Laser Design Engineer Jobs

Come join the Server Ingress Security team, where we are rearchitecting MongoDB Server’s ingress networking to make MongoDB clusters even more secure. This new team is building the Atlas Network Protection layer, a set of performant, security-critical services that harden MongoDB's pre-authentication attack surface and provides the ability to respond rapidly to emergent threats. We are looking for talented Senior Engineers to join the team and be founding members, where you will play a crucial role in our multi-year roadmap. Our team champions a strong culture of inclusivity, diversity, and collaboration. If you want to work on a collaborative team that applies security and systems engineering fundamentals to protect a popular database at scale, join us! We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model. Candidate Profile 5+ years of experience building production-quality systems software Experience with large backend/compiled codebases and performance-sensitive software, preferably in Rust Bonus points for experience working hands-on in security-sensitive or networking-adjacent domains Strong systems fundamentals, including multi-threaded programming and performance profiling. Bonus points for: Understanding of network protocols, TLS, and connection lifecycle management Familiarity with security concepts such as attack surface reduction, input validation, memory safety, and defense-in-depth architectures Excellent verbal and written technical communication skills, with a strong desire to collaborate with colleagues Strong time management skills and the ability to realistically assess project complexity B.Sc. in Computer Science or a related field, or equivalent practical experience, with strong competencies in data structures, algorithms, and software design/architecture. Interest in the theory and practice of high-availability, security-critical systems Position Expectations Design, implement, and operate production

Come join the Server Ingress Security team, where we are rearchitecting MongoDB Server’s ingress networking to make MongoDB clusters even more secure. This new team is building the Atlas Network Protection layer, a set of performant, security-critical services that harden MongoDB's pre-authentication attack surface and provides the ability to respond rapidly to emergent threats. We are looking for talented Staff Engineers to join the team and be founding members, where you will play a crucial role in our multi-year roadmap. Our team champions a strong culture of inclusivity, diversity, and collaboration. If you want to be a key technical leader on a collaborative team that applies security and systems engineering fundamentals to protect a popular database at scale, join us! We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model. Candidate Profile 10+ years of experience building production-quality systems software with a large user base, robust design structure, and rigorous code quality Experience with large backend/compiled codebases and performance-sensitive software, preferably in Rust Bonus points for experience working hands-on in security-sensitive or networking-adjacent domains Strong systems fundamentals, including multi-threaded programming and performance profiling. Bonus points for: Understanding of network protocols, TLS, and connection lifecycle management. Familiarity with security concepts such as attack surface reduction, input validation, memory safety, and defense-in-depth architectures. Excellent verbal and written technical communication skills for communicating to a wide variety of audiences ranging from junior engineers to executive stakeholder Strong mentorship skills, and excitement about leveling up your peers and teammates through coaching, feedback, and enablement Strong time management skills and the ability to realistically assess project complexity B.Sc. in Computer Science or a related

About Druva Druva is the resilience foundation for the AI enterprise, helping organizations secure and recover from connected risk across data, cyber, identity, and AI. The Resilience Cloud is a fully managed, cloud-native SaaS platform that delivers air-gapped and immutable protection across cloud, SaaS, on-premises, endpoint, and edge environments. Powered by Dru MetaGraph, Druva’s graph-powered intelligence layer, the platform connects critical business context so customers can understand risk, respond faster, recover cleanly, and govern data with greater confidence. Trusted by nearly 7,500 customers, including 75 of the Fortune 500, Druva helps safeguard the critical information and systems businesses depend on in an increasingly connected world. Visit druva.com and follow us on LinkedIn , X and Facebook . The Data team within Foundation processes data at scale. It builds and operates tools that scan petabytes of data to extract insights. The team builds indices and views for semi-structured data to facilitate analytics, using both in-house and off-the-shelf tools. . The team diligently keeps track of newer services, storage tiers, and various aspects of existing AWS services to take advantage of the continuous evolution of services and use them effectively in the background. As a Sr. Software Engineer, you will be providing technical leadership to create high-quality software by owning low level , design and implementation of services within a product. This role will require excellent communication skills as you will collaborate with Product Management to refine requirements, product architects to propose design changes, and other product owners to drive features to completion with good quality. Key Skill AI first mindset to software development, having experience using genAI during various phases of software development lifecycle from design to code to test using tools like 'cursor' 5-7

MeltPlan | Planning Engine for the Built Environment MeltPlan is building the “planning engine” for the $14 Tn construction industry, an AI system designed specifically to optimize decisions before construction begins. While design software optimizes use and aesthetics and construction software optimizes execution and control, MeltPlan is building the missing layer - software that optimizes decisions and tradeoffs upstream, before scope is locked, procurement begins, and change orders become inevitable. MeltPlan’s long-term goal is to help teams make construction “boring” by making planning more intense: surfacing constraints and tradeoffs early, aligning stakeholders before plans are frozen, and reducing the need for late-stage redlines, rework, and change orders. MeltPlan is founded by operators who have built at scale. Kanav previously co-founded Innovaccer, a $3Bn health-tech company focused on making US healthcare more affordable and accessible. He’s now applying that systems-level thinking to construction.He’s joined by Tanmaya Kala, former Project Executive at DPR Construction, who led large commercial, healthcare, and life sciences projects. We combine deep tech scale with real construction execution. What This Role Really Is Code writing is a commodity. We’re not hiring someone to close tickets. We’re hiring someone who: Is biased toward building Thinks in systems Designs for scale and resilience Reviews architecture, not just PRs Can move fast without creating long-term mess You’ll ship products daily. You’ll also help shape the system so it doesn’t collapse under growth. What You’ll Do Build end-to-end features (DB → API → UI) Design scalable data models and backend architecture Ship clean, production-grade frontend experiences Review and improve system design decisions Work directly with founders on product direction Help define engineering standards as we scale What We’re Looking For Strong backend fundamentals (APIs, databases, performance, system desi

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. ABOUT THE ROLE: SpaceXSI is building at a furious pace with the latest compute and switching hardware to help people understand the universe. We are looking for exceptional ML Infrastructure Engineers with deep expertise in high-speed interconnect technologies to design, build, and optimize the network fabric that powers large-scale AI training and inference clusters. This strategic role will drive innovation in high-bandwidth, low-latency, power-efficient interconnects critical for AI/ML clusters based on advanced computing platforms. You will have the opportunity to work on all modalities of interconnects connecting GPUs and switches both inside and between data centers, including our primary front and backend networks that train Grok and that customers use for inference. Engineers will own all aspects from design and development to build and operations. You will be expected to define and improve team processes and to contribute to scaling and maintenance efforts. You will focus on the physical layer and system-level integration of copper (ACC, AEC, CPC) and optical (FRO, LRO/TRO, LPO, AOC, CPO) interconnects that directly determine the performance, power efficienc

About the Team The Agent Infrastructure team at OpenAI is responsible for building systems that enable training and deployment of highly useful AI agents, both internally and for the world. We work hand-in-hand with researchers to design and scale the environment in which agentic models are trained – providing a workspace for AI models to execute code, debug issues, and develop software just as human SWEs do. Our training environment for agentic models operates at an extremely high scale and has the flexibility to emulate any environment in which an agent might work. At the same time, our team builds and maintains OpenAI’s core platform for the deployment and execution of agents in production. Our systems power products such as Codex, Operator, tool use in ChatGPT, and future agentic products. Some of the most challenging technical problems in scaling the capabilities and utility of agents and agentic models lie in the infrastructure layer – and our team is focused on building the research and production systems that enable OpenAI to train the most capable models in the world, and maximize the utility of our agentic products for users around the world. About the Role As a Software Engineer on the Agent Infrastructure team, you will have the opportunity to work closely with both research and product at OpenAI - building and scaling systems to train highly capable agentic models, and building the platform and integrations to launch new agents to hundreds of millions of users worldwide. Your work will consist of both building new capabilities - standing up the infrastructure and integrations needed to train more complex agentic models - and rapidly scaling these new capabilities to some of the largest compute clusters in the world. At the same time, you’ll be instrumental to the launch of agentic products at OpenAI - building, maintaining, and scaling the production platform on which all agents run. We’re looking for people with deep experience building AI infrastructu

About the Team The Storage Infrastructure team builds and operates the storage foundation behind OpenAI’s most demanding workloads. We work directly with research to design storage systems for rapidly evolving experiments, while also powering production at scale. We own the platform end to end: backend systems, user-facing services and APIs, and the control planes that manage how data is placed, moved, and retained over time. Our stack spans cloud and in-house object stores across very different workload profiles, from GPU-attached systems to dedicated storage hardware. We also build the federation layer that unifies these backends behind a simple interface and routes each workload to the right storage solution. About the Role You will help build the storage platform that powers OpenAI’s research and production systems. This is a hands-on infrastructure role for engineers who want to work on deeply technical systems at scale and own them in production. You’ll work across object storage, cross-region data movement, lifecycle management, and the federation layer that provides a unified interface across multiple backends. Much of our stack runs on Kubernetes, and we primarily build services in Rust. In this role, you will: Build and operate storage services that underpin OpenAI’s research infrastructure Develop object storage systems across cloud and in-house environments Build systems for cross-region data movement, replication, and recovery Design lifecycle management capabilities that keep data durable, available, and cost-effective Evolve the federation layer that unifies multiple backend systems behind a simple interface Improve performance, reliability, and operational excellence across the platform Collaborate closely with researchers and infrastructure teams to support rapidly evolving workloads You might thrive in this role if you: Have experience building or operating distributed systems in production Have worked on storage infrastructure, object stores, dist

About the Role Together AI is building the AI Native Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art GPU cloud infrastructure. The Together Cloud team builds the [Together GPU Clusters](https://www.together.ai/gpu-clusters) flagship IaaS product that provides high-performance, AI-ready GPU clusters through a self-serve cloud console, along with the virtualized infrastructure layer powering Together's inference, RL, and fine-tuning products. As a Staff Software Engineer focusing on AI Compute in the Together Cloud org, you will set technical direction for and build major components of the next generation AI cloud platform – a highly available, global cloud infrastructure with cutting-edge virtualization of the latest ML hardware: GB300s/VRs, BlueField DPUs, InfiniBand and dual/quad-plane RoCEv2 fabrics. That virtualized computing platform powers our own SaaS products – inference, RL, and fine-tuning – and serves external cloud customers through self-serve offerings such as on-demand/reserved Kubernetes/Slurm clusters, across dozens of data centers and hundreds of thousands of GPUs. This is an architect-and-build role. Fully automated bootstrapping of GPU data centers, high-performance virtualization of GPU compute and DC networking without compromising isolation or portability, and fault-tolerant decentralized control planes — you'll set the architecture for these across our global and in-DC services, and be a key owner of the hardest parts, in the code as well as the design. Your designs will span the IaaS layer of a greenfield Vera Rubin data center up to the global management plane that schedules capacity across all of them. At this level the job is as much leverage as code: the standards you set and the engineers you grow decide how fast the rest of Together Cloud ships. Responsibilities Own the GPU and network virtualization stack: the hypervisor, kernel, and SDN work that keeps

Senior Analytics Engineer The Data Science & Analytics team at Asana is how the company turns data into decisions — defining the questions that matter, surfacing the answers, and making sure insight is at the center of every critical product and business call . As a Senior Analytical Engineer, you sit at the intersection of Data Engineering, Analytics, and Data Science, and you own the data foundations for a business domain end to end. Your mandate is to turn raw data into reliable, business-ready datasets that PMs, analysts, data scientists, and leaders actually trust and use — and to define the business logic and metric standards that make AI-powered self-serve trustworthy. You consume governed Silver tables and produce the Gold layer and semantic layer beneath Asana's most important metrics, dashboards, and Genie spaces. This role is based in our Vancouver office with an office-centric hybrid schedule . The standard in-office days are Monday, Tuesday, and Thursday . Most Asanas have the option to work from home on Wednesdays . Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements . What you’ll achieve Own the Gold layer for a given business domain (e.g., PLG funnel, marketing attribution, revenue, NPI/AWM): Design and continuously improve the curated, dimensional data models that downstream dashboards, Genie spaces, and ELT reporting depend on. Implement the canonical business logic behind your domain's core KPIs: Translate KPIs into governed, versioned metric marts that resolve "this number doesn't match" disputes for good. Build and curate the semantic layer and Genie spaces that power self-serve in your domain: Author the metadata, documentation, and prompt/metric definitions that let stakeholders query governed data in plain language through Claude and Databricks Genie. Own the metric dictionary for your domain: a single source of truth for what each metric means,

About the Role Global Safety and Security (GSS) protects our people, our sites, and the physical and logical systems that keep the business running. Our security and protection programs are never single-team efforts: one rollout can touch physical security operations, customer experiences, site readiness, hardware provisioning, networking, cloud infrastructure, identity, and the data platforms above them — spanning many countries, on timelines tied to leases, permits, and vendors. About the Team We are hiring a Staff Security Engineer to help design and deliver strategic and durable security services. You own the technical and architectural plan, strategic partner engagement with technology providers, the delivery sequence, the dependencies, and the program status leadership relies on. You are accountable for outcomes influencing teams that you don’t manage. You will collaborate with software engineers, third-party providers, physical security operations, project managers running site readiness and provisioning, and networking and cloud infrastructure partners, and you will keep managers, directors, and senior leaders informed. Security Enablement Engineering delivers security paved paths and capabilities that address systemic security issues through well-designed customer experiences, easy-to-adopt and robust, well-architected security solutions, systematically reducing organizational risk. You’re excited about this opportunity because you will… Own the design of our physical security systems integration layer — such as access control (PACS) and video management (VMS) platforms, the APIs they expose, and the connectors that carry their data into our systems of record. Own end-to-end design and delivery of multi-domain security services spanning physical security systems, hardware provisioning and site readiness, cloud and network infrastructure, identity and access management, key management, and the reporting/observability layers on top. You’ll bring experti

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role We are on the lookout for a Senior Java Developer to join our Elasticsearch team and drive our work on the Inference API in Elasticsearch. The Elasticsearch Inference API is the integration layer between Elasticsearch and external machine learning services including Elastic's own Elastic Inference Service (EIS), third-party providers (Anthropic, OpenAI, Cohere, Google), and self-hosted models. It powers features like semantic search, reranking, and generative AI across Elastic Cloud and in hosted environments. You'll maintain and develop the plugin framework and REST API with your work spanning protocol design, streaming, async execution, billing integration, and with a tight collaboration with the wider inference team and the Kibana team. What You Will Be Doing Build and maintain integrations with internal systems and external inference providers, including schema negotiation, streaming (SSE), and error normalisation Contribute to the inference plugin's internal architecture: task settings, chunking strategies, rate limiting, and provider-level configuration Review open source contributions to the codebase and work with third party engineers to ensure their contributions meet our technology standards Participate in on-call rotation for inference-related incidents Write thorough tests: unit tests using ESTestCase, YAML-based REST

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role We are on the lookout for a Senior Java Developer to join our Elasticsearch team and drive our work on the Inference API in Elasticsearch. The Elasticsearch Inference API is the integration layer between Elasticsearch and external machine learning services including Elastic's own Elastic Inference Service (EIS), third-party providers (Anthropic, OpenAI, Cohere, Google), and self-hosted models. It powers features like semantic search, reranking, and generative AI across Elastic Cloud and in hosted environments. You'll maintain and develop the plugin framework and REST API with your work spanning protocol design, streaming, async execution, billing integration, and with a tight collaboration with the wider inference team and the Kibana team. What You Will Be Doing Build and maintain integrations with internal systems and external inference providers, including schema negotiation, streaming (SSE), and error normalisation Contribute to the inference plugin's internal architecture: task settings, chunking strategies, rate limiting, and provider-level configuration Review open source contributions to the codebase and work with third party engineers to ensure their contributions meet our technology standards Participate in on-call rotation for inference-related incidents Write thorough tests: unit tests using ESTestCase, YAML-based REST

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role We are on the lookout for a Senior Java Developer to join our Elasticsearch team and drive our work on the Inference API in Elasticsearch. The Elasticsearch Inference API is the integration layer between Elasticsearch and external machine learning services including Elastic's own Elastic Inference Service (EIS), third-party providers (Anthropic, OpenAI, Cohere, Google), and self-hosted models. It powers features like semantic search, reranking, and generative AI across Elastic Cloud and in hosted environments. You'll maintain and develop the plugin framework and REST API with your work spanning protocol design, streaming, async execution, billing integration, and with a tight collaboration with the wider inference team and the Kibana team. What You Will Be Doing Build and maintain integrations with internal systems and external inference providers, including schema negotiation, streaming (SSE), and error normalisation Contribute to the inference plugin's internal architecture: task settings, chunking strategies, rate limiting, and provider-level configuration Review open source contributions to the codebase and work with third party engineers to ensure their contributions meet our technology standards Participate in on-call rotation for inference-related incidents Write thorough tests: unit tests using ESTestCase, YAML-based REST

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role We are on the lookout for a Senior Java Developer to join our Elasticsearch team and drive our work on the Inference API in Elasticsearch. The Elasticsearch Inference API is the integration layer between Elasticsearch and external machine learning services including Elastic's own Elastic Inference Service (EIS), third-party providers (Anthropic, OpenAI, Cohere, Google), and self-hosted models. It powers features like semantic search, reranking, and generative AI across Elastic Cloud and in hosted environments. You'll maintain and develop the plugin framework and REST API with your work spanning protocol design, streaming, async execution, billing integration, and with a tight collaboration with the wider inference team and the Kibana team. What You Will Be Doing Build and maintain integrations with internal systems and external inference providers, including schema negotiation, streaming (SSE), and error normalisation Contribute to the inference plugin's internal architecture: task settings, chunking strategies, rate limiting, and provider-level configuration Review open source contributions to the codebase and work with third party engineers to ensure their contributions meet our technology standards Participate in on-call rotation for inference-related incidents Write thorough tests: unit tests using ESTestCase, YAML-based REST

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role We are on the lookout for a Senior Java Developer to join our Elasticsearch team and drive our work on the Inference API in Elasticsearch. The Elasticsearch Inference API is the integration layer between Elasticsearch and external machine learning services including Elastic's own Elastic Inference Service (EIS), third-party providers (Anthropic, OpenAI, Cohere, Google), and self-hosted models. It powers features like semantic search, reranking, and generative AI across Elastic Cloud and in hosted environments. You'll maintain and develop the plugin framework and REST API with your work spanning protocol design, streaming, async execution, billing integration, and with a tight collaboration with the wider inference team and the Kibana team. What You Will Be Doing Build and maintain integrations with internal systems and external inference providers, including schema negotiation, streaming (SSE), and error normalisation Contribute to the inference plugin's internal architecture: task settings, chunking strategies, rate limiting, and provider-level configuration Review open source contributions to the codebase and work with third party engineers to ensure their contributions meet our technology standards Participate in on-call rotation for inference-related incidents Write thorough tests: unit tests using ESTestCase, YAML-based REST