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Experienced Low Observables Mission Systems Integration Engineer Company: The Boeing Company We are seeking a Low Observables (LO) Design & Integration Engineer to support design and analysis activities for stealth/low-signature systems. The engineer will perform LO material and structure design, electromagnetic analysis, integration and test support, data processing, and technical reporting. The role requires practical experience with LO materials and technologies, solid electromagnetics knowledge, and hands-on expertise with computational electromagnetic (CEM) solvers used to design and optimize LO solutions. Key Responsibilities Perform design and analysis tasks for LO materials, coatings, treatments, and structural treatments to minimize radar, infrared, and other signatures. Develop and validate LO integration concepts for aircraft/vehicle structures and subsystems, including manufacturability and testability considerations. Use CEM solvers to model, simulate, and optimize LO components and systems (e.g., surface treatments, RAM, apertures, seams, RAM-structure interactions). Perform sensitivity studies and trade-offs across materials, geometry, and integration approaches to meet system-level LO requirements. Process and analyze measured test data from laboratory and flight/field tests; compare test results to simulation and iterate designs. Produce technical documentation: detailed analysis reports, integration guidance, test plans, and summaries suitable for engineering and program management audiences. Communicate technical results and recommendations to multidisciplinary teams and support design reviews. Support manufacturing and test engineering to ensure LO design intent is preserved through fab

👋 WELCOME TO GLIDE! At Glide we're reimagining the banking experience for the modern world. Our agentic platform empowers legacy financial institutions, like community banks and credit unions, to deploy specialized agents that help the bank grow its deposit and loan portfolio. In just the last year, we've raised $20M and grown revenue 500%, and we're accelerating. We're looking for our first Talent Engineer to help us hire the people who will carry that mission to thousands of banks. As Glide's first Talent Engineer, you will build the recruiting engine that doubles our team to more than 100 people. Think of it as a hybrid of recruiter and engineer: you'll design and run the software, automations, and data pipelines behind how we hire, so that finding and winning great people becomes a system we can scale instead of a manual grind. You'll decide what to build and what to buy. Some of it is a polished tool worth paying for. Plenty of it is a few lines of Python and an API call you wrote yourself. The instinct for which is which, and a bias toward the leaner, more controllable option, is what we're hiring for. This is a rare opportunity to join an early-stage company and help create a new standard for how a company hires. What You'll Do: Turn our network into our pipeline: Our best hires will come from people our team and investors already know. You'll build the systems that surface those second and third-degree connections at scale across LinkedIn, GitHub, operator communities, and referral graphs, so warm introductions happen on purpose instead of by luck. Automate sourcing and outreach: Stand up and tune the agents and sequences (Juicebox, Clay, Ashby, and whatever you build yourself) that find, enrich, and reach candidates faster and far more personally than any one person could by hand. Put AI on the first read: Design the LLM-assisted screening that filters for fit before a human spends a minute on it. You own the prompts, the scoring logic, and the quality che

About the team Online Data builds and operates Habitat, the single product surface of Online Data and the system of record for OpenAI’s online user data. As OpenAI’s scale and product requirements evolve, Habitat is becoming a full-stack, one-size-fits-most database platform with end-to-end ownership of: Provisioning and developer experience APIs and guardrails Scaling, performance, and reliability Data movement, caching, routing, and placement Privacy enforcement and access control Change Data Capture (CDC) as a first-class primitive The foundation for future storage backends You’ll work on the core online database platform behind OpenAI’s products, building and operating Habitat services that handle high-QPS, latency-sensitive workloads across regions. You’ll partner closely with internal platform and product teams to ship safe, reliable systems, then push them to be faster and more cost-efficient through better caching, routing, observability, and operational tooling. This is a critical role for engineers who like owning hard distributed-systems problems end to end and sweating the details from p99 latency to production operations at massive scale. In this role, you will Design and build core abstractions spanning storage, caching, routing, CDC, and privacy enforcement Own a major surface area end to end, from product and API design to operational excellence Improve latency, correctness, and cost efficiency for real production workloads at massive scale Build strong instrumentation, debugging workflows, and developer-first tooling Collaborate closely with internal product and infrastructure teams to understand requirements and ship pragmatic solutions Participate in an on-call rotation and raise the bar on reliability while aggressively improving performance and usability You might thrive in this role if you have A strong track record building and operating high-scale backend or data-intensive distributed systems in production Excellent systems judgment and the a

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We embed deeply with users to solve high-leverage problems. We move quickly from prototype to deployment and surface patterns that shape the platform. We operate at the intersection of customer delivery and core development. We work closely with Product, Research, and Go-To-Market (GTM). About the role We are hiring a Forward Deployed Engineer (FDE) to build and deploy AI systems for legal work. You will embed deeply with customers—often working closely with senior legal practitioners—to identify the right first use case, rapidly prototype a solution, and prove measurable value. Early engagements may focus on creating a “hero” workflow that shows how OpenAI’s models can support legal analysis, drafting, research, or real-time work with complex case records. You will own the technical work from discovery and proof of concept through production adoption, while translating customer workflows and constraints into clear product feedback. As the motion matures, you will turn successful deployments into repeatable patterns that can scale across larger accounts and the broader legal market. This role is based in San Francisco or New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance. Travel up to 50% may be required. In this role, you will Embed with law firms and legal teams to understand their workflows, identify high-value opportunities, and select the right initial use cases to prove value. Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks t

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We embed deeply with users to solve high-leverage problems. We move quickly from prototype to deployment and surface patterns that shape the platform. We operate at the intersection of customer delivery and core development. We work closely with Product, Research, and Go-To-Market (GTM). About the role We are hiring a Forward Deployed Engineer (FDE) to build and deploy AI systems for legal work. You will embed deeply with customers—often working closely with senior legal practitioners—to identify the right first use case, rapidly prototype a solution, and prove measurable value. Early engagements may focus on creating a “hero” workflow that shows how OpenAI’s models can support legal analysis, drafting, research, or real-time work with complex case records. You will own the technical work from discovery and proof of concept through production adoption, while translating customer workflows and constraints into clear product feedback. As the motion matures, you will turn successful deployments into repeatable patterns that can scale across larger accounts and the broader legal market. This role is based in San Francisco or New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance. Travel up to 50% may be required. In this role, you will Embed with law firms and legal teams to understand their workflows, identify high-value opportunities, and select the right initial use cases to prove value. Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks t

The Dashboards product is Datadog's unified single-pane-of-glass for metrics, logs, and traces—a comprehensive treasure trove of observability data. We are transforming Dashboards into an AI-native control surface and the central hub where every team moves seamlessly from question to insight to action – providing a guided experience that feels like having an expert SRE at your side and ensuring the entry point is never an empty canvas. We're hiring a Staff Applied Scientist to define and guarantee the quality of this AI system at scale. "Good" isn't one number — it spans answer quality, tool-selection accuracy (critical given the growing catalog of data sources and visualizations), retrieval relevance, latency, token cost, and end-to-end agent success. The space is full of open questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when a user’s query can result in the agent making decisions against dozens of visualizations and data sources – both of which are growing month over month? How do you build a measurement system that catches regressions across all widget types and data sources (e.g., enforcing correct grouping, sorting, and time overrides), and is easy to use and extend by dozens of teams? If those are the problems you want to spend your time on, come build this with us. 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 evaluation strategy for Dashboards, as well as sister teams within our organization. Define the metrics — offline and online, quality and cost, single-turn and multi-turn — that the team and the broader organization optimize against. Build the eval datasets, golden traces, and regression harnesses that catch quality changes before they hit customers, an

Datadog is looking for a Senior Product Manager to help lead the evolution of our fleet and lifecycle management capability, the product surface that gives customers visibility into, and control over, the observability software running across their infrastructure. This capability manages the deployment lifecycle for core observability agents and OpenTelemetry collectors running on customer hosts and containers. The Senior PM will expand the scope of fleet capability to additional Datadog software components, making it the single place customers go to see everything running in their environment, at any version, in any deployment model, and to manage it remotely and safely at scale, for both human operators and, increasingly, AI agents acting on their behalf. This is a high-visibility, cross-functional role. You'll partner with multiple engineering teams and be responsible for defining and delivering a coherent, unified fleet experience across UI, API, and MCP for customers. 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 evolve the product vision and roadmap for a unified fleet and lifecycle management capability spanning multiple product lines and deployment models. Define what "managed" means for each new software component as it's brought into fleet, balancing consistency of experience with the realities of each component's operational model. Drive a phased expansion plan, sequencing new components into fleet based on customer value, technical complexity, and dependency readiness. Partner closely with engineering leads across several teams to align on shared architecture principles to support disparate software components. Represent the voice of the customer for a capability that must work equally well for human operators using a UI and for AI

About the Team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to Semiconductor customers. You will own how solutions are scoped, built, shipped, and adopted across high-value engineering workflows such as RTL design, verification, and physical implementation. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will focus on the semiconductor vertical to deploy next-generation AI capabilities. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project m

About the team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in San Francisco. W

About the team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in NYC. We use a hy

Use Your Power for Purpose Every day, Pfizer’s unwavering commitment to quality ensures the delivery of safe and effective products to patients. Our science and risk-based compliant quality culture is both flexible and innovative, always putting the patient first. Whether you are involved in development, maintenance, compliance, or research analysis, your contribution directly impacts patients. What You Will Achieve In this role: The incumbent is a member of the Quality Environmental Control (EC) Laboratory team. Under the supervision of the Environmental Monitoring (EM) Section Manager, and designated EM Shift Team Leader(s), the incumbent will be responsible for the collection, analysis, and inspection of manufacturing environmental conditions and materials according to Standard Operating Procedures (SOPs). Samples can include both physical and microbiological, air, surface, and water system products, as well as commodity items. In addition, the incumbent shall be responsible for both physical and microbiological, collection and analysis of pharmaceutical waters, raw materials, active pharmaceutical ingredients (APIs), and finished products according to Standard Operating Procedures (SOPs). Assays to be performed will be qualitative, quantitative, and investigational in nature and are performed in compliance with USP, FDA, other regulatory body requirements, Pfizer SOPs, and approved license requirements. Aseptic gowning practices will also be adhered to for the performance of activities as required. Results are compared with specifications, documented as per data integrity regulations, and incumbent is responsible for providing communication of all process and specification deviations. Incumbent has working knowledge of EM, microorganism handling, aseptic technique, and quality concepts as to perform routine assignments with minimal supervision. Additional responsibility may include performing data trending

The way products get built is changing. Agents write a growing share of shipped interfaces, designers work in code, and a design system's output is bigger than a component library. At Datadog we're redefining ours for that world, and evolving how the product looks and feels at the same time. DRUIDS is the design system behind every Datadog surface, used daily by more than a hundred designers and thousands of engineers across thirty-plus products. You'll lead the team that owns it: designers and design engineers who set the system's direction, hold the quality bar for what ships, and build the tools that make designing in code the default way to work. The team partners closely with product designers, frontend engineers and PMs across the company. This is a hands-on leadership role in a technical, engineering-forward company. You'll be expected to have a point of view and defend it, to be the person the design org asks about quality, and to make the call when work isn't good enough yet. Much of what a design system should be right now hasn't been settled — here or anywhere else. If you're a designer who never stopped making things, and you'd rather decide what a system should be than maintain one that already exists, this is the role. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do Lead the team and set its direction Decide what DRUIDS owns, what it ships, and what stays with product teams. Own where the system goes next. Have a view on what a design system should be, and argue for it. Turn direction into a roadmap, and work with partners on what gets built and when. Coach the designers and design engineers on your team, be clear about what each person owns, and hire as the team grows. Own craft and quality Own the craft and quality of components, patterns,

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 Mixpanel's website is the front door to our product and our biggest driver of pipeline — it's the first real experience most prospects have with us. We design, build, and ship it ourselves in Framer, treating it as a living product surface rather than a set of static pages. We're looking for an Interactive Web Designer who lives and breathes this work — someone energized by building, not just designing and handing off. You'll report to our Brand Design Leader, partnering closely with our Staff Interactive Designer and Website Manager, and working cross-functionally with Marketing and other teams to turn strategy into shipped web experiences. The work directly shapes how prospects understand, trust, and convert on Mixpanel — from product storytelling to improving conversion paths. This is a hands-on-role: you should be as comfortable building in Framer as sketching a layout in Figma. Webflow experience translates well — different platform, same muscle of designing and building in one motion. What You'll Do Design and build end-to-end experiences and iterations Design and build pages and components directly in Framer, not just hand off static designs for someone else to implement Bring interaction, motion, and detail to web experiences — micro-interactions, transitions, scroll behavior — that make the site feel considered rather than templated Build and maintain landing pages for campaigns, launches, and regional/ABM needs, working from brand and campaign direction that drives pipeline goals Strengthen our web design system Contribute to and help maintain a component library that lets the te

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role Modal's LLM inference platform delivers frontier performance for open-source models with best-in-class elasticity and developer experience, made in part possible by our custom runtime with GPU memory snapshots and multi-cloud substrate . We're looking for a leader to own the direction and execution of this platform to continue to establish us as the clear market leader, working closely with customers like Cognition, Doordash, Ramp, and many more. You'll be leading a group of highly talented engineers working on our market-leading LLM inference offering, spanning the serving stack, routing infrastructure, internal agentic optimization platform, and the user-facing product surface area. This is a hands-on leadership role — expect to split your time between technical contribution, product shaping and people management depending on what the team needs. You'll set direct

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 Team The Revenue Marketing team at Mixpanel is responsible for pipeline generation across paid, website, and product-led channels. This role sits within that team as its dedicated engineering owner — accountable for the technical systems that power how people discover, evaluate, and request Mixpanel. You are the only engineer dedicated to this surface, which means you set its technical direction rather than execute against someone else's. You work directly with our marketing teams and partner with Growth Engineering on shared systems. Website design and content are handled by our web design team; your focus is the technical infrastructure, integrations, and systems that sit underneath. About the Role As our Marketing Systems Engineer, you own the technical layer of our marketing engine: the integrations and infrastructure that power our marketing website. The website is our primary lead capture system that turns traffic into pipeline. You own the systems that connect our marketing surface to Salesforce, Customer.io/Hubspot, and our broader GTM stack. You set the technical roadmap for this surface, move fast, measure impact, and treat reliability as a first-class concern rather than a cleanup task.You will also collaborate with Growth Engineering on shared infrastructure including handraiser routing and tracking. Responsibilities Own the technical health of the Mixpanel marketing website: page speed, WCAG compliance, Google Tag Manager, technical SEO, and third-party integrations including Qualified, Optimizely, and TrustArc. Own the integrations between the marketing website and our GTM stack t