Full Stack Engineer, Money Movement

SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: We are seeking a talented Software Engineer to join our X Money team, focused on building a revolutionary global payment network that will serve over 600 million users and rival the world’s largest financial institutions. In this role, you will specialize in backend development, designing and optimizing robust microservices to ensure scalability, security, and reliability. You will support full-stack efforts, collaborate with cross-functional teams on payments, fraud detection, and compliance initiatives, and contribute to the creation of a high-scale financial products platform. This is an opportunity to work on greenfield projects in a fast-paced, startup-like environment, driving innovation at the intersection of AI and finance. RESPONSIBILITIES: Develop backend services, APIs, and data models to support high-volume, multi-user environments. Work with iOS, Android & Web client engineers to ship products. Design robust infrastructure and microservices for payments, transactions, growth, monetization, and engagement across platforms. Build and maintain fullstack features, including user dashboards, personalized experiences, content delivery, interactive tools, assessments, and real-time analytics. Le

About the Team The Privacy Engineering team builds secure, reliable systems that help OpenAI meet its legal obligations while protecting user data. We partner closely with Legal and engineering teams across OpenAI to support lawful data access requests and other critical legal workflows. Our work turns complex, high-stakes processes into auditable and dependable technical systems with clear human oversight and strong privacy and security controls. About the Role We’re looking for a full-stack Software Engineer to build the internal tools and data pipelines that power lawful data access request workflows and Legal Operations. You will work across product and data systems to make authorized retrieval and case handling accurate, efficient, and auditable. This role is well suited to someone who enjoys translating ambiguous operational requirements into durable systems, cares deeply about sensitive-data handling, and wants to improve both technical reliability and the day-to-day experience of the people operating these workflows. In this role, you will: Design, build, and operate backend systems and workflow tooling for the full lifecycle of lawful data access requests, from intake and scoping through authorized retrieval, review, preparation, and audit. Build reliable data pipelines and interfaces across products and data stores so authorized teams can locate and handle the right records accurately and reproducibly. Implement least-privilege access, approval gates, provenance, audit trails, data minimization, and safe failure modes for sensitive workflows. Partner with Legal and Legal Operations to translate legal and operational requirements into clear technical designs and intuitive operator experiences. Identify responsible automation opportunities that reduce repetitive work while preserving human review, judgment, and accountability. Own production systems through testing, observability, incident response, documentation, and continuous reliability improvements. Hel

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. The Role You'll be an engineer who builds AI agents in production, sitting close to the customers who depend on them. This is a full-stack engineering job with an unusually short distance between your code and someone's actual workday. You'll write Go and Python, design schemas, build evals, and present your solution to a senior executive at an enterprise - often in the same week. What You'll Do Design and ship production agents. You'll build agents that are mission-critical from day one: embedded in Teams, Slack, intranets, voice lines, and email, taking real actions against SAP, ServiceNow, Workday, and a long tail of systems nobody has heard of. These run at enterprise volume under enterprise scrutiny. Own the full lifecycle. Discovery, build, eval, launch, and the unglamorous months afterward where an agent goes from good to genuinely reliable. Work directly with the people whose problem it is. You'll sit with leaders at global enterprises, extract the process from their heads, and decide what should be an agent, what should be a workflow, and what should stay human. Push your work back into the platform. The best patterns you find in the field become part of Ema's core product

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. We believe that security should be monitored and verified continuously, including the security of your supply chain. The Vendor Risk Management (VRM) product was designed to provide software buyers with tools to evaluate the security of their vendors by inventorying vendors, prioritizing risks, automating security reviews and remediating findings. VRM or Third party Risk Management (TPRM) presents a massive opportunity for Vanta - representing a market of $5-$10B in ARR and a CAGR of 10.8% driven by secular tailwinds in the industry that requires more focussed and deeper scrutiny of the company’s supply chain. As a Senior Software Engineer with full stack focus, you’ll be responsible for driving complex projects across our technical stack and mentor our talented engineering team. Your past experience will be leveraged to accelerate the evolution of our Vendor Risk Management product and help software buyers continuously and comprehensively monitor risks across their vendor supply chain. Our business has found incredible product-market fit and has monetized effectively since the day we signed our first customer. We’re growing at a blistering pace, which presents career-defining opportunities for engineers to accelerate their growth and to contribute to a rapidly-scaling company. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. We’d love for you to join us! Visit our Vanta Engineering Blog to learn more about what our team is working on! What you’ll do as a Senior Software Engineer at Vanta: Lead complex, ambiguous projects end-to-end, partnering wit

We're looking for an ML Data & Platform Engineer to own the infrastructure that powers our speech AI models: the pipelines that source and prepare training data, and the platform that trains, evaluates, and serves them in production. Speech AI has a data problem most ML teams don't, and you'll be at the centre of solving it, working as part of our ML team to remove friction across the entire lifecycle and get better models into production faster. This is a broad, cross-functional role suited to someone who enjoys working across the full stack: data infrastructure, distributed systems, and production ML, and who takes ownership of problems end to end rather than waiting to be told what to fix. What you'll do Designing, building, and maintaining scalable data pipelines for ingesting, transforming, validating, and storing large datasets used to train our models Developing and maintaining web scraping and data acquisition solutions to keep training datasets fresh, high-quality, and available at scale Building and operating the infrastructure that lets the ML team deploy and evaluate new models quickly, and that serves models efficiently and reliably in production Optimising infrastructure for both iteration speed and production reliability, including GPU utilisation, job scheduling, and training efficiency Implementing observability (monitoring, logging, alerting) across data pipelines and ML systems to catch issues early and keep things running smoothly Troubleshooting complex issues across distributed systems, spanning data infrastructure, training, and inference Continuously improving our data and MLOps practices, and helping shape the roadmap for how our platform evolves as we scale What you'll need Strong proficiency in Python and SQL, with a solid backend or data engineering foundation Hands-on experience with containerisation and orchestration (Docker, Kubernetes), and working with a major cloud provider Experience building data pipelines and ETL/ELT processe

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! We’re looking for a senior engineer to help build, maintain and evolve the training framework that powers our frontier-scale language models. This role sits at the intersection of large-scale training, distributed systems, and HPC infrastructure. You will design and maintain the core components that enable fast, reliable, and scalable model training — and build the tooling that connects research ideas to thousands of GPUs. If you enjoy working across the full stack of ML systems, this role gives you the opportunity and autonomy to have massive impact. What You’ll Work On Build and own the training framework responsible for large-scale LLM training. Design distributed training abstractions (data/tensor/pipeline parallelism, FSDP/ZeRO strategies, memory management, checkpointing). Improve training throughput and stability on multi-node clusters (e.g., GB200/300, AMD, H200/100). Develop and maintain tooling for monitoring, logging, debugging, and developer ergonomics. Collaborate closely with infra teams to ensure our cluster, container environments, and hardware configurations support high-performance training. Investigate and res