Trading Support Analyst Jobs

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role Agents are becoming the default way developers ship LLM-powered software, and they are miserable to debug. A single run fans out across model calls, tool calls, retries, handoffs between agents, and multi-turn conversations that only make sense as a whole. When one goes wrong, the developer usually has a log line and a shrug. Sentry's Agent Tracing turns that into something you can actually inspect: agent runs, tool calls, model interactions, token usage and cost, conversations you can replay message by message. As a Senior Software Engineer on the Telemetry Experience team, you'll own that product surface - Python/Django and Postgres on the backend, React and TypeScript on the frontend, sitting on top of Sentry's trace storage. You'll work with the SDK engineers who instrument the agent frameworks upstream and own everything customers touch downstream: the dashboards, the conversation views, the APIs, and the workflows that turn a confusing agent run into an obvious fix. In this role you will Own projects end to end. Take a problem from a rough customer complaint through scoping, design, implementation across the stack, rollout, and measurement. You'll write the design doc, cut the work into shippable pieces, and stay with it until the numbers move Build the views developers debug agents in. Multi-agent workflows, conversation replay, cost and token breakdowns, the moment where a run failed and why. Making a deeply nested, wildly variable trace legible is a genuinely hard interface problem Make the data underneath fast and queryable. Filtering and sorting millions of conversations, getting cost calculation ri

The Martech Analyst, Customer Systems is responsible for mapping how guests move through the digital ecosystem and owning the systems and data flow that power those journeys. While journeys are broken down by customer persona, the core of the role is technical: tracing how events, triggers, and data move between systems—CDP, CRM/ESP, loyalty, app, and POS—at each stage, building and QA'ing journeys within orchestration platforms, and ensuring tracking and tagging capture the right data throughout. This role partners closely with engineering and platform teams to keep systems running smoothly and connected. Map end-to-end digital customer journeys as system and data-flow diagrams, tracing how events, triggers, and data move between platforms (CDP, CRM/ESP, loyalty, app, POS) at each stage. Translate journey and persona findings into technical requirements - event triggers, tagging needs, and platform logic - for engineering, CRM, and platform teams to build against. Define customer personas as behavioral and event-based models grounded in customer data, and identify how their journeys and system paths differ Manage and maintain tag management implementation (Amplitude, Google Tag Manager) to ensure journey and touchpoint data is captured accurately across web, app, and messaging channels. Partner with engineering to troubleshoot and resolve data flow or integration issues between systems and validate that events and triggers fire correctly end to end. Present journey architecture and technical recommendations to marketing, CRM, and engineering stakeholders in a clear, visual format BENEFITS Free Play & 1/2 price food! Health, dental, vision, 401(k) team member match, free mental well-being platform – and that’s just fo

Datadog's Application Performance Monitoring (APM) provides deep visibility into the health, performance, and lifecycle of modern distributed applications, tracing requests from end-user devices (web and mobile) through to backend services. Our goal is to help customers detect root causes faster, optimize application performance, and improve resource efficiency at scale. As the Engineering Manager for APM Serverless, you will help define and deliver the end-to-end serverless APM experience, from auto-instrumentation through troubleshooting, and ensure that OpenTelemetry and Datadog-native customers alike have a frictionless and performant journey. You will also lead efforts to expand coverage of cloud-managed services across providers, ensuring customers can seamlessly trace and monitor critical services in all major and emerging cloud environments. We’re looking for an experienced engineering leader who thrives at the intersection of infrastructure and developer experience. You should care about well-designed APIs, observability-first thinking, and building systems that empower other developers. This is a high-leverage role that will influence how developers across the industry understand and instrument their serverless workloads. 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: Lead a polyglot team of 8-9 engineers and partner closely with Product and Engineering teams across Datadog to deliver industry-leading serverless capabilities that power consistent, scalable, and intuitive instrumentation across languages. Drive a domain that is technically rich: Lambda, Azure Functions, GCP, OTel billing, Rust, durable functions, distributed tracing across managed services. Engineers on this team work

About Datadog We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at a high scale - trillions of data points per day — providing always-on alerting, metrics visualization, logs, and application tracing for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Opportunity User safety and platform integrity is critical to our business. Our customer’s success is our success. We’re looking for a Senior Security Engineer to join us in taking a proactive, highly scalable, and data-centric approach to enabling a safe and trustworthy experience for the users of our rapidly growing and increasingly interactive platform. You’ll fight against threats to our users, platform abuse, and other potentially risky and unwanted behaviors on our platform. Our team covers a broad range of trust and safety related topics including software engineering, data science, user engagement, privacy, threat detection, incident response, and bridging gaps between security and the broader Datadog business. You will bring expertise in a few of these areas. You’ll join a growing security team at an ideal time for making a big impact. Datadog is growing rapidly, and AI-assisted development is increasing both the pace of software delivery and the amount of activity generated by AI agents. The product is seeing very high growth, with the platform becoming more interactive and new products and features developed regularly. 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: Have a direct impact on customers and their overall trust of our platform. Drive the technical roadmap in colla

About Datadog We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at a high scale - trillions of data points per day — providing always-on alerting, metrics visualization, logs, and application tracing for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Opportunity We are looking for an experienced software engineer to join our CI/CD Security Team within our SDLC Security organization. We work at the intersection of security and engineering infrastructure to secure Datadog's continuous integration and continuous delivery systems. Our responsibilities include hardening pipelines, protecting credentials, and enforcing tightly scoped access controls. We also develop authorization and verification mechanisms to ensure that only trusted code and approved processes can reach production. In this role, you will shape and build a new security layer for our CI/CD infrastructure and drive its adoption across the engineering organization. You will solve challenging systems problems around trusted build provenance, secure secret delivery, and real-time policy enforcement at high throughput. The work sits directly in the critical path of software delivery, where strong security guarantees have to coexist with low latency, high reliability, and a seamless developer experience. You’ll join at an ideal time to make a big impact, as the need for robust software supply chain security is higher than ever. Datadog is growing rapidly, and AI-assisted development is increasing both the pace of software delivery and the amount of activity flowing through our CI/CD systems. Securing that scale without slowing engineers down requires strong software engineering fundamentals, thoughtful automation, and security controls designed to operate reliably at high throughput. At Datadog, we pla

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is seeking Software Engineers to join our Observability team within the Infrastructure organization. The Observability team owns the monitoring and telemetry infrastructure that every engineer and researcher at Anthropic depends on—from metrics and logging pipelines to distributed tracing, profiling, error analytics, alerting, and the dashboards and query interfaces that make it all actionable. By joining this team, you'll have a direct impact on the reliability and operational excellence of Anthropic's research and product systems. As Anthropic scales its infrastructure across massive GPU, TPU, and Trainium clusters, the volume and complexity of operational data is growing by orders of magnitude—and an increasing share of the hardest problems live below the application layer. We're building next-generation observability systems—high-throughput telemetry pipelines, fleet-wide continuous profiling, eBPF-based tracing and network visibility, and agentic diagnostic tools—so engineers can detect, diagnose, and resolve issues in minutes rather than hours, even when the answer lies in the kernel, the network stack, or an accelerator rather than on a dashboard. Key responsibilities Design and build scalable telemetry ingest and storage pipelines for metrics, logs, traces, and error data across Anthropic's multi-cluster infrastructure Build observability solutions that give engineers deep, low-overhead visibility into system behavior across the fleet Own and evolve core observability platforms, driving migrations and architectural improvements that improve reliability, reduce cost, and scale with organizational growth

Senior Software Engineer - Observability and Reliability About the Role We are growing the engineering team and looking for engineers who have the chops to build and deliver world-class technology. You will be part of a talented team of engineers with a shared mission to make data easily accessible. What You Will Be Doing Build observability tools and platforms, including: metrics, logging, distributed tracing, dashboarding, alerting, application performance management Build with modern tools and languages like Go, Open Telemetry and Kubernetes Participate in on-call rotation and ensure uptime of services Create runtime tools/processes that optimize cloud triaging and limit downtime Define best practices around making our systems and services measurable Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies. We expect successful candidates to be coding a majority of their time Qualifications We Need Strong Computer Science fundamentals 5+ years industry experience building and maintaining high-quality software, especially software other engineers use You apply a product mindset to infrastructure systems and feel accomplished enabling others Desire to be a great teammate and have fun at work Strong sense of craftsmanship, and a healthy academic curiosity Qualifications We Want (also, skills you’ll learn!) Experience building systems for data analytics Distributed systems monitoring and profiling skills Knowledge of cloud application security models Administered cloud service infrastructure (GCP, AWS, Azure) Startup experience Additional Job details Additional Job details The base salary range for this position is $170k - $240k annually. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize e

Senior Software Engineer - Observability and Reliability About the Role We are growing the engineering team and looking for engineers who have the chops to build and deliver world-class technology. You will be part of a talented team of engineers with a shared mission to make data easily accessible. What You Will Be Doing Build observability tools and platforms, including: metrics, logging, distributed tracing, dashboarding, alerting, application performance management Build with modern tools and languages like Go, Open Telemetry and Kubernetes Participate in on-call rotation and ensure uptime of services Create runtime tools/processes that optimize cloud triaging and limit downtime Define best practices around making our systems and services measurable Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies. We expect successful candidates to be coding a majority of their time Qualifications We Need Strong Computer Science fundamentals 5+ years industry experience building and maintaining high-quality software, especially software other engineers use You apply a product mindset to infrastructure systems and feel accomplished enabling others Desire to be a great teammate and have fun at work Strong sense of craftsmanship, and a healthy academic curiosity Qualifications We Want (also, skills you’ll learn!) Experience building systems for data analytics Distributed systems monitoring and profiling skills Knowledge of cloud application security models Administered cloud service infrastructure (GCP, AWS, Azure) Startup experience Additional Job details Additional Job details The base salary range for this position is $170k - $240k annually. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize e

We’re looking for a Staff Software Engineer with deep experience in GenAI/ML to join Datadog’s Application Performance Monitoring (APM) team. APM is a product which provides deep visibility into applications, enabling users to identify performance bottlenecks, troubleshoot issues, and optimize services. With distributed tracing, profiling, out-of-the-box dashboards, and seamless correlation with other telemetry data, Datadog APM provides some of the deepest and most structured visibility into the health and performance of applications. This context sets us up for an opportunity to be the world leaders in agentic investigations and incident troubleshooting. You’ll act as a technical leader within the APM group, focused on agentic workflows. You’ll lead efforts to design, train, evaluate, and deploy GenAI/ML models at scale. We’re looking for a product-minded ML engineer with strong technical expertise, excellent communication skills, and a track record of driving impactful initiatives end to end. 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: Act as a technical leader within the APM organization, driving GenAI/machine learning projects from concept to production. Build and benchmark GenAI/ML models using state-of-the-art techniques. Collaborate with cross-functional teams to build automated investigation and triaging tools. Influence product direction by bringing a strong product mindset to your work, always advocating for the end user. Guide teams through ambiguity, scaling challenges, and evolving requirements with clear technical direction. Actively mentor engineers and influence engineering culture through leadership in design reviews, technical talks, and working groups. Who You Are: You have a BS/MS/PhD in a scientific field or equiva

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is seeking Software Engineers to join our Observability team within the Infrastructure organization. The Observability team owns the monitoring and telemetry infrastructure that every engineer and researcher at Anthropic depends on, from metrics and logging pipelines to distributed tracing, profiling, error analytics, alerting, and the dashboards and query interfaces that make it all actionable. By joining this team, you'll have a direct impact on the reliability and operational excellence of Anthropic's research and product systems. As Anthropic scales its infrastructure across large GPU, TPU, and Trainium clusters, the volume and complexity of operational data is growing by orders of magnitude, and an increasing share of the most challenging problems live below the application layer. We're building next-generation observability systems, including high-throughput telemetry pipelines, fleet-wide continuous profiling, eBPF-based tracing and network visibility, and agentic diagnostic tools, so engineers can detect, diagnose, and resolve issues in minutes rather than hours, even when the answer lies in the kernel, the network stack, or an accelerator rather than on a dashboard. Key responsibilities Design and build scalable telemetry ingest and storage pipelines for metrics, logs, traces, and error data across Anthropic's multi-cluster infrastructure Build observability solutions that give engineers deep, low-overhead visibility into system behavior across the fleet Own and evolve core observability platforms, leading migrations and architectural improvements that improve reliability, reduce cost, and scale with

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! As the Engineering Manager for Observability, you'll lead the team building the systems that show Figma how its platform and its AI products actually behave in production. That spans our core observability stack, meaning metrics, logs, and distributed tracing, as well as a fast-growing new frontier: the AI observability pipeline that turns traces, conversations, and model outputs into the classification and evals that make Figma's AI features measurably better. You'll set strategy across both, raise the bar on instrumentation and data quality, and push into AI-driven approaches to anomaly detection and operational automation. Observability was an unowned space at Figma until recently, so this is a rare chance to shape an early-stage, high-leverage platform that every engineering team here depends on. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you’ll do at Figma: Lead and grow a 6 engineer team responsible for the reliability, scalability, and evolution of Figma's observability and AI observability platforms. Own and evolve the AI observability ecosystem: a privacy-safe telemetry pipeline that aggregates trace, conversation, and model data, runs classification, and lets teams run evals to measure and improve AI feature quality. Own Figma's core observability stack, including platforms like Datadog, ensuring high availability, strong data quality, and a healthy signal-to-noise ratio across metrics, logs, and traces. Set the technical st

The ML Observability team builds cutting-edge tools to monitor, explain, and improve AI systems in production, particularly those leveraging Large Language Models (LLMs) and generative AI. We provide robust, scalable observability for AI workloads, including drift detection and model evaluation, and behavior tracing, enabling customers to ship AI with confidence. As a Staff Engineer, you’ll lead the development of new features and foundational capabilities within Datadog’s LLM Observability product. You will shape product direction, drive experimentation, and apply your deep understanding of both AI systems and software engineering to solve open-ended problems in the fast-moving AI landscape. Your work will directly impact how our customers monitor, troubleshoot, and optimize LLM-based applications in production. Join us in building the foundational tools that make AI systems observable, understandable, and reliable in the real world. 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: Drive design and implementation of LLM observability features. Ideate, prototype, and scale new product features to provide insights and drive improvements for generative AI systems Work cross-functionally with other eng teams, product, UX, and applied science to iterate fast and find product-market fit Develop and extend tools for tracing, evaluating, and debugging LLMs Influence architecture decisions and mentor engineers to build resilient, high-performance systems Stay close to customer pain points and use those insights to guide product and engineering priorities Stay current with industry trends and advancements in machine learning and observability, driving innovation within the team Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or r

The Agent Observability team builds cutting-edge tools to monitor, explain, and improve AI systems in production, particularly those leveraging Large Language Models (LLMs) and generative AI. We provide robust, scalable observability for AI workloads, including drift detection and model evaluation, and behavior tracing, enabling customers to ship AI with confidence. As a Staff Engineer, you’ll lead the development of new features and foundational capabilities within Datadog’s LLM Observability product. You will shape product direction, drive experimentation, and apply your deep understanding of both AI systems and software engineering to solve open-ended problems in the fast-moving AI landscape. Your work will directly impact how our customers monitor, troubleshoot, and optimize LLM-based applications in production. Join us in building the foundational tools that make AI systems observable, understandable, and reliable in the real world. 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: Drive design and implementation of LLM observability features. Ideate, prototype, and scale new product features to provide insights and drive improvements for generative AI systems Work cross-functionally with other eng teams, product, UX, and applied science to iterate fast and find product-market fit Develop and extend tools for tracing, evaluating, and debugging LLMs Influence architecture decisions and mentor engineers to build resilient, high-performance systems Stay close to customer pain points and use those insights to guide product and engineering priorities Stay current with industry trends and advancements in machine learning and observability, driving innovation within the team Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or related scie

We’re looking for a Senior Staff Software Engineer with deep experience in GenAI/ML to join Datadog’s Application Performance Monitoring (APM) team. APM is a product which provides deep visibility into applications, enabling users to identify performance bottlenecks, troubleshoot issues, and optimize services. With distributed tracing, profiling, out-of-the-box dashboards, and seamless correlation with other telemetry data, Datadog APM provides some of the deepest and most structured visibility into the health and performance of applications. This context sets us up for an opportunity to be the world leaders in agentic investigations and incident troubleshooting. You’ll act as a technical leader within the APM group, focused on agentic workflows. You’ll lead efforts to design, train, evaluate, and deploy GenAI/ML models at scale. We’re looking for a product-minded ML engineer with strong technical expertise, excellent communication skills, and a track record of driving impactful initiatives end to end. 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: Serve as the technical owner for GenAI initiatives within APM, leading design, development, and deployment of ML/AI-powered features across multiple teams. Guide long-term strategy and technical direction for GenAI workflows across APM and related products. Build and benchmark GenAI/ML models using state-of-the-art techniques. Contribute to Datadog’s broader senior engineering community through thought leadership and collaboration on company-wide initiatives. Collaborate with cross-functional teams to build automated investigation and triaging tools. Influence product direction by bringing a strong product mindset to your work, always advocating for the end user. Guide teams through ambiguity, sc

We are building the best platform in the world for engineers to understand, scale, and protect their systems, applications, and teams. We operate at high scale—trillions of data points per day—providing always-on alerting, metrics visualization, logs, application tracing, and security insights for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way . 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: Solve a scaling bottleneck in a critical service Deploy a new feature to production, progressively rolling it out with feature flags Investigate and fix a production issue from a service your team owns Design a way to scale up a service for more traffic With your team, plan the most important projects to work on next Who You Are: You have significant experience in one or more languages You value code simplicity and performance You can design architecture to solve problems at high scale You have a BS/MS/PhD in a scientific field or equivalent experience You want to work in a fast, high-growth startup environment that respects its engineers and customers You’re excited about leveraging AI tools to enhance how you code, solve problems, and build – or eager to learn how You have demonstrated ability to use AI coding tools in day-to-day workflows and build, validate, and refine AI-generated output in products You can design AI Backend systems, with awareness of quality, cost, and latency tradeoffs Bonus: You’re motivated to push the boundaries of how AI can improve software engineering best practices and contribute to building AI-enabled products Datadog values people from all walks of life. We understand not everyone will meet all