Lead Software Engineer Query Language Jobs

Join the Atlas Search Query team to design and develop the next generation of Search query architecture, optimization, and execution. Atlas Search is a growing cloud service that allows users to execute complex search and vector search queries using the MongoDB Query Language. Our users can focus on relevance and data retrieval instead of the machinery needed to search data at scale. Our team is building a cloud-based distributed system responsible for the core components of search including data ingestion, performance, query language, query execution, for both relevance-based search and vector search. Our product is being adopted quickly and there are many interesting projects. This is a technical role where you will be responsible for the success of complex Search Query feature development. We are looking to speak to candidates who are based in San Francisco, CA for our hybrid working model. What You’ll Do Lead complex projects across the MongoDB ecosystem, for instance, development of a new Search aggregation framework within the MongoDB aggregation framework. Set project level strategy, architect features, and lead projects to successful execution Identify, design, and implement features enhancing our query language, performance, and operability Perform code reviews with peers and make recommendations on how to improve our software development processes Influence and grow team members through active mentoring and leading by example What We Look For 5+ years experience in data management/search systems, ideally with a strong query processing and optimization background Experienced in the development and maintenance of stateful distributed systems Eager to shape the technological direction of a complex system and have the ability to lead initiatives through collaboration with others Experienced in debugging and profiling multithreaded applications written in Java and Rust Bonus: experience with designing high-volume query engines, such as a datab

MongoDB Search and Vector Search allows users to execute complex search queries and build RAG applications using the MongoDB Query Language. Our users are free to focus on relevance and data retrieval instead of the machinery needed to search data at scale. We are looking to speak to candidates who are based in Toronto for our hybrid working model. Candidate Profile: 5+ years of hands-on experience designing, building, testing, and maintaining industrial-strength backend software in a complex codebase Proficient in modern programming languages and techniques Experienced in developing distributed systems, cloud services, and SaaS products Excellent verbal and written technical communication skills; enthusiasm for collaborating closely with colleagues and mentoring other engineers A growth mindset and the desire to learn quickly through taking on challenges, reflecting on outcomes, and incorporating feedback A strong sense of ownership over their work, from initial design all the way through maintaining code in production You will: Build and design our integrated search platform, written in Java Work with a collaborative team that prioritizes sound technical decision-making and building systems that our customers love and that we are proud of as engineers Lead projects and own subsystems Help determine the team’s roadmap and the architecture of our system Success measures: In 3 months you’ll have contributed to the development of an existing project and completed several improvements or bug fixes In 6 months you’ll be reviewing code and project designs, and be an active participant in team meetings In 12 months you’ll have a thorough understanding of the systems the team owns and have led a project. You’ll have had a positive impact on our code, product, and team processes About MongoDB MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the data platform for the AI era, enabling builders to cr

Join the Atlas Search team to design and develop the next generation of Semantic and Vector Search infrastructure. Atlas Search is a growing cloud service that allows users to execute complex search and vector search queries using the MongoDB Query Language. Our users can focus on relevance and data retrieval instead of the machinery needed to search data at scale. Our team is building a cloud-based distributed system responsible for the core components of search including data ingestion, performance, query language, query execution, for both relevance-based search and vector search. Our product is being adopted quickly and there are many interesting projects. This is a technical role where you will be responsible for the infrastructure and features enabling our at-scale cloud service powering vector and semantic search. We are looking to speak to candidates who are based in the San Francisco Bay Area for our hybrid working model. What You’ll Do Lead complex projects across the MongoDB ecosystem, for instance, development of a new Search deployment framework within the MongoDB managed cloud Set project level strategy, architect features, and lead projects to successful execution Identify, design, and implement features enhancing our reliability, performance, security and efficiency Perform code reviews with peers and make recommendations on how to improve our software development processes Influence and grow team members through active mentoring and leading by example What We Look For 5+ years experience in data management/search systems, ideally with a strong distributed systems and infrastructure background Experienced in the development and maintenance of concurrent, stateful services Eager to shape the technological direction of a complex system and have the ability to lead initiatives through collaboration with others Experienced in writing features, debugging and optimizing multithreaded applications written in Java Familiarity with LLM

Atlas Search is a multi-cloud service that allows users to execute complex full text and vector search queries using the MongoDB Query Language . Our users are free to focus on relevance and data retrieval instead of the machinery needed to search data at scale. Our team is building the cloud-based distributed systems software responsible for the lifecycle of search indexes including: data ingestion, index building, partitioning, performance, availability, and backup management. Our product is quickly gaining traction with customers and we are making core architectural improvements that you will contribute to. This role is based in Toronto, ON hybrid. Successful candidates will have the following qualities: 2+ years of hands-on experience designing, building, testing, and maintaining industrial-strength backend software in a complex codebase Experience developing distributed systems and cloud services Experience with at least one modern statically typed programming language, and interest in working with Java Excellent verbal and written technical communication skills and enthusiasm for collaborating closely with colleagues A growth mindset and the desire to learn quickly through taking on challenges, reflecting on outcomes, and incorporating feedback A strong sense of ownership over their work, from initial design all the way through maintaining code in production You will: Contribute to the design, implementation, and support of projects that improve the scalability of Atlas Search to make using it a seamless experience for even the largest workloads Work with a collaborative team that prioritizes sound technical decision-making and building systems that our customers love and that we are proud of as engineers Have the opportunity to lead projects and own subsystems Provide input on the team’s roadmap and help determine the architecture of our system Success measures: In 3 months you’ll have a solid high-level understanding of what our team does and how we operate.

Atlas Search is a multi-cloud service that allows users to execute complex full text and vector search queries using the MongoDB Query Language . Our users are free to focus on relevance and data retrieval instead of the machinery needed to search data at scale. Our team is building the cloud-based distributed systems software responsible for the lifecycle of search indexes including: data ingestion, index building, partitioning, performance, availability, and backup management. Our product is quickly gaining traction with customers and we are making core architectural improvements that you will contribute to. We are looking to speak to candidates who are based in San Francisco, CA for our hybrid working model. Successful candidates will have the following qualities: 2+ years of hands-on experience designing, building, testing, and maintaining industrial-strength backend software in a complex codebase Experience developing distributed systems and multithreaded applications Experience with at least one modern statically typed programming language, and interest in working with Java Excellent verbal and written technical communication skills and enthusiasm for collaborating closely with colleagues A growth mindset and the desire to learn quickly through taking on challenges, reflecting on outcomes, and incorporating feedback A strong sense of ownership over their work, from initial design all the way through maintaining code in production You will: Contribute to the design, implementation, and support of projects that improve the scalability of Atlas Search to make using it a seamless experience for even the largest workloads Work with a collaborative team that prioritizes sound technical decision-making and building systems that our customers love and that we are proud of as engineers Have the opportunity to lead projects and own subsystems Provide input on the team’s roadmap and help determine the architecture of our system Success measures: In 3 months you’ll have a

ABOUT THE ROLE The Senior Software Engineer acts as the technical lead for an agile team, focusing on the design and development of scalable microservices for Peloton's core features across all platforms (Bike, Tread, Strength, and Digital). The Content AI Team is responsible for training and hosting various models in the domains of Natural Language Processing (NLP) and Automatic Speech Recognition (ASR). This role is highly collaborative, requiring close partnership with Product, Design, and QA throughout the development lifecycle. The candidate will be responsible for designing, developing, testing, deploying, and monitoring microservices that specifically power features like search, voice, and captions, which are crucial for platform expansion and international growth. In addition to technical delivery, excellent communication and engineering skills are essential for providing guidance to junior team members and effectively coordinating with other stakeholders, such as Technical Program Managers (TPM). YOUR DAILY IMPACT AT PELOTON Design, develop and operate business-critical APIs and services with a focus on high availability, low latency, security and scalability Mentor junior engineers in the team and communicate effectively with TPM and Product Write understandable, well tested code with an eye towards maintainability and scalability Architect and build reusable code, libraries, and patterns for use across teams Propose, experiment, and implement solutions to scale services while meeting business and product requirements. Leverage production monitoring/profiling/tracing and load testing tools to discover bottlenecks and using techniques such as data modeling, query optimization, and caching to address the bottlenecks Lead technical discussions during architecture meetings, design reviews, and task breakdown Identify common patterns as well as develop and foster development of reusable components and standards across teams Champion and implement industry

Join the Vector Search team and help build a cutting-edge vector database on top of MongoDB. Our team is responsible for the syntax and implementation of MongoDB's $vectorSearch aggregation, which enables approximate nearest neighbor queries over high-dimensional vectors. We are a small team with a large and rapidly growing customer base, providing engineers an opportunity to make a highly-visible, broad impact. When scaling search to billions of vectors, performance is paramount. We're looking for engineers who enjoy solving complex and open-ended problems that directly impact users' performance. This role is based in San Francisco, CA with a hybrid work model. You would get to: Implement new features within MongoDB's $search and $vectorSearch aggregation operators Work cross-functionally with Product teams to define new query and index syntax Identify and address performance bottlenecks in filter queries and nearest neighbor search Have the opportunity to lead projects and own subsystems Perform code reviews with peers, review technical designs, and mentor junior developers Ideally you will be: 3+ years of experience working on large-scale backend systems Experience writing high-performance applications in Java or another JVM language A growth mindset and the desire to learn quickly through taking on challenges, reflecting on outcomes, and incorporating feedback Passionate about optimization, code quality, and problem solving Bonus: experienced with Apache Lucene, vector databases, or high-throughput web services Success Measures In 3 months you'll have a solid high-level understanding of what our team does and how we operate You'll have contributed to the development of an existing project and completed several small improvements or bug fixes In 6 months you'll be reviewing code and project designs, and be an active participant in team meetings In 12 months you'll have a thorough understanding of the systems our team owns and have led a small project. You'll have

Envoy Global is a proven innovator in the global immigration space. Our mission combines our industry-leading tech platform with holistic service to streamline, simplify and expedite the immigration process for employers and individuals. We are looking for a highly skilled Lead Software Engineer to join our team on a full-time, permanent basis. In this role, you will lead the design and implementation of robust, scalable systems, provide technical direction to the team, and take ownership of end-to-end delivery. You will play a key role in building high-quality solutions across APIs, microservices, and integrations, while driving engineering excellence and best practices. As our Lead Engineer, you will be required to: Design, code, and unit test platform and integration components Develop frameworks for standardizing and enabling data flows via APIs, files, microservices, and message queues. Provide technical guidance to the team and take ownership of delivery Responsible to technically groom backlog items providing design, architecture, and implementation details Quality is the key driver to product engineering, ensure highly testable and quality deliverables To apply for this role, you should possess the following skills, experience and qualifications: Minimum 8+ years of strong programming experience on .NET platform, Microsoft Tech Stack Expertise in C#, ASP.NET Web API / Typescript / Angular (or any front-end framework or passion to learn Angular) Experience developing with containers, micro-services, and message queues Dedication to delivering high-performance, secure and scalable services Experience working with a wide variety of systems and integrating APIs from third parties Hands on experience with SQL and query optimization Analytical and troubleshooting skills to investigate and resolve issues Ability to dig through Memory, CPU and IO bottlenecks to improve performance and scalability Azure experience is a plus Knowledge and experience

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Baseten is building its own GPU infrastructure for large-scale inference. As we move into large scale, high-density NVIDIA systems, the hardest failures are intermittent, cross-layer, and difficult to prove: RoCE congestion, InfiniBand stalls, ECN/DCQCN mis-tuning, bad optics, RNIC issues, host kernel stalls, GPU driver problems, and workload symptoms that look like network problems, but are not. We are hiring a Lead Software Engineer to build a first-class observability and root-cause analysis system for GPU fabrics. This is a hard distributed systems problem, not a dashboarding problem. The system will collect high-volume signals from switches, hosts, active probes, and inference services; reduce and correlate them in real time; understand topology and service ownership; and produce actionable diagnosis while an incident is still unfolding. This role sits at the boundary between networking and inference software. RDMA data paths, GPUDirect transfers, prefill/decode disaggregation, KV cache movement, request routing, and workload backpressure can all create fabric symptoms or hide real fabric failures. The goal is to tell an operator, quickly and with evidence, whether an incident is caused by the fabric, host, NIC, GPU, RDMA path, scheduler, or serving layer — and what to do next. EXAMPLE INITIATIVES Real-time telemetry engine — Build the ingestion, reduction, storage, and query path for high-cardinality fab

We're looking for a Staff Engineer to join the Logs organization at Datadog and help redefine how our customers ingest, query, and derive insights from logs data. In this role, you’ll work closely with Product Managers and customers to drive complex initiatives across ingestion pipelines, search infrastructure, and intelligent log management capabilities - all while pushing the boundaries of what’s possible with AI and distributed systems. You’ll have the opportunity to lead efforts that shape the future of log management. 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: Partner with Product Managers to define ambiguous product requirements and determine the most impactful solutions for customers Lead technical strategy and execution and design systems surrounding log query performance and ingestion at scale. Explore and prototype new capabilities and collaborate with peers on initiatives spanning AI-powered log management, security and business operations, advanced query capabilities, and external data sources query capabilities. Mentor engineers across levels and contribute to growing a high-performing, collaborative team culture Who You Are: You have deep experience architecting and scaling backend systems, with a strong focus on data-intensive or distributed infrastructure You excel in ambiguous environments, demonstrating a mix of drive, curiosity and pragmatic decision-making You’ve partnered effectively with Product Managers and customers to define product direction and ship impactful features You have expertise in debugging complex systems and optimizing performance across real-time data pipelines You have experience in using AI agents tools in your day-to-day engineering practices You lead by example and enjoy helping others grow through m

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role The Events Analytics Platform (EAP) team is responsible for the infrastructure that powers all of Sentry's time-series data and searching capabilities across billions of events with sub-second latency. We started this initiative by building Snuba, the primary storage and query service for Sentry's event data powered by ClickHouse, and we are now focused on unlocking deeper visibility and reporting across the terabytes of event data our users generate. As a Senior Software Engineer, you will lead efforts to push the boundaries of data visibility at Sentry. You will do this by expanding the capabilities of our search infrastructure, building new capabilities on top of our state-of-the-art storage layer and increasing the performance and integrity of Sentry’s core data services. You will also help shape Infrastructure's technical direction at Sentry and collaborate with Product and other Engineering teams to turn that vision into a reality. If you want to solve the hard problems that come with scaling event data into the petabyte range, this could be the job for you. In this role you will: Expand EAP's ability to deliver data at world-class speed and reliability. Architect and automate services and systems to scale reliably under growing demand. Make architectural trade-offs that balance product requirements with engineering constraints. Maintain and grow the team's code quality initiatives by regularly reviewing code and contributing to design decisions. Lead design and discussions around deliverables the team is working towards. Improve the maintainability and developer experience of the codebases EAP owns. Exa

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role The Events Analytics Platform (EAP) team is responsible for the infrastructure that powers all of Sentry's time-series data and searching capabilities across billions of events with sub-second latency. We started this initiative by building Snuba, the primary storage and query service for Sentry's event data powered by ClickHouse, and we are now focused on unlocking deeper visibility and reporting across the terabytes of event data our users generate. As a Senior Software Engineer, you will lead efforts to push the boundaries of data visibility at Sentry. You will do this by expanding the capabilities of our search infrastructure, building new capabilities on top of our state-of-the-art storage layer and increasing the performance and integrity of Sentry’s core data services. You will also help shape Infrastructure's technical direction at Sentry and collaborate with Product and other Engineering teams to turn that vision into a reality. If you want to solve the hard problems that come with scaling event data into the petabyte range, this could be the job for you. In this role you will: Expand EAP's ability to deliver data at world-class speed and reliability. Architect and automate services and systems to scale reliably under growing demand. Make architectural trade-offs that balance product requirements with engineering constraints. Maintain and grow the team's code quality initiatives by regularly reviewing code and contributing to design decisions. Lead design and discussions around deliverables the team is working towards. Improve the maintainability and developer experience of the codebases EAP owns. Exa

We are looking for a Senior Software Engineer to help us take REDAPL, our Referential Data Platform, to the next level. REDAPL is Datadog's main platform for tracking our customers' infrastructure resources and relationships. The platform enables products where customers can understand, keep track of, and gain insights into their infrastructure related to performance, cost, security, and more. Many Datadog products use REDAPL today such Cloud Security Posture Management, Resource Catalog, Cloud Cost Management, and Service Catalog and others - REDAPL ingests more than 4.5mil updates/second. As a Senior Engineer, you will drive, lead and collaborate on projects both inside and outside the platform. You can expect to contribute to key technical decisions relating to our data ingestion, processing, and query pipelines. 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: Build a query engine that supports efficient relationship traversals for our most demanding workloads. Contribute to design and drive high-priority, high-visibility projects to increase the platform's value, resilience, and scalability across multiple teams. Lead and guide other engineers through architectural platform decisions Identify potential system risks and trends in reliability and design solutions to address them Provide input on prioritizing engineering-led initiatives in short- and long-term planning and roadmaps Collaborate with internal product teams to understand their requirements and how we plan for their product growth as they integrate and depend on REDAPL Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent experience You have worked extensively with multiple types of data stores You have contributed to in

We are looking for a Senior Software Engineer to help us take REDAPL, our Referential Data Platform, to the next level. REDAPL is Datadog's main platform for tracking our customers' infrastructure resources and relationships. The platform enables products where customers can understand, keep track of, and gain insights into their infrastructure related to performance, cost, security, and more. Many Datadog products use REDAPL today such Cloud Security Posture Management, Resource Catalog, Cloud Cost Management, and Service Catalog and others - REDAPL ingests more than 4.5mil updates/second. As a Senior Engineer, you will drive, lead and collaborate on projects both inside and outside the platform. You can expect to contribute to key technical decisions relating to our data ingestion, processing, and query pipelines. 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: Build a query engine that supports efficient relationship traversals for our most demanding workloads. Contribute to design and drive high-priority, high-visibility projects to increase the platform's value, resilience, and scalability across multiple teams. Lead and guide other engineers through architectural platform decisions Identify potential system risks and trends in reliability and design solutions to address them Provide input on prioritizing engineering-led initiatives in short- and long-term planning and roadmaps Collaborate with internal product teams to understand their requirements and how we plan for their product growth as they integrate and depend on REDAPL Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent experience You have worked extensively with multiple types of data stores. You have contribute

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About Dynamic Tables Dynamic Tables (DTs) are Snowflake's declarative streaming transformation primitive. Customers define a SQL query and a freshness target; Snowflake handles the rest: orchestrating refreshes, maintaining snapshot consistency across a DAG of dependencies, and automatically incrementalizing the computation so that cost scales with what changed. Dynamic Tables is one of the fastest growing products at Snowflake and is a core part of Snowflake’s Data Engineering strategy. The Dynamic Tables performance team is responsible for making incremental refresh fast, predictable, and cost-efficient across increasingly complex query shapes. As a Staff Engineer on this team, you will own the technical direction for critical performance initiatives and be a force multiplier for the engineers around you. What You'll Do Lead the design and implementation of performance improvements to the incremental view maintenance engine, including multi-join incrementalization, novel incrementalization semantics, incremental window functions, and stacked operations. Help define the roadmap for the incremental view maintenance engine, identifying key performance, scalability, and correctness milestones, prioritizing high-impact enhancements, and aligning technical investments with prod