Laser Design Engineer Jobs

About the role We’re looking for a strong engineer who has a passion for building scalable systems and who can help drive and innovate on our communication platform at Chime! In this role, you would be developing fullstack, from building out our backend infrastructure, to defining the messaging interface on our apps for our members. As a foundational member of this team, you would drive key architectural changes to the layer that powers messaging for millions of members. The Communication Platform team aims to provide a high quality platform to help our members work towards better financial health, while accelerating development velocity within Chime. As a small and nimble team, each person has a profound impact on the experience of each of our millions of users. In this role, you can expect to Design, develop, test, release, and scale changes to our mobile and backend architecture Collaborate effectively with the cross functional team to solve complex problems within the team domain Develop thoroughly tested code and conduct quality assurance on all new code Work in a team as well as independently to deliver on goals to accelerate development velocity while delivering the best experience to our members To thrive in this role, you have A minimum of 3 years experience of fullstack development Experience in backend development and frameworks (Bonus: GraphQL, Ruby) Experience in mobile development and frameworks (Bonus: React Native) Experience working cross functionally and collaborating well with team members Understanding of architectural patterns of large production services built for scale. Ability to safely make changes without disrupting and introducing regressions to millions of users. A passion for learning and sharing knowledge alongside teammates, with self-motivation and keen attention to detail A strong empathy for the users of the products you create #LI-Onsite #LI-AC2 Below is the base salary offered for this role and level of experience. Full-time

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,

The Agent Research and Tooling team, part of MongoDB's AI Builder Experience organization, owns the platform layer around agents: how teams author, distribute, evaluate, monitor, and improve agent skills and agent behavior. We are hiring a software engineer to build and maintain the tooling, evaluation systems, and quality gates behind MongoDB's agent skills. This is a software engineering role at the intersection of developer tooling, applied AI, and software quality. You will take loosely defined agent and tooling problems, break them into workable plans, and ship durable internal systems: command-line tools, reusable libraries, evaluation harnesses, and CI workflows. This role is open to remote work in Canada or can be based out of any of our Canada offices. What you'll do Build and maintain agent skills and the infrastructure to validate, evaluate, publish, and maintain them Design evaluation datasets and workflows that compare agent behavior against a baseline and produce actionable quality signals Build agent metrics and observability: skill selection and routing, success and failure outcomes, tool calls, latency, and token usage Design safety and quality gates for agent-authored content: rule packs, static analysis, confidence thresholds, structured verdicts, and bounded suppression Create CLIs, libraries, and MCP integrations that other repositories adopt and that run in local development and CI Integrate tooling into GitHub Actions and other CI workflows, including secrets, annotations, exit codes, and artifacts Build code-generation quality checks, such as anti-pattern catalogs and linting for AI-generated MongoDB code Investigate real failures such as nondeterministic results, false positives, and unsafe generated guidance, and turn them into reusable improvements Collaborate with engineers, security partners, and product teams; communicate trade-offs, risks, and ownership across teams Examples of the problems you'll solve How can tests verify an agent to

About Supabase Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. About the Role We are hiring a AI Platform Engineer to build the execution layer for Supabase's internal AI systems. Supabase is building an AI-native internal operating system: a common way of working across the company where AI carries a meaningful share of the operational load rather than sitting alongside it as an assistant. We are standing up a new central team to build those systems, enable the teams, and embed AI operations throughout the organization. You are the engineer on that team. The execution layer is yours. You will build the platform that actually runs agents: an event-triggered queue, a headless model-agnostic runtime, durable state so work survives a restart, a human review gate, atomic rollback, and full logging of every prompt, tool call and decision so any run can be reconstructed. You will build the evaluation layer that makes any of it trustworthy, because an agent that cannot be measured cannot be trusted with anything beyond reading. And you will build the agents themselves, across everything from executive reporting down to a layer of agents that watch the platform and improve it. This is a governance-heavy environment by design, and that is the interesting part of the problem. Agents are risk-tiered from read-only internal data through to external-facing output, with review depth, evaluation requirements and human approval scaling by tier. Some capabilities are permanently off limits: an agent may read and report, it may carry a human-authored update into a system of record once a human consents, and it may initiate contact within a strict budget, but it may never autonomously write a commitment (an owner, a due date, a status) into a shared work system. Your job is

The Agent Research and Tooling team, part of MongoDB's AI Builder Experience organization, owns the platform layer around agents: how teams author, distribute, evaluate, monitor, and improve agent skills and agent behavior. We are hiring a software engineer to build and maintain the tooling, evaluation systems, and quality gates behind MongoDB's agent skills. This is a software engineering role at the intersection of developer tooling, applied AI, and software quality. You will take loosely defined agent and tooling problems, break them into workable plans, and ship durable internal systems: command-line tools, reusable libraries, evaluation harnesses, and CI workflows. This role is open to remote work in the US or can be based out of any of our US offices. What you'll do Build and maintain agent skills and the infrastructure to validate, evaluate, publish, and maintain them Design evaluation datasets and workflows that compare agent behavior against a baseline and produce actionable quality signals Build agent metrics and observability: skill selection and routing, success and failure outcomes, tool calls, latency, and token usage Design safety and quality gates for agent-authored content: rule packs, static analysis, confidence thresholds, structured verdicts, and bounded suppression Create CLIs, libraries, and MCP integrations that other repositories adopt and that run in local development and CI Integrate tooling into GitHub Actions and other CI workflows, including secrets, annotations, exit codes, and artifacts Build code-generation quality checks, such as anti-pattern catalogs and linting for AI-generated MongoDB code Investigate real failures such as nondeterministic results, false positives, and unsafe generated guidance, and turn them into reusable improvements Collaborate with engineers, security partners, and product teams; communicate trade-offs, risks, and ownership across teams Examples of the problems you'll solve How can tests verify an agent tool's

We’re seeking an experienced engineer to lead bump interconnect development for advanced semiconductor devices (2.5D/3D/chiplet/fan-out). This role spans ubump and C4 bump metallurgy, RDL design and plating, chip-side and interposer capture pad design rules, OSAT engagement, reliability, failure analysis, and cross-functional support through package and system productization. Core Responsibilities Own end-to-end bump interconnect development for both ubump (micro-bump) and C4 processes, including bump formation, and reflow for use with mass reflow, TCB, and LAB chip attach for high-performance semiconductor packages. Define and own bump metallurgy stacks for ubump (e.g., Cu pillar/SnAg) and C4 (e.g., SAC alloys) interconnects, including UBM selection and pad finish specifications for both chip-side and interposer capture pads. Develop and own design rules for bump interconnects including pitch, bump diameter, standoff height, keep-outs, and land pad geometry for both the chip side and interposer or substrate capture pads. Lead RDL (redistribution layer) process development including electroplating of Cu RDL traces, via fills, and pad finishes; define RDL design rules for line/space, via diameter, and layer stack-up to meet electrical and reliability requirements. Collaborate with OSATs and bumping foundries to qualify ubump and C4 bumping processes, drive design rule alignment, and manage process transfers into production. Evaluate and mitigate bump interconnect assembly risks including non-wet opens, voiding, head- in-pillow, intermetallic growth, and joint fatigue failures across both ubump and C4 interconnect types. Perform root cause analysis of assembly and reliability failures using cross-sectioning, SEM, CSAM, and other failure analysis techniques. Support reliability qualification including thermal cycling, drop, mechanical shock, and power cycling. Work cross-functionally with design, reliability, thermal, and manu

ABOUT THE TEAM The AI Foundations Team at Mural is pioneering how generative AI transforms visual collaboration and decision-making. We’re a remote-first group of engineers, designers, and product thinkers focused on helping teams work together more effectively. Our goal isn’t to replace human creativity. It’s to amplify it, building AI that enhances how people align, communicate, and make decisions visually. YOUR MISSION You will design and build the core AI systems and platforms that enable Mural’s next wave of agentic, AI-driven collaboration experiences. Rather than building isolated AI features, you’ll work on the core backend systems that power Mural’s agent platform, including agent orchestration, durable execution, contextual memory, tool integration, observability, and evaluation. Your work will enable intelligent agents to reason over product context, act on behalf of users, and operate reliably and safely at scale. Our stack at Mural includes Azure OpenAI, React, Node, MongoDB. WHAT YOU'LL DO Build the core backend systems that power Mural’s agent platform, including orchestration, durable execution, tool execution, memory, observability, and evaluation infrastructure Design scalable services and APIs that allow AI agents to retrieve context, coordinate multi-step workflows, interact with Mural data, and act reliably on behalf of users Develop the agent memory layer, including systems for conversation context, product context, retrieval, summarization, compaction, and long-term context management Create infrastructure to monitor, debug, and improve agent behavior through traces, metrics, feedback loops, and offline evaluation Translate complex, open-ended product needs into clear backend architectures, service boundaries, data models, and implementation plans that align technical capabilities with user value Help define the technical direction for agentic AI at Mural, contributing to long-term architecture and strategy Champion engineering excellence, men

P-988 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers and customer obsessed, we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. Lakebase enables teams to deliver applications faster with an optimized database developer experience, integration with the lakehouse, and simplified operations. It provides a managed Postgres transactional layer for application state and workloads that combine operational data, analytics, and AI. You'll join as one of the key engineers building out the Lakebase product. As the Technical Lead on the Lakebase Manager (LBM) team, you will drive, build, and operate the central control plane that owns the core logic for Lakebase: database creation and deletion, wake-up and suspend, maintaining computes on hot standby, HA failover, and more. LBM interacts with every Lakebase component (storage, compute, proxy, and console) and manages the full database lifecycle at scale, with a focus on reliability. This is a hands-on individual-contributor role: you lead the team technically and partner with the team's engineering manager, who owns people management and delivery planning. The stack is Go, Rust, PostgreSQL, and Kubernetes. The impact you will have: Set the technical direction for LBM and own the quality and reliability of what the team ships, driving execution on the hardest, highest-risk parts. Drive architecture and design, and write code on the hardest parts of your team's projects. Set and uphold high technical standards through a

Perforce is a community of collaborative experts, problem solvers, and possibility seekers who believe work should be both challenging and fun. We are proud to inspire creativity, foster belonging, support collaboration, and encourage wellness. At Perforce, you’ll work with and learn from some of the best and brightest in business. Before you know it, you’ll be in the middle of a rewarding career at a company headed in one direction: upward. With a global footprint spanning more than 80 countries and including over 75% of the Fortune 100, Perforce Software, Inc. is trusted by the world’s leading brands to deliver solutions for the toughest challenges. The best run DevOps teams in the world choose Perforce. About the Role The Perforce IP Lifecycle Management (IPLM) suite - used by semiconductor and hardware design teams to manage their intellectual property (IP), releases, and dependencies at scale - includes a Python command-line client (pi), the IPLM API server, the PiCache caching layer, and a Web based interface. As a Senior Software Engineer on the IPLM team, you will own end-to-end features across the CLI and PiCache. You will be expected to work closely with the server team that provides the API and database layers, as well as solutions and support teams to help resolve customer errors. This role blends product feature work, systems engineering, and modern AI-assisted development practices.

P-1580 About Us: The Web Engineering team at Databricks builds and owns the public-facing web experiences that represent Databricks to the world, across databricks.com, the blog, landing pages, hubs, microsites, and event properties. We are rebuilding the platform from the ground up, AI native from the start, and pioneering an agentic SDLC as our operating model. The Role: As Senior Software Engineer, AI Native Web Platform on the Web Engineering team, you will build and scale the platform layer that Web Engineering builds on: framework, infrastructure, CI/CD, and deployment pipelines. You will work under the direction of the Staff Software Engineer and contribute to a unified, agentic-ready foundation that shifts platform maintenance from per-surface effort to a centralized, scalable system. The impact you’ll have : Build and scale platform infrastructure including CI/CD pipelines, deployment automation, secrets management, and edge delivery configurations that power all of databricks.com Own accessibility testing in CI, bringing automated a11y validation into the deployment pipeline so accessibility is enforced at every release rather than caught after the fact Implement consent management infrastructure at the platform layer, replacing fragmented per-surface implementations with a centralized, policy-driven system that enforces compliance automatically across all web properties Contribute to tech stack unification: consolidating a fragmented set of frameworks and deployment models onto a shared design system and unified deployment foundation Operate in an AI native SDLC where agents assist across code generation, testing, and deployment, building faster and more reliably alongside them What we look for: 8+ years of software engineering experience with a track record of shipping and operating production web infrastructure Strong expertise across web platform infrastructure including CI/CD, deployment pipelines, build systems, and edge

About the role The Infrastructure Engineering organization comprises three sub-teams: Core Infrastructure (which manages the infrastructure systems that power Chime, including AWS, Networking, Kubernetes, Terraform, and Observability), Infra Platform , and Data Infra (which provides infrastructure support for the Data Engineering organization). This role is on the Core Infrastructure team , where we manage the Infrastructure components that power Chime and make sure our members are able to use Chime products reliably. This includes our Cloud operations, Observability layer and Compute layer. In this role, you can expect to Automate everything, including scaling, monitoring, and operations. Build tools to enable self-service both within the team and across all of Chime engineering. Tooling is written in Ruby on Rails and Go Lang. Design, build, and support Chime's cloud infrastructure using automation and infrastructure-as-code. Adapt new technologies to make Chime run as efficiently and reliably as possible. Partner with product development engineers to build services according to modern design patterns; for example, the 12 Factor App methodology. Develop strong relationships with engineers, managers, and other colleagues based on trust, empathy, and technical expertise. Be a constant advocate and adopter of AI tools and evangelize agentic AI workflows in a way that is safe and reliable. To thrive in this role, you have More than 2 years of cloud and Infrastructure experience Strong development experience in Ruby on Rails and Go Lang. Previous professional experience in a DevOps/SRE/ProdEng role supporting customer-facing web services. Previous success in enabling effective partnerships and strong communication with other engineers and teams. Experience managing Kubernetes clusters cloud hosted or self hosted. Experience building and managing highly-available public cloud infrastructure and services, with an emphasis on stability, scalability, and security. Experien

About the Team OpenAI's research training infrastructure powers how our frontier models are trained and evaluated. The Simulation team sits at the intersection between the agentic harness that powers OpenAI's products and the research infrastructure where GPT-next is trained, ensuring that our model's training environment is as realistic as possible. This team owns the integration layer that connects our production harness capabilities into the training stack. The work is highly cross-functional and high leverage: researchers depend on it to run experiments and evaluations reliably as well as to develop the next generation of harness capabilities. Failures in this surface can materially affect training velocity and correctness. About the Role We're looking for a Principal Software Engineer to lead the architecture and evolution of the Simulation Platform. You'll own a critical interface between research and engineering, building the systems, APIs, and operational patterns that let researchers use agentic coding infrastructure safely and effectively in training environments. This role is ideal for a senior backend or infrastructure engineer with strong technical judgment, product sense for highly technical users, and the ability to drive execution across multiple teams. The highest-leverage work is building robust infrastructure that supports and accelerates research without compromising engineering quality. In this role, you will Design, build, and evolve the integration between the Codex harness that powers OpenAI's products and research training infrastructure used for training GPT-next Build a platform for our LLMs to train and be evaluated in simulated environments that mimic their deployment setting as closely as possible, on every axis: agentic harness, compute substrate, timing, tools, data sources, humans in the loop, and more Own major integration surfaces end-to-end, from architecture and API design through rollout, operations, and long-term maintenance Bu

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We're looking for an Operating Systems Security Engineer to harden and secure the OS layer of our infrastructure. You'll be responsible for designing and implementing OS-level security controls, from kernel hardening to runtime protection, ensuring our systems can withstand sophisticated attacks while maintaining the performance required for AI model training. This is a hands-on role where you'll work with cutting-edge hardware and implement novel security solutions for environments that don't exist anywhere else in the world. You'll need to balance extreme security requirements with the operational needs of researchers training models at unprecedented scale. Key responsibilities Design and implement hardened OS configurations for AI workloads across diverse hardware platforms Minimize attack surfaces by removing as many unnecessary components as possible from kernelspace and userspace Develop kernel security policies using SELinux, AppArmor, and custom Linux Security Modules and runtime enforcement mechanisms Implement and maintain full-disk encryption solutions for diverse storage systems Build security infrastructure for AI systems, research environments, and production services Create OS-level attestation and integrity monitoring systems Apply security patches, develop patches for custom kernel modules, and kernel hardening configurations Design secure boot processes and trusted execution environments Work with container teams to ensure proper workload isolation at the kernel level Design privilege separation and mandatory access control policies Implement secure update mechanisms for OS components Build tooling for

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role We're looking for experienced engineers to build and scale the database infrastructure that powers Claude's products and Anthropic's research. As a Software Engineer on the Databases team, you'll architect and operate the systems that let millions of users interact with Claude while also supporting frontier AI research workloads. You'll help set the database strategy for Anthropic: designing systems that handle billions of API requests, building storage that runs cleanly across GCP, AWS, and a range of deployment models, and creating the reliable data layer that lets research move fast. The Databases team spans three areas: the core database platform (data plane and control plane), data movement (migrations, backfill, and change data capture), and caching. We're hiring across all three. Key Responsibilities Drive the technical direction for database solutions used across Product and Research Design and implement database solutions that scale to support millions of users across Claude's product ecosystem Build and scale database systems through 100x+ growth while maintaining reliability and performance Build the database platform that lets Anthropic engineers ship without thinking about databases or scaling. Architect data storage solutions that operate across GCP, AWS, first-party deployments, third-party deployments, and other environments Develop database infrastructure that serves both product and research workloads with different performance characteristics Build data movement infrastructure (migration tooling, backfill, and change data capture pipelines) that safely consolidates and moves data across the organizati

DeepIntent is the leading healthcare marketing platform, purpose-built to help marketers plan, activate, and optimize data-driven campaigns with speed and precision. Trusted by the world’s top healthcare brands and their agencies, DeepIntent uniquely unites media, identity, and real-world clinical data to power privacy-safe, omnichannel marketing across every screen. Backed by patented technology and proven outcomes, DeepIntent’s platform delivers measurable audience quality and script lift at scale. Learn more at www.deepintent.com . Location: Banja Luka, Bosnia and Herzegovina (primary) or Belgrade, Serbia What You’ll Do: As a Senior Security Engineer, you will own the security architecture and enforcement across our infrastructure. Our infrastructure relies heavily on a Linux ecosystem, and as we scale our cloud footprint and AI initiatives, this layer is becoming increasingly security-sensitive. You will be embedded directly with the teams operating these systems, bridging the gap between high engineering velocity and secure-by-design architecture. Your core mandate is to protect production, harden our Linux environments, establish AI guardrails, and build secure access patterns without creating process overhead. This role will report to the Sr Director, Infrastructure and Networking and will be a hybrid role based out of Banja Luka, Bosnia. Linux Hardening & Threat Detection: Secure our underlying Linux infrastructure and container runtimes. Deploy, tune, and manage our SIEM for continuous threat detection, file integrity monitoring, and host-based intrusion detection (HIDS) across our fleet. Identity & Access Control: Design and enforce secure access patterns. Ruthlessly eliminate shared accounts, long-lived credentials, and overly broad permissions across the organization. Cloud & Infrastructure Governance: Own the security posture across our cloud environments. Implement secure infrastructure-as-code practices using Terraform an