Database Engineering Team Manager Jobs

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: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Requirements: 5+ years of experience writing high-quality production code Experience building high-performance distributed systems at a large scale (the more battle scars, the better) Strong cloud skills Strong knowledge of low-level operating system foundations (Linux kernel, file systems, containers, etc.) Experience with performance engineering (tell us a story of when you shaved off a few milliseconds!) Ability to work in-person in our Stockholm office. Prior experience with Rust is nice to have, but not required. Ability to participate in on-call rotation and respond to production incidents.

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: We're looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads

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: We're looking for engineers with deep AI/ML and low-level systems experience who want to build the best technical support experience in the world. This isn't a traditional support role — it's an engineering role where you happen to be closest to our customers. You'll split your time roughly 50/50 between working directly with customers and shipping fixes, features, and automation that improve Modal for everyone. When you help a customer debug a training run, you'll also fix the underlying issue in the platform. When you notice ten customers hitting the same friction point, you'll build the tooling or automation that eliminates it entirely. This role is for people who solve problems, not people who answer tickets. The problems you encounter are deeply technical and arise from running some of the most demanding AI workloads in the world. You'll be a member of our eng

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: We are looking for PhD research interns with strong research experience in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This internship is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustness in high-stakes real-world deployments. Preferred Qualifications: Currently pursuing a PhD in computer science, machine learning, or a related field. A demonstrated record of research in reinforcement learning, machine learning, foundation models, or related areas. Experience developing and evaluating large-scale models or machine learning systems. Familiari

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: We're looking for a Growth Engineer to own the technical foundation of Modal's marketing and developer-facing web surfaces: the marketing site, docs site, growth landing pages, high-profile microsites, forms, analytics instrumentation, and the integrations that help users discover, understand, and get started with Modal. This is a frontend-heavy role for someone with strong product taste, web engineering craft, and a business-owner mindset. You'll partner with Product Engineering, Design, Data, and Growth to ship polished, measurable web experiences from high-profile projects like the GPU Glossary and LLM Engine Advisor to internal tooling that helps teams publish content faster. When this role is going well, Modal launches new pages, docs experiences, campaigns, and experiments quickly without sacrificing performance, craft, or measurement. In this role you will:

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: We're looking for a Detection & Response Engineer to build the systems that help us identify, investigate, and respond to threats across our platform. This is an engineering role focused on automation. You'll build detections, investigation tooling, and response capabilities that scale with our infrastructure, using AI where it meaningfully improves signal, investigation speed, and operational effectiveness. You'll work closely with infrastructure, platform, and security engineers to ensure every incident makes the platform more resilient. What You'll Work On: Detection Engineering Design and build high-fidelity detections for attacks, abuse, and anomalous behavior across our infrastructure and production systems Continuously improve detections based on telemetry, threat intelligence, and lessons learned from incidents Improve visibility across cloud infrastruc

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: We're building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. What you'll do: We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This role is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustnes

Senior Product Engineer Engineering Prolific Prolific is not just another player in the AI space – we are the architects of the human data infrastructure that's reshaping the landscape of AI development. In a world where foundational AI technologies are increasingly commoditized, it's the quality and diversity of human-generated data that truly differentiates products and models. The role We’re looking for impact-focused Software Generalists to join our specialized team focused on serving frontier model creators and enterprise AI application developers. As a full-stack engineer, you will work across Prolific’s domains to solve customer and product problems. This is an exciting opportunity to work directly with frontier AI companies, making critical technical decisions that balance scrappy startup execution with scalable, reliable engineering, as Prolific revolutionizes research for the AI community. You'll will have regular in person collaboration with customers and our US team, as well as collaborate closely with our UK-based tech teams. This role is hybrid based out of our New York office, approx 1-2 days a week. What you’ll bring to the role Over 4 years of experience in a product engineering role Can translate business concepts into software models Ability to quickly learn and adapt across the breadth of Prolific’s domains Familiar working in both monoliths and distributed systems Strong communication and collaboration skills for direct customer interaction Good understanding of modern web applications and architecture design patterns Experience supporting applications in production environments Judgment to balance scrappy startup execution with scalable, reliable engineering Comfort with rapid iteration and responding to customer queries with urgency Experience with some of our technology stack: Python (we use Django & Fast API) TypeScript and JavaScript (we use Vue.js) SQL and NoSQL databases (we use MongoDB and PostgresSQL) Building an

At Bolna, we’re building tools that change how businesses leverage voice AI. We’re looking for a Software Engineer to build reliable, scalable systems that power millions of production conversations across languages, industries, and telephony environments. This is a high-impact, high-ownership role where you’ll work on core platform problems across distributed systems, real-time communication, developer infrastructure, and customer-facing products. Our team includes IIT alumni with experience at Bain, Atlassian, Uber, Zomato, and LinkedIn, and is backed by leading investors. Responsibilities Build systems that operate at scale: Design and build backend services that support high-volume, real-time voice AI conversations with strong reliability, performance, and fault tolerance. Own features end to end: Take problems from product requirements and technical design through implementation, testing, deployment, monitoring, and iteration. Improve platform reliability: Build systems that are observable, resilient, and easy to debug. Identify bottlenecks, reduce failure rates, and improve system availability. Work on real-time infrastructure: Solve problems across telephony, streaming audio, webhooks, queues, scheduling, concurrency, and low-latency communication. Build for developers and customers: Improve APIs, SDKs, integrations, dashboards, and internal tools that make the Bolna platform easier to use and operate. Raise the engineering bar: Contribute to technical design reviews, code quality, testing standards, documentation, incident response, and engineering best practices. Required Skills Strong engineering fundamentals: Solid understanding of data structures, algorithms, databases, networking, operating systems, and distributed systems. Backend development experience: 2+ years of experience building and operating production backend systems using Python, Go, Java, Node.js, or a similar language. Production ownership: Experience shipping software to production and own

Instawork is on a mission to create meaningful economic opportunities for skilled hourly professionals in communities around the globe. Our AI-powered labor marketplace helps local businesses scale, and enables global technology companies to push the frontiers of robotics and AI. Backed by world-class investors like Benchmark, Spark Capital, Craft Ventures, Greylock, Y Combinator, and others, we’re looking for exceptional talent to reimagine the way the world works. Check out our Engineering blog here Who You Are: 5–8 years building and shipping high-traffic web or mobile apps in production. Strong coding and problem-solving skills. While experience with our stack (Python/Django, Celery, MySQL, Redis, ElasticSearch, React Native) is preferred, it's not mandatory. Proficiency in frontend technologies like React, Redux, and Responsive Design Systems. Experience in system design, distributed systems, and both relational and No-SQL databases. What You'll Do: End-to-end design, development, and deployment of high-scale web and mobile features. Prioritizing the highest ROI work—move quickly on the projects that matter most. Tackling large, complex software projects and delivering them on aggressive timelines. Maintaining peak team productivity: juggle multiple priorities in a fast-paced environment. Partnering with PMs and designers to choose the simplest, most maintainable solution. Raising the bar through thoughtful code reviews and clear technical feedback. Perks: Free snacks Health Insurance Personal Insurance Flexible Hours Maternity/Paternity Leave Broadband Reimbursement #LI-SS3 Our Values Empathy, Trust & Candor We put ourselves in the shoes of our colleagues and customers and don’t shy away from uncomfortable conversations, instead building trust through honest and direct feedback. Bias for Action We practice high-velocity decision-making, clear-eyed that we often operate with incomplete information. Growing quickly means it’s OK to be wrong, so l

About the Team At OpenAI, we’re building safe and beneficial artificial general intelligence. We deploy our models through ChatGPT, our APIs, and other cutting-edge products. Behind the scenes, making these systems fast, reliable, and cost-efficient requires world-class infrastructure. The Caching Infrastructure team is responsible for building a caching layer that powers many critical use cases at OpenAI. We aim to provide a high-availability, multi-tenant cache platform that scales automatically with workload, minimizes tail latency, and supports a diverse range of use cases. We’re looking for an experienced engineer to help design and scale this critical infrastructure. The ideal candidate has deep experience in distributed caching systems (e.g., Redis, Memcached), networking fundamentals, and Kubernetes-based service orchestration. In This Role, You Will: Design, build, and operate OpenAI’s multi-tenant caching platform used across inference, identity, quota, and product experiences. Define the long-term vision and roadmap for caching as a core infra capability, balancing performance, durability, and cost. Collaborate with other infra teams (e.g., networking, observability, databases) and product teams to ensure our caching platform meets their needs. You Might Thrive In This Role If You: Have 5+ years of experience building and scaling distributed systems, with a strong focus on caching, load balancing, or storage systems. Have deep expertise with Redis, Memcached, or similar solutions, including clustering, durability configurations, client-side connection patterns, and performance tuning. Have production experience with Kubernetes, service meshes (e.g., Envoy), and autoscaling systems. Think rigorously about latency, reliability, throughput, and cost in designing platform capabilities. Thrive in a fast-paced environment and enjoy balancing pragmatic engineering with long-term technical excellence. About OpenAI OpenAI is an AI research and deployment company d

MongoDB is launching an EMEA AI Natives team to win high-potential, fast-growing AI-native companies and accelerate new-logo acquisition. We are seeking a Regional Director, AI Native to build and lead an initial team of five Acquisition reps covering a number of regions across EMEA. Reporting to EMEA Sales Leadership, you will own the team’s strategy, hiring, development, execution, and results. You will drive new-logo acquisition and NARR while establishing a repeatable sales motion for the AI-native segment. We are looking to speak to candidates who are based in London for our hybrid working model. What you will do Recruit, onboard, coach, and develop a high-performing AI Native acquisition team Define territory plans, account priorities, pipeline goals, and operating rhythms across EMEA Build a data-driven go-to-market strategy for high-potential, well-funded AI-native companie. Engage founders, investors, C-suite leaders, engineering executives, and technical decision-makers Coach the team through complex, multi-stakeholder sales cycles and negotiations Lead strategic opportunities and help the team win net-new logos Own performance against new-logo, NARR, pipeline, and forecast objectives Drive adoption of MongoDB’s sales methodology, including MEDDIC Partner with Marketing, Product, Solution Architecture, Customer Success, Partners, and Sales Operations Provide market feedback to shape MongoDB’s AI Native strategy and scale the pilot What you bring 2 years of experience managing a quota-carrying sales team or 3+ years of experience as a quota-carrying enterprise sales representative A strong record of overachievement and winning net-new logos Experience building a new market, segment, territory, or sales motion Success selling complex technology to executive and technical stakeholders Understanding of cloud, databases, software development, and emerging AI technologies Ability to translate technical concepts into clear business value Strong coaching, fo

Your challenge As an Integration Consultant, you focus on the technical analysis and implementation of our integration solutions into our customer’s business systems. Together with our integration architects, your contributions assist with delivering high-quality, fully-tested, and documented solutions by integrating our solution with enterprise systems such as SAP. You are responsible for: Designing and implementing integration workflows. Writing integration scripts. Designing and executing data mapping, data modeling, and data loading. Developing specifications. Analyzing customer needs. Performing testing. Developing integration solutions. About you Essential talents and qualifications: A Master’s degree in Computer Science, Mathematics, Industrial Engineering, or similar. A solid background in IT. 1-3 years of experience in systems integration implementations, troubleshooting, or support. Hands-on experience in building complex integrations with a broad variety of application types and technologies. Great analytical and problem-solving skills. A customer-oriented and results-committed attitude. Passionate about working in a multinational, customer-driven environment. A team player who can also work independently. Fluent in English. Willingness to travel. Bonus points if you have: Knowledge of or experience with SAP (PP and MM). Integration experience with enterprise systems like SAP or Blue Yonder. Experience with communication protocols for SAP (through BAPI / RFC), databases, and files. Web services technologies such as HTTP, SOAP, and REST (based APIs). Middleware such as SAP PO and SAP PI. Experience with MES/WMS. Proficiency in data communication or transformation techniques. Hands-on experience in designing, building, testing, debugging, deploying, and managing APIs and integrations. Experience with ETL tools. Technical knowledge of SQL, R, JavaScript, Python, etc. Soft skills · C

ABOUT THE ROLE Scale Peloton’s $1B+ e-commerce platform as a Senior Full Stack Software Engineer on the E-Commerce Subscriptions team. You will drive the technical roadmap for high-impact features in close partnership with Product, Design, Marketing, and International teams. If you excel across the full stack, champion engineering excellence, and thrive in a dynamic, high-growth environment, this is your opportunity to shape the future of fitness tech. YOUR DAILY IMPACT AT PELOTON Design and deliver scalable, performant microservices and modern, high-conversion front-end web experiences Set the bar for code quality, testability, and system performance while driving architectural decisions, design docs, and cross-team alignment Lead pair programming, whiteboard sessions, and task breakdowns, while conducting empathetic, constructive code reviews that foster a culture of learning Work directly with product and business stakeholders to evaluate technical trade-offs and drive informed product decisions YOU BRING TO PELOTON 6+ years of software development experience with proficiency in JavaScript/TypeScript (React preferred, Vue), server-side languages (Python, Kotlin), and relational databases (PostgreSQL) 3+ years designing and scaling reliable, modern systems, supported by modern deployment tools (Kubernetes, Docker, GitHub Actions) Grounded in Agile, Lean, DevOps, and SRE principles, with a strong focus on quality, detail, and continuous learning in a fast-paced environment BONUS Experience with e-commerce, subscriptions, payment processing, cloud infrastructure (AWS/GCP), or microservices architectures Familiarity with TDD, DDD, Event Sourcing, or internationalization (i18n) Active engagement in the software community via open-source contributions, meetups, or conferences #LI-KN1 #LI-Hybrid The base salary range represents the low and high end of the anticipated salary range for this position based at our New York City headquarters. The actual base salary offered f

Your challenge As an Integration Consultant, you focus on the technical analysis and implementation of our integration solutions into our customer’s business systems. Together with our integration architects, your contributions assist with delivering high-quality, fully-tested, and documented solutions by integrating our solution with enterprise systems such as SAP. You are responsible for: Designing and implementing integration workflows. Writing integration scripts. Designing and executing data mapping, data modeling, and data loading. Developing specifications. Analyzing customer needs. Performing testing. Developing integration solutions. About you Essential talents and qualifications: A Bachelor’s or Master’s degree in Computer Science, Mathematics, Industrial Engineering, or similar. A solid background in IT. 1-3 years of experience in systems integration implementations, troubleshooting, or support. Hands-on experience in building complex integrations with a broad variety of application types and technologies. Great analytical and problem-solving skills. A customer-oriented and results-committed attitude. Passionate about working in a multinational, customer-driven environment. A team player who can also work independently. Fluent in English. Willingness to travel. Bonus points if you have: Knowledge of or experience with SAP (PP and MM). Integration experience with enterprise systems like SAP or Blue Yonder. Experience with communication protocols for SAP (through BAPI / RFC), databases, and files. Web services technologies such as HTTP, SOAP, and REST (based APIs). Middleware such as SAP PO and SAP PI. Experience with MES/WMS. Proficiency in data communication or transformation techniques. Hands-on experience in designing, building, testing, debugging, deploying, and managing APIs and integrations. Experience with ETL tools. Technical knowledge of SQL, R, JavaScript, Python, etc. Soft skills ·