Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy. A day in the life (Responsibilities) Independently design and implement well-defined features across the full stack with minimal day-to-day guidance. Collaborate with Product Managers, UX designers, QA, and fellow engineers to translate requirements into working software. Develop and maintain frontend features using React or Angular, focusing on usability and performance. Contribute to backend services using Java, Kotlin, or .NET (expertise in one is sufficient; .NET is not mandatory). Build and consume RESTful APIs and integrate with internal systems. Write clean, maintainable, and testable code aligned with Toast engineering standards. Participate actively in code reviews—both receiving and providing constructive feedback. Troubleshoot production and non-production issues within owned areas and contribute to root-cause analysis. Use Gradle or Maven, Git, and standard development workflows effectively. Apply AI-assisted development tools (e.g., Claude Code, Cursor, Devin) to improve development speed and quality. Support team delivery during critical phases when needed, including production issues and urgent fixes. Consistently delivers on commitments with predictable cycle time for scoped work. Demonstrates ownership of components or features but does not yet own large systems end-to-end. Understands and follows established architectural patterns and engineering best practices. Proactively communicates progress, risks, and dependencies. Seeks feedback and continuously improves technical depth and execution quality. What you'll need to thrive (Requirements): A minimum of Bachelor’s degree in any area, or any other related discipline. 6+ years of experience in software or full-stack development. Strong hands-on experience with frontend frameworks such as React or Angular. Solid back
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About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role Ramp's Dev API team builds the programmatic surfaces that let developers and AI agents read from and write to Ramp. We are an AI-focused platform team making it trivially easy for any engineer at Ramp (or outside it) to ship new capabilities across all surfaces. Our ideal candidate thinks agent-first, has strong opinions on developer experience, and wants to define how software interacts with financial infrastructure at scale. Check out our Engineering Blog for more on our tech stack, mission, and values! What You'll Do Build and operate Ramp's multi-surface platform with a high bar for reliability, correctness, and developer experience across tens of thousands of businesses. Serve thousands of builders and partners using our API, driving a large fraction of Ramp’s revenue, and deliver on a massive business opportunity to embed Ramp everywhere. Build software factories -- autonomous tooling and agents that accelerate endpoint creation, enabling teams across Ramp to ship their own API surfaces. Lead design and execution of complex back
Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Responsibilities Design, develop, deploy, and maintain automation software solutions supporting factory operations, including autonomous material delivery, factory scheduling, and in-house equipment automation. Work closely with site manufacturing teams to understand operational needs and develop automated scheduling solutions that improve productivity, cycle time, and system efficiency. Collaborate with global factory automation teams to enable and integrate autonomous mobile robot solutions for automated material delivery within the factory. Partner with global equipment and automation groups to develop, enhance, and support in-house equipment automation, ensuring performance, reliability, and scalability of production systems. Own the end-to-end lifecycle of automation solutions, including understanding requests, solution design, development, deployment, monitoring, and continuous evaluation and improvement. Identify opportunities for automation, optimization, and performance improvement using data analysis, system monitoring, and visualization tools (e.g., dashboards and reports). Support day-to-day production operations by troubleshooting automation systems, reso
Datadog's Forward Deployed Engineering function is in an active growth phase, and the FDE Lead will play a central role in shaping what comes next. Working in close partnership with the Head of Datadog for Startups and Forward Deployed Engineers, and the existing FDE team, you will help define and expand the FDE framework, build out the structures and processes that allow the team to operate at scale, and extend the program's reach well beyond any single customer segment. This role sits at the rare intersection of sales, execution, program design, and hands-on engineering leadership. You are part field technical leader, part program architect, and part cross-functional connector. You will help determine what the FDE motion looks like at Datadog, contribute to its playbook, and push the boundaries of what the team can deliver. 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: Evolve and scale the FDE operating model end to end: engagement intake, scoping, sprint delivery, handoff back to account teams, and the success metrics (time-to-value, adoption lift, ARR influence, NPS) and reporting infrastructure that support them. Build out a catalog of FDE offerings spanning observability quickstarts, custom integration development, LLM/AI observability accelerators, CI/CD pipeline instrumentation, and cost optimization deep dives, and contribute to their pricing and business models, including free-to-paid conversion plays, paid deployment packages, and post-deployment success motions. Capture product and feature gaps uncovered during deployments, translate them into structured prioritized briefs, and partner with PM and Engineering to strengthen the field-feedback channel that informs roadmap decisions on a regular cadence. Hire, onboard, an
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet. The Team: Value Engineering is responsible for our largest Fortune 500 customers and owns their transformation journey by working on the very frontier of what’s possible with data and AI on the Celonis Platform. Partnering closely with the Sales team, Value Engineering is responsible for ensuring that the Celonis Platform is deployed to tackle the most strategic business challenges, fits into the right place in our customers’ technology stack and most importantly generates strong ROI through deep and broad deployments. The Role: As a Senior Value Engineer, you will spearhead AI and data-driven business transformation within the Public sector by contributing to your customer’s end-to-end value journey using the Celonis Context Model. Working alongside Lead and Principal VEs, you will combine technical execution with consulting and project management. As an AI-fluent operator, your core mandate is to orchestrate complex roadmaps and execute targeted transformation initiatives that improve how these businesses operate across their core ecosystems. The work you’ll do: Value Selling & Realization: Uncover the real issues by peeling back layers of organizational complexity. Own the Outcome from first discovery through realized
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet. Are you a digital transformation leader ready to architect the AI-driven future of the Energy sector? This is not a standard process optimization role. We are looking for a Lead Value Partner to own customer success and drive high-stakes SaaS and AI adoption across top-tier O&G enterprise accounts. You will serve as the strategic bridge—translating complex business needs into technical strategy. As a trusted advisor to C-suite executives (COO, CFO, CTO), you will blend deep operational Oil & Gas DNA with elite management consulting and an AI-first mindset to realize maximum customer value. The Impact You Will Drive Value Architecture: Translate executive priorities into AI use cases (optimization, maintenance, decarbonization) and Value Realization Frameworks. Solution Blueprints: Architect scalable, end-to-end data flows to resolve complex operational bottlenecks (refinery, pipeline, reservoir). Financial Quantification: Build data-backed business cases driving $10M+ in CAPEX/OPEX savings. Executive Advisory: Deliver high-stakes value narratives to C-suite stakeholders and supermajor leadership to accelerate software pipelines. Process Transformation: Automate field-to-back-office workflows using Master Black Belt methodolo
About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role Ramp is building something ambitious, and we believe our most important advantage is our people. This role sits at the foundation of that belief. You'll help shape how Ramp identifies, evaluates, and hires world-class engineering talent, with a particular focus on the engineers at the center of what we're building next. This is a craft role. You'll own pipelines end-to-end, partner directly with our Engineering leadership, and be accountable for the quality of the people we bring through the door. We're looking for a Technical Recruiter who treats hiring as a discipline. Someone who cares as much about candidate experience and calibration as they do about closing. You won't just be working off a req list. We're looking for someone who can take ambiguous or high-level direction from engineering leadership and turn it into a sharp, targeted search, knowing exactly who they want before the role even opens. You'll be expected to have strong opinions on talent, defend them with evidence, and push back on stakeholders when the bar is at ris
Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Job / Role Summary The Principal Engineer provides technical leadership for NAND Advanced Thin Films, defining technical direction and driving the strategic advancement and integration of sophisticated structural and electrical film processes into manufacturing. Success requires proven leadership in thin film module development, strong cross-functional influence, deep characterization and correlation capability, and strong judgment in technical tradeoffs for manufacturability, scaling, yield, and reliability. Main Responsibilities Define and implement technical strategy for structural and electrical film process development aligned to business and technology objectives . Lead multi-functional teams to develop, integrate, and scale thin film processes for advanced NAND structures/devices. Oversee end-to-end development of process modules with
About Hark Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory. We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world. To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems. About the Role The Embedded Software team owns the software running on Hark’s next generation of AI hardware, and we are looking for an Embedded Software Engineer, Platform to own the OS platform layer of it. You will design, configure, maintain, and optimize the OS platform services, the user space services and daemons above them, and the protocols that connect the device to our backend. This is the platform end of the embedded spectrum: services, frameworks, virtualization, and protocol work on top of a complex multi-core SoC, in addition to driver and MCU work. You will partner closely with the BSP, embedded software, UX, and backend teams, and with the AI teams whose models run on the platform you build. Responsibilities Design, configure, maintain, and optimize the OS platform services on Hark devices Build system services and daemons, frameworks, and networking primitives and protocols Own backend integrations, including protocol design and the performance analysis behind it Build and maintain virtualization frameworks and multi-OS system design, with the performance analysis to back it Profile and tune the platform for performance and power across the full multi-core system Partner with BSP, embedded software, UX, and backend teams so platform se
Agents have changed the game for software delivery and efficacy. Diligent is the leading GRC platform in the world, and we are racing ahead to take the agents show on the road and work with the customers where they work . The FDE function will lead the change on how we embed AI agents into some of the world’s most complex governance, risk and compliance environments. This is not a support or consultancy role. It is a builder role, for someone who is equally comfortable reading a failing agent trace, running a discovery workshop with a bank’s internal audit team, and translating what they find into a production-grade agentic solution. You will be building AI agents for GRC professionals , not assistants that surface suggestions, but agents that own complex, multi-step workflows end to end . Agents that customers can hand a task to and trust it will come back done. Closing the gap between a promising prototype and something a company Board and ELT depends on is a completely . Here’s a breakdown of what you’ll do Embed directly with major enterprise customers (global banks, regulated corporates) across EU and US ; sitting wi th internal audit teams, risk functions, compliance and governance professionals to understand their real workflows and devise agentic solutions to intelligently automate them creating tremendous efficacy and efficiencies for our customers. Run agent-focused discovery workshops, rapidly prototype agentic solutions, and test them with practitioners; distinguishing between workflows that need an agent and those that need a button. Source, integrate, and move data between enterprise systems as part of live customer implementations — understanding the real data landscape customers operate in and building reliable pipelines to support it . Take agents from prototype t
Why RoboForce RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company's robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability. We are looking for a Senior / Staff AI Research Engineer, Data Infrastructure to build the data and learning engine behind RoboForce's Physical AI stack. In this role, you will own the full pipeline — from raw teleoperation and UMI device data collection through curation, annotation, and storage, to post-training infrastructure that scores demonstrations, identifies failure patterns, and closes the loop back into model retraining. Responsibilities Design and maintain end-to-end data collection pipelines ingesting multimodal demonstration data from teleoperation devices and UMI hardware, including synchronization, versioning, and distributed storage at scale. Build annotation tooling and data curation workflows — quality filtering, deduplication, episode scoring, and domain reweighting — to produce high-quality training datasets for robot policy learning. Develop post-SFT reinforcement learning infrastructure: implement reward scoring on demonstrations, mine and categorize failure patterns, and feed curated failure data back into the retraining loop. Build evaluation and test infrastructure to log policy rollouts on-robot, capture structured results, and surface actionable diagnostics for the research team. Collaborate with ML researchers to define data schemas, episode formats, and pipeline interfaces that support rapid iteration on VLA and manipulation policy training. Architect scalable storage and retrieval systems for heterogeneous robot data (vision, proprioception, action, language) across both cloud and on-prem environments. Requirements Bachelor's or Master's degree in Computer Science, Robotics, or related field with 5+ years of experience. Strong proficiency in Python and experience build
Note: if you are an intern or new grad applicant, please do not apply using this link and visit our jobs page for those specific postings. 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 Organization Money as a Service (MaaS) oversees a diverse portfolio of Stripe's core products and platforms. These offerings facilitate the global movement and management of funds for users. The teams that fall under the MaaS umbrella include: Accounts and Connect, Money Movement and Storage (MMS), Crypto and Banking as a Service (BaaS). Together, these teams work to ensure Stripe users have the robust financial infrastructure and tools they need to power their businesses on a global scale. Team Matching: exact team matching for one of the sub-teams will begin during final stages. Please note we may also consider you for different orgs based on your experience, location, etc. More information on our team matching process can be found here . What you’ll do We’re looking for Full Stack engineers who are interested in building software services and platforms that impact thousands of employees and millions of Stripe users, regardless of whether they’re an end user, developer, or partner. Responsibilities Build end-to-end experiences for Connect that make it as easy as possible to participate in the Internet economy and receive money online. Some of Stripe’s largest users are platforms that connect senders of payments with receivers of payments. Lyft connects riders to drivers, Kickstarter connects back
About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team The Agent Platform team builds the runtime and model orchestration layer that powers Decagon’s agents in production. This is the orchestration layer that turns workflows, tools and guardrails into a reliable, low-latency, and delightful experience for end users. At the core of this work is the agent harness: the routing, execution logic, tool orchestration, and control-plane systems that determine how an agent behaves in a live conversation. The team owns the full execution lifecycle of each conversation—from selecting workflows and orchestrating multiple models (e.g., router/planner/supervisor patterns), to coordinating tool calls, enforcing safety constraints, and communicating back to the user. The team operates across both real-time systems (e.g., voice interactions with strict latency requirements) and longer-horizon execution (supporting more complex reasoning and workflows). Our research shows that an agent’s task execution reliability increasingly depends on the orchestration
About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team The Agent Platform team builds the runtime and model orchestration layer that powers Decagon’s agents in production. This is the orchestration layer that turns workflows, tools and guardrails into a reliable, low-latency, and delightful experience for end users. At the core of this work is the agent harness: the routing, execution logic, tool orchestration, and control-plane systems that determine how an agent behaves in a live conversation. The team owns the full execution lifecycle of each conversation—from selecting workflows and orchestrating multiple models (e.g., router/planner/supervisor patterns), to coordinating tool calls, enforcing safety constraints, and communicating back to the user. The team operates across both real-time systems (e.g., voice interactions with strict latency requirements) and longer-horizon execution (supporting more complex reasoning and workflows). Our research shows that an agent’s task execution reliability increasingly depends on the orchestration
At Scale, we build the AI systems behind some of the country's most important decisions. On the Public Sector Engineering team, you'll embed directly with U.S. government customers, including the Army, Air Force, Joint commands and Intelligence Community, to build and deploy AI applications that support their most critical missions. This is a hybrid customer-facing engineering role. You'll sit with the people whose problems you're solving, own delivery from first prototype to production, and ship software that customers adopt and rely on in the field. Model performance matters, timelines are urgent, and ambiguity is the norm. Your work directly shapes what Scale's platform can do for the public sector. What you'll do Embed with government customers to understand their mission, scope the problem, and turn it into working software. Own delivery end-to-end: design, build, deploy, and maintain solutions at customer sites, from prototype to stable production. Build robust backend systems and data integrations that connect customer environments to Scale's platform and back. Partner with product and engineering to feed field signals back into the roadmap, so the patterns you build once become capabilities the whole team can reuse. Serve as the technical point of contact for customer stakeholders, guiding adoption and maximizing mission impact. What we're looking for Required 5+ years of software engineering experience, ideally in customer-facing, forward-deployed, or government contexts. Strong production coding in Python and TypeScript (or comparable modern languages). Comfort across the stack, including cloud platforms (AWS, Azure, or GCP), containers, Linux, and networking fundamentals. Ability to operate independently in ambiguous, fast-moving environments and make sound trade-offs under pressure. An active TS/SCI clearance, or eligibility to obtain one. Bonus Experience building or deploying systems powered by LLMs or generative models. Familiarity with Node and
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