a core member of our AI Engineering team, you will collaborate with data scientists, ML engineers, and product managers to build scalable, production-ready infrastructure and APIs that power intelligent systems. What you'll be doing: As a Senior Backend Engineer in the AI Engineering team, you will: Build and maintain reliable, scalable backend services to support AI agent execution and orchestration. Develop AI agent systems for complex operational workflows using LangChain, LangGraph, LiteLLM, and Langfuse. Orchestrate a hybrid model stack that includes OpenAI and Google Gemini alongside self-hosted and fine-tuned LLMs like Gemma and Llama. Build and maintain integrations with clinical systems (FHIR, EMR). Drive observability and reliability using OpenTelemetry, Datadog, and Langfuse. Design APIs (GraphQL, REST), background workers, and event-driven systems that interface with AI inference engines and agent runtimes. Collaborate with Data Science, ML, and engineering teams to deploy AI features and improve the performance, scalability, and reliability of backend systems. Participate in code reviews, knowledge sharing, and mentoring to elevate the team’s technical capabilities. What we're looking for: 6+ years of backend engineering experience, with strong proficiency in more than one major programming language (such as Python, Java, Go, Rust, or Kotlin). Solid understanding of AI systems architecture and experience working in environments involving AI agents, LLMs, or inference pipelines. Proven experience in building and scaling backend APIs, microservices, and background jobs. Strong experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Redis), including schema des

About Us Blueshift is the Intelligent Customer Engagement Platform (CEP), headquartered in San Francisco, that empowers leading B2C brands to drive truly personalized, 1:1 marketing across every channel. Founded by repeat entrepreneurs who previously built Mertado (acquired by Groupon) and were part of the early team at Kosmix (acquired by Walmart), Blueshift leverages AI, including Predictive, Generative, and Agentic AI, to automate customer engagement for clients like ClearScore, LendingTree, Udacity, and U.S. News. Backed by top-tier VCs including Nexus Venture Partners, Storm Ventures, and SoftBank Venture Asia, the company has raised a total of $65 million in venture funding and is consistently recognized as a market leader and a Deloitte Technology Fast 500 award recipient. Blueshift is actively scaling its development center in Pune, India. As part of our team, you will drive innovation in cutting-edge technologies including machine learning, artificial intelligence, big data, and large-scale distributed data systems. This is an exciting career path for motivated individuals looking to build complex, impactful solutions that define the future of customer engagement. AI Solutions Engineer II As a Software Engineer in the AI Solutions team , you occupy a unique techno-functional position. You are not a researcher; you are an implementation specialist and problem-solver . You bridge the gap between our core AI infrastructure and real-world customer impact. You aren't just writing code; you are applying data engineering, analysis, and AI knowledge to help global brands realize the full potential of AI-driven marketing. Responsibilities End-to-End Solution Delivery: Lead the full lifecycle of custom AI projects—from initial customer design and technical architecture to testing and production implementation. Production Stewardship: Take ownership of the "last mile" of delivery. This includes triaging technical tickets, analyzing logs (Datadog/Kibana), and deb

About Us What if your work could drive change in a globally established industry, shaping processes that touch every corner of the world? At Forto, we are at the forefront of change, harnessing the power of AI to revolutionise logistics. We want to reinvent digital supply chains to be transparent, frictionless and sustainable. From day one, our mission has been to simplify global trade – creating a seamless and efficient logistics process. Your role & Mission The Site Reliability Engineering team at Forto is responsible for reliability and developer experience. We enable our development teams to write complex business logic by providing best-in-class tooling and infrastructure. We have a production environment based on GCP, Kubernetes, Terraform, and Helm. On top of that, we have self-service tooling written in TypeScript. “You build it, you run it” - our job is to make that real. This is a high-ownership role on a lean team that directly shapes how 70+ engineers build and ship software. If you care about platform quality and want your work felt immediately across an engineering org, this is a great match for you. What you will do Build out our runtime platform as a self-service product that enables our engineering teams to write code, run workloads, and drive engineering culture forward. Bring software development skills and practices into platform engineering, such as code quality, domain-driven design, and test-driven development. Own the developer portal and internal platform roadmap, including leading this year's overhaul of our CI/CD pipelines in collaboration with all product teams. Ensure site reliability by building observability solutions, deployment, and disaster recovery capabilities. Own reliability standards end-to-end through SLOs and error budgets — shaping how teams balance velocity and risk. Drive infrastructure cost optimisation across Kubernetes, MongoDB, and Datadog at scale. Improve our security posture through tooling, compliance work, and

Asana’s rapid growth brings new challenges in keeping our systems fast, reliable, and resilient. As our product evolves, we’re making a major investment in reliability – and building a brand new SRE team in Warsaw is a key part of that strategy. This is your chance to help shape it from day one. This isn’t a traditional “ops” role – we’re looking for strong software engineers who are passionate about building reliable, distributed systems. You’ll work closely with a small SRE team in San Francisco, infrastructure engineers in Reykjavik, and an established infrastructure team in Warsaw. Warsaw will be a significant hub for our future infrastructure engineering and operations. As one of the first engineers here, you’ll have a real say in how we build reliable infrastructure, manage incidents, and support the rest of the company. 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 Influence the future of Asana’s SRE practice, especially as we grow the Warsaw team. Lead reliability-focused projects across our stack – from infrastructure to tooling to incident response. Define and implement Asana’s incident management process – we’re investing here, and you’ll help shape how it works. Build internal platforms and frameworks that help other teams improve the reliability of their services. Be part of (and help shape) a sustainable on-call rotation – shared across teams in Warsaw, San Francisco, and Reykjavik. On average, we handle ~1 page per day, but it’s not constant, and we care about keeping things sane. Work with our stack: AWS, Kubernetes (EKS), Datadog, MySQL (RDS), ElasticSearch (OpenSearch), Redis

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Figma’s Observability engineering team builds and operates the systems that give us deep visibility into the health, performance, and efficiency of our platform. From metrics, logs, and traces to cost attribution and budgeting, this team ensures that engineers across Figma can detect issues quickly, understand system behavior at scale, and make informed decisions about reliability and spend. The team owns and evolves our core observability stack—including platforms like Datadog, shared instrumentation libraries, and the agents and operators that power telemetry collection—while continuously raising the bar on signal quality and operational clarity. This team ensures that engineers across Figma can detect issues quickly, understand system behavior at scale, and make informed decisions about reliability. The team owns and evolves our core observability stack—including platforms like Datadog, shared instrumentation libraries, the agents and operators that power telemetry collection, and a host of internally developed components to power AI Trace Observability —while continuously raising the bar on signal quality and operational clarity. As the Engineering Manager for Observability, you will lead a team of five engineers responsible for shaping the future of visibility and efficiency at Figma. You’ll define the strategy for instrumentation standards and cost transparency, drive initiatives to optimize observability footprint and spend, and explore innovative AI-driven approaches to anomaly detection

As an Account Executive (AE) on our Commercial Sales team, you will assist in Datadog’s overall business growth by strategically engaging and closing net-new customers across small to midsize markets. Sellers follow a well-defined methodology, collaborate with internal stakeholders, identify the customer's unique needs, and clearly convey the value of the Datadog product. AEs have the opportunity to grow their careers in Sales and continue contributing to Datadog team success. 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: Focus on net-new logo acquisition via outbound activity Become a Datadog expert through continued product and sales trainings Manage the full sales cycle, including technical demonstrations and negotiation Collaborate with Sales Development Representatives to drive top of funnel activity Strategically prospect into Chief Technology Officers, Engineering/IT Leaders, and technical end-users Who You Are: Curious, driven, and motivated as a sales person Creative in how you map and break into accounts Able to learn from feedback and champion a growth mindset Comfortable operating in a highly technical, fast paced environment Experienced in carrying quota, with a proven track record of success Fluent in Portuguese Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your experience, we encourage you to apply. Benefits and Growth: High income earning opportunities based on self performance New hire stock equity (RSU) and employee stock purchase plan (ESPP) Continuous professional development, product training, and career pathing Sales training in MEDDIC and Command of the Message Intra-d

Datadog AI Research — Scholars Program with Carnegie Mellon University Datadog AI Research (DAIR) is partnering with Carnegie Mellon University to support a small number of PhD students working on open research problems grounded by ongoing efforts at Datadog/DAIR. You will frame a problem, run your own experiments, and write up what you find, with compute and data at a scale most academic labs cannot provide. You will collaborate with colleagues working on the same questions. The Lab And The Research: DAIR is an industrial research lab motivated by practical challenges in observability and software operation: detecting and diagnosing failures, understanding complex production environments, and helping engineers operate software more effectively. The lab focuses on creating specialized foundation models, post-training and evaluating AI agents, and building frontier-scale machine learning systems. By combining fundamental research with Datadog's large-scale, real-world data and infrastructure, the lab develops new AI capabilities and translates them into practical systems with meaningful impact. Internship projects are shaped with your DAIR mentor and your CMU faculty advisor. You do not need prior experience with observability, monitoring, or infrastructure. What You'll Do: Own a research project end to end: framing the question, running the experiments, writing it up Work directly with a DAIR mentor engaged in the same problem, and stay connected to your advisor and lab Publish, and use the work toward your dissertation See research reach production, when it works Who You Are: Currently enrolled in a PhD program at Carnegie Mellon in machine learning, computer science, statistics, or a related field Depth in at least one area relevant to the research above Comfort running real experiments — training models, working with GPUs, reading and reimplementing recent papers Evidence you can do research: conference or workshop papers, preprin