Database Engineering Team Manager Jobs

Cloud Operations Engineers are responsible for building internal tools and process automation. Day-to-day duties are creating and monitoring systems alert dashboards, reviewing critical event and system logs, accessing customer instances that underpin their production databases, and performing server administration duties including performance troubleshooting. Applicants must be critical thinkers who are quick to detect, resolve, or escalate issues that are sometimes broad in scope and difficult to trace. We are looking for a Lead with strong technical leadership experience as well as technical depth who is looking to collaborate closely with Cloud Operations Engineering Management in building and maintaining a high-performing team that delivers high quality outcomes while fostering psychological safety and professional growth. We are looking to speak to candidates who are based in Dublin for our hybrid working model. Core responsibilities Team leadership: partner with and assist COE Management with the tasks of providing ongoing technical feedback to engineers, support their growth and creating an inclusive team environment Execution and delivery: play a key role in guiding team members through project deliverables ensuring high quality outcomes while also assisting in meeting or resetting timelines when required Time management: between assisting team members with day to day tasks ranging from incident to project management Cross-functional collaboration: work closely with Product, Technical Services and R&D to surface team’s pain points and drive alignment with the goal of providing an excellent user experience to the end customer Coordinate with Lead counterparts within Cloud Operations as well as Technical Services to ensure our uptime guarantees to the MongoDB Atlas customer base Assist and collaborate with the team on scoping, designing, deploying and ongoing maintenance of systems that focus on reducing mean time to resolve customer incidents Detec

About the Team The Storage teams build and operate online stateful systems and abstractions that are reliable, efficient, secure and easy to use for DoorDash Engineering. The teams are responsible for understanding Product Engineering’s evolving needs and developing platform and infrastructure capabilities to serve them. The team currently supports CockroachDB, Cassandra, Kafka and Redis as well as data abstraction services to reduce the complexity of interacting with storage systems for Product Engineers. About the Role The Storage team is building and operating a high-performance, scalable, and reliable data abstraction layer that optimizes both efficiency and reliability. Our goal is to create a platform that manages itself and fades into the background—empowering engineers to focus on delivering product experiences our customers love. This role is available across two teams within Storage, each solving unique and high-impact challenges: One team is building the orchestration layer for DoorDash’s storage platform—unifying lifecycle management, operations, and self-serve APIs for databases and streaming systems, turning complex, stateful infrastructure into reliable, developer-friendly services used across the company. One team builds and operates the distributed data platform powering DoorDash's largest stateful workloads -- including Cassandra, which backs critical product surfaces across DoorDash, Wolt, and Roo. You'll design high-throughput data abstractions, smart clients, and platform services that make distributed data reliable and easy to work with at multi-petabyte, multi-million-QPS scale, with opportunities to go deep on distributed systems internals and contribute to the open-source Cassandra ecosystem. If you're passionate about distributed systems, developer experience, and building foundational infrastructure at scale, we'd love to hear from you. You must be located in San Francisco, Sunnyvale, Seattle, or the New York Metro Area for this hybrid pos

About the job We are looking for a Software Engineer to join the Kapacity.io team at EnergyHub! Our team, made up of YC alumni (S21) and elite product and software talent, builds some of the most advanced flexibility solutions in the market. Kapacity.io , previously backed by Y Combinator and acquired by EnergyHub in 2024, focuses on the European energy market, offering an energy management platform to energy companies, allowing them to connect residential heat pumps, EVs and batteries to a Virtual Power Plant. EnergyHub is the leading residential Virtual Power Plant provider in North America, with over 2.5 million connected residential devices. Virtual Power Plants (VPP) allow energy companies to adjust their customers’ power consumption to reduce grid congestion and benefit from price volatility. VPPs reduce the need for peak power generation, reducing investment needs and carbon emissions of the grid. Residential users are compensated for participation with reduced energy costs and/or direct compensation. Join us in building high impact solutions for energy grid flexibility. If you’re a growth minded individual who has a passion for tech and energy, this team is for you! Here's what you'll do... Design, build, and maintain the software that sits at the core of Kapacity.io’s optimization products. Become a core contributor to our codebase, actively participating in work planning, retrospectives, and overall team improvement. Work directly with sales, translating business needs into viable technical solutions. We use Go, React, Typescript, Python, Django, PostgreSQL and Docker. We’re on AWS and communicate on Slack. Here's what we're looking for... We’re seeking a Software Engineer with 2+ years of experience developing and deploying production-quality software with experience in UI / UX development. Experience with UI / UX Typescript, Javascript Go(lang), python, docker, AWS Relational Databases (Postgresql) Adaptability and resilience when facing new, difficult a

Description: Graviton is a privately funded quantitative trading firm striving for excellence in financial markets research. We are seeking a Software Engineer for our team in Gurgaon. Our Core Technology team has some of the best programmers in India working on cutting edge technologies to build a super fast and robust trading infrastructure handling millions of dollars worth of trading transactions every day. Requirements Contribute to all layers of backend systems including databases, APIs and applications Design, build and maintain applications for business requirements Architect scalable and reliable applications Write clean and modular code, following good coding standards and practices Troubleshoot and debug applications Be involved in the entire application lifecycle Collaborate with multidisciplinary team of front-end developers, engineers and system administrators Devise innovative solutions to address new and complicated challenges Build reusable code and libraries for future use Take lead on projects, as needed Work in a high paced competitive environment Qualifications The ideal candidate will have: Engineering degree in Computer Science (preferred) or any other discipline from a Tier 1 college. 3 to 4 years of relevant experience in designing and improving information systems Proficiency in Python programming Extensive experience working with relational databases and handling large datasets Good Understanding of object oriented and asynchronous programming Familiarity with front-end languages such as HTML, JavaScript and CSS Knowledge of Linux systems and bash scripting Good communication and interpersonal skills Willingness to continuously learn and improve Ability to work in fast paced environment under pressure and manage multiple high priority projects Good to have: Experience in Financial services space/domain Experience in and understanding of system design decisions Experience in leading small teams or projects Benefits: Our open and casua

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done. Airtable’s infrastructure is evolving to meet the needs of our fast growing engineering org. We are looking for infrastructure engineers to join our team to help improve critical product infrastructure, with a focus on building systems that have a great developer experience and will scale as we grow. We currently have openings on: Asynchronous Serving: The Asynchronous Serving team is scaling critical systems used by Airtable’s most essential and up-and-coming product features, especially AI features. Upcoming projects include refactoring our background task queue to track its tasks in DynamoDB, adding quality of service to the job queue, and revamping a streaming service to handle 10x scale while being more resilient. Compute: The compute pod builds and manages our Kubernetes-based platform that supports every service at Airtable, including all new AI services such as vector databases, AI evals store, and document extraction and understanding services. We have a lot of exciting foundational work in our roadmap, such as Overhauling our network stack and service discovery, to simplify service setup and strengthen security Region level disaster recovery, and bringing up compute platform from 0->1 in a new region Building custom Kubernetes operators for reliably managing some of our most critical workloads Developer Platform : The Developer Platform team sits at the intersection of all engineering at Airtable, focusing on building the internal tooling, frameworks, and CI/CD systems that power our product teams. We strive to streamline developer workflows - from build and test cycles to production deployments—and foster a best-in-class developer experience. Join us if you’re passionate about creating high-lever

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 an Infrastructure Security Engineer to design and secure the core systems that power our platform. This role focuses on building security directly into our infrastructure—from container isolation and orchestration to identity and secrets management in a multi-tenant, cloud-native environment. You’ll work closely with engineering teams to define secure primitives and ensure our platform is resilient, scalable, and trustworthy by design. This is a hands-on, deeply technical role focused on real systems, not compliance or policy. What You'll Do: Platform & Runtime Security Design and improve isolation mechanisms for multi-tenant workloads (containers, sandboxing, execution environments) Strengthen boundaries between customers, workloads, and internal systems Identify and mitigate risks in distributed, dynamic compute environments Container &

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: Most of the value of owning a model shows up at serving time. We're building a platform that covers the whole life of an LLM -- train it, deploy it, observe it -- and inference is where teams feel the difference every day. We already run elastic inference, sandboxes, distributed volumes, and multi-node training, and we control the infrastructure underneath, so the serving stack is ours to shape rather than something we resell. You will do hands-on inference research at Modal, working with the research lead to pick high-impact bets and owning them end to end. The bets that matter most are the ones that move cost per token and tail latency on the workloads our customers actually run. What you'll do: Own end-to-end inference research bets: speculative decoding, disaggregated prefill/decode, quantization (FP8, INT4), KV-cache and memory management, autoscaling for spik

We deliver foundational systems that shape the future of how technology is used in a top performing quantitative equity fund that manages over $78+ billion USD in financial assets. This is a fantastic opportunity in the exciting intersection of finance and technology where investment decisions are made using technology. Quantitative equity funds use programmed investment strategies and as a result, our technology team is crucial to its success. The team is headquartered and deeply rooted in West Coast Vancouver. We place high value on maintaining an entrepreneurial spirit and creating a culture where each of us has opportunities to succeed. What You Will Do The technology infrastructure team plays an essential role through innovative technologies on our hybrid (on-premise and cloud based) platform: distributed computing, petabyte-scale data storage, containerization, non-traditional high-performance databases, process orchestration, monitoring, data visualization and DevOps. You own the entire technology infrastructure life cycle: Engineer and support software and systems infrastructure. Introduce new foundational technologies that advance our software engineering capabilities to the next level. Collaborate with our software development teams on support issues and improvements to our infrastructure tools, processes, and software. Act as a conduit between our application development teams, and IT, network security, and other stakeholders to align priorities and translate business requirements into technical designs. Improve systems infrastructure reliability. Gather and analyze metrics from operating systems and applications to assist in performance tuning, fault finding and business continuity planning. Design, plan and implement solutions in an entrepreneurial spirit. What You Bring Programming Knowledge – you have an undergraduate, graduate, or post-graduate degree in a computer-related field OR exceptional programming skills gain

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Everpure Data Intelligence (formerly 1touch.io) enables enterprises to discover, classify, and contextualize data across cloud, on-premises, and edge environments, improving AI accuracy, building trust in AI outcomes, reducing risk, and delivering measurable business impact. We are seeking a Professional Services Engineer to join a team working with some of the world’s largest financial services, healthcare, retail, government, and technology customers to help them understand and secure their data. WHAT YOU'LL DO Work with customers, usually via screen share, to configure Inventa software relative to their business needs and use cases. Drive adoption. Guide customers through technical setup, configuration, and integration Connect Inventa to various applications, including on-premises databases and file servers, cloud databases and file storage, SaaS applications, and data lakes. Accurately report project status to stakeholders. Troubleshoot connectivity, permissions, resource utilization, and other issues. Manage customer expectations by setting clear success criteria, fostering a collaborative attitude, and understanding platform capabilities. Deeply understand the product architecture and integrate external systems to Everpure Data Intelligence using APIs. Create and maintain technical documentation, FAQs, and knowledge base articles. Share insights with sales, success and product teams to improve processes and

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. About Modal Data: We’re growing our Data team and are looking for our first few key hires to build self-serve data tools and drive business strategy in the right direction. The mission of the Modal Data team is to make it easy to track company goals, make evidence-backed decisions, and prioritize the right work. We do this via: Self-serve AI analytics tools (Hex, Snowflake) Embedding with teams as a “data adviser”, providing strategic analysis and consulting What You'll Do: Contribute to building the most modern analytics stack in Data today to support AI-driven self-serve analysis, key metrics tracking, and external customer reporting Influence work on new products like LLM Inference Endpoints through product analytics tracking Identify millions of dollars of cost savings and optimization across our tools and financial operations Write data pipelines that power the operatio

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Through a combination of strategic partnerships and self-built campuses, we are scaling the compute, storage, and networking platforms that power frontier AI training and inference. The Scaling Analytics team builds the data and software systems that help Industrial Compute understand, plan, and operate infrastructure at global scale. We work across capacity, hardware, storage, infrastructure software, and operational systems to connect fragmented sources of infrastructure data and make that information reliable and usable for engineering and planning. As OpenAI's infrastructure footprint grows, CPU and storage data increasingly spans internal platforms, vendor systems, APIs, databases, object storage, capacity management systems, and operational tooling. Building reliable connections across these environments is critical to understanding available capacity, utilization, fleet state, and infrastructure growth. About the Role We are seeking a Data Engineer to build the data systems and integrations that connect OpenAI's CPU, storage, and supporting infrastructure platforms. This role sits at the intersection of data engineering and backend software engineering. Rather than focusing primarily on traditional analytical pipelines, you will build the software and integrations required to collect, normalize, and make infrastructure data available across a heterogeneous set of systems. CPU and storage data may originate from internal infrastructure platforms, vendor APIs, databases, object storage, capacity systems, and operational services. You will determine how to reliably connect these systems and where those integrations should live—whether within an existing infrastructure service, an orchestration framework, a scheduled workload, or a purpose-built application. You will work closely with Infrastructure Engineering, Capacity Engineering, Storage,

About the Team API Enterprise Controls is part of the API Infrastructure organization and owns the platform capabilities that help developers, startups, and enterprises adopt the OpenAI API securely and confidently. We build the systems underneath our APIs and developer platform across authentication and identity, service accounts and key management, secure networking, compliance, auditability, observability, and operational controls. Our users are developers and teams running critical applications on OpenAI, and we partner closely with Product, go-to-market, security, and infrastructure teams to turn their most important needs into reliable, intuitive platform capabilities. About the Role We are looking for an exceptional backend software engineer to help define and ship the enterprise capabilities our API Platform needs to scale.; this is a product-engineering role grounded in deep backend systems. You will work across databases, streaming systems, request routing, authentication, and developer-facing APIs while bringing strong product judgment, developer empathy, and attention to the small details that make a platform easier to understand, trust, and operate. You will lead large cross-functional initiatives, work closely with Product and go-to-market teams, engage directly with sophisticated users, and carry ambiguous needs from discovery through design, launch, and iteration. In this role, you will: Own backend product capabilities end to end across authentication and identity, service accounts and key controls, secure networking, compliance, observability, and operational workflows. Partner with Product, go-to-market, security, infrastructure teams, and sophisticated customers to identify needs, shape the roadmap, and lead large cross-functional projects from design through launch. Design developer-facing APIs, system behavior, configuration, error handling, safe defaults, auditing, and notifications with exceptional care for the details that define a great dev

AI agents are transforming the way developers interact with software - and databases are no exception. We're seeking a Senior Software Engineer to join our AI Interfaces team within AI Builder Experience (ABX), where you'll provide technical direction, shape architecture, and build the core products that make it seamless for developers and AI agents to work with MongoDB. Our team owns the surfaces through which humans and agents connect to MongoDB - including the MongoDB MCP Server, Agent Skills, our Intelligent Assistant Platform, and purpose-built agents. In short: if it's how an agent talks to MongoDB, we're building it. This is a new team charting new territory, and as a Senior Software Engineer here, you'll be right at the frontier - building the technologies that let AI applications and agentic workflows work seamlessly with MongoDB at scale. You'll integrate with fast-moving, often unproven technologies, make pragmatic calls in the face of ambiguity, and own high-visibility projects end to end with minimal guidance. We're looking for product-minded engineers who thrive on autonomy and take pride in shipping. MongoDB engineering teams pride themselves on building high-quality software and living our cultural values every day - we value intellectual curiosity and honesty, and building together in an environment that prioritizes collaboration over competition. This position requires participation in a 24/7 on-call rotation to ensure business continuity and incident response capabilities. This role can be based out of our Gurugram office. Position Expectations Work closely with research, product management, product engineering, product design, peers, as well as other teams within the company to define the first version and future evolution of our AI interfaces Design, build, and deliver well-tested core pieces of the platform - including the MongoDB MCP Server, Agent Skills, the Intelligent Assistant Platform, and purpose-built agents - in collaboration with othe

NVIDIA is a global leader in high-speed computer vision, artificial intelligence (AI), and deep learning. Our team develops data engineering solutions that empower AI developers in autonomous vehicle (AV) domains to innovate quickly and effectively at scale. Are you ready to take on a senior technical role in building high-performance AI data pipelines? We seek an exceptional individual to design and optimize microservices and data pipelines to process massive volumes of AV data and enable seamless data mining and AI training. The ideal candidate will bring expertise in big data processing and distributed computing to create efficient solutions and overarching architectures for challenges such as video data curation, behavioral search, and AI dataset management. What you'll be doing: Scope and build tools, microservices, workflows, and distributed applications to accelerate data mining and AI training. Design and implement solutions for streaming, resilience, logging, security, authentication, workflow orchestration, and data management. Deploy AI models. Design and develop Retrieval-Augmented Generation (RAG) workflows enabling hybrid and agentic patterns. Analyze and operationalize complex distributed systems for speed-of-light performance. What we need to see: Experience developing high-performance, scalable software systems. MS with 6+ years, or BS (or equivalent experience) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field. Strong programming skills in Python or Golang Proficiency in key technologies like Kubernetes, Helm, Hive, Parquet, SQL, vector databases, e.g., Milvus. Strong architectural skills with a proactive, problem-solving mentality. Experience in data mi

We are expanding our agentic AI capability and are looking for an AI Engineer to join the team. You will work alongside senior engineers to build and maintain AI systems — contributing to agentic pipelines, retrieval infrastructure, and the integrations that tie these systems together. This is a hands-on implementation role with real ownership of components. You will grow your skills in a fast-moving AI practice, working on production systems that directly affect client outcomes. What This Involves: Build and maintain agentic pipelines and workflows under the guidance of senior engineers: tool use, orchestration, and multi-step reasoning. Implement and tune RAG pipelines — including embedding, chunking strategies, vector retrieval, and retrieval evaluation. Contribute to memory and context layer components: integrating vector databases, supporting knowledge graph pipelines, and helping maintain state management across agentic systems. Write clean, well-tested Python code and participate in code reviews. Debug and improve existing AI systems based on evaluation results and production feedback. Collaborate with data engineers and domain experts to integrate AI components with upstream data sources and downstream applications. Document implementations clearly and contribute to shared internal tooling. Requirements: 2–4 years of software or ML engineering experience, with at least 1 year working with LLMs or AI systems in a professional setting. Working knowledge of LLM APIs (OpenAI, Anthropic, or similar) and at least one agentic or RAG framework (LangChain, LlamaIndex, or equivalent). Solid Python skills and comfort with software engineering basics: version control, testing, REST APIs. Familiarity with vector databases or embedding-based search. Curiosity about agentic AI — you follow developments in the space and are eager to apply new techniques. Excellent communication and collaboration skills — comfortable working across cross-functional and client-facing te