Director of Engineering, Database Excellence

Director of Engineering, Physical AI Role Overview The Director of Engineering will report to the General Manager of Physical AI, and will be responsible for leading a multi-disciplinary engineering organization. In this senior leadership role, you will own the execution of the Physical AI Data Engine — the platform powering the next generation of Physical AI/Embodied AI. You will collaborate closely with Operations and GTM to guide product direction and help solve the data bottleneck that stands between today's robotics research and real-world deployment. This role requires significant ownership in a fast-paced environment and you will motivate internal teams to set the pace for business growth. Travel will come into play. Key Responsibilities: Set and drive the technical vision across data collection infrastructure, teleoperation systems, ML training pipelines, model evaluation frameworks, annotation tooling, and research Lead a multidisciplinary engineering organization—spanning engineering managers, software engineers, ML engineers, and ML research scientists—while designing the organizational structure, talent strategy, and culture required to scale rapidly without compromising on quality or strategic alignment Maintain exceptional technical and operational excellence by deeply understanding team deliverables, asking incisive questions, identifying slipping standards early, and knowing precisely when to step in Drive cross-functional alignment across Engineering, Operations, and GTM on platform architecture, release processes, and shared priorities Collaborate with researchers and clients to architect and deliver scalable, production-grade data infrastructure tailored for complex robotics workloads Required Qualifications: Bachelor's degree in Engineering, Robotics, Computer Science, or a related technical field 8+ years of engineering experience in fast-paced environments, including 4+ years direct people management demonstrated history of recruiting, mentorin

REQ ID - FEQ227R90 Location: Toronto, ON The Databricks Field Engineering team activates and accelerates the value our customers get from their data and AI. Major Enterprises in Canada are leveraging the Databricks Data Intelligence Platform to securely deliver AI’s potential to every audience, at scale. Our Field Engineering team is hiring a dynamic Solution Architecture leader who is not only focused on team culture but also can translate their team vision into a tangible and effective strategy in order to drive our customers’ data and AI experiences forward. Reporting to the Director of Field Engineering, the Manager, Field Engineering will help lead a team of SAs for the Commercial and Enterprise segment of Databricks’ Field Engineering team focused on the Financial Services Industry. You will lead and promote a dynamic team focusing on enterprise software, big data/analytics, data engineering, and data science. Leading the technical split-focused team (70% pre-sales, 30% technical acumen/demonstrations), you will partner with Sales (and other Field Engineering technical segments) to increase revenue and help customers become wildly successful. You'll scale and maintain an outstanding Field Engineering team that is efficient in its operations to help accelerate Databricks' growth in the market. The impact you will have: You will hire, train, grow and manage a team of Solutions Architects for a company in high-growth mode. Make your customers extremely successful with Databricks and provide outsized value to their businesses. You will maintain a robust hiring pipeline at all times. Establish relationships across the business to make your customers and team successful. Partner with sales leadership to hit sales and consumption targets and ensure customer success Keep your team of SAs ahead of the technical curve. An SA adds value by maintaining a deep understanding of the technology stack. You will make sure that your team is continuously learnin

PagerDuty, Inc. (NYSE: PD) is the global leader in AI-first digital operations. By automatically detecting, diagnosing, and remediating issues, the PagerDuty Platform orchestrates AI agents and automated workflows with context from over 750 integrations. Trusted by approximately two-thirds of the Fortune 100 and nearly half of the Fortune 500, PagerDuty is the industry standard for organizations scaling resilient, autonomous operations. Notable customers include Chipotle, Cloudflare, Docusign, Fox, Nvidia, Salesforce, Spotify, Zoom and more. We are growing rapidly and hiring top talent with leading AI skills across engineering, sales, product, marketing, and beyond as we build the leading digital operations platform. Senior Engineering Manager, Release Engineering AI has changed how fast PagerDuty writes code. Release Engineering decides how fast, and how safely, that code reaches our customers. We’re looking for a Senior Engineering Manager to build the delivery system for this new pace: pipelines that give AI agents fast, trustworthy feedback, environments fully defined in Git, and the CI/CD platform we’ll run for years to come. You’ll lead a team of experienced platform engineers and set the delivery direction for all of PagerDuty Engineering. Reporting to the Director of Infrastructure, you’ll partner closely with our AI-native development program to shape how software gets built and shipped at PagerDuty. **This role will require you to be in office 2 times a week** What You’ll Do: Set the multi-year roadmap for how PagerDuty builds, tests and deploys software. Lead our GitOps transformation, so every environment is defined in Git and every change is promoted and rolled back the same way. Bring CI-quality checks into the developer and agent loop, so problems are caught in minutes, before code ever reaches a merge gate. Give engineers and AI agents short-lived, isolated environments to test changes safely. Rework code review so people spend their time on c

NMI is looking for a Senior Product Owner to drive tactical delivery across our Billing and Data platform teams. This role sits within the Engineering organization, reporting directly to the Director of Software Engineering, and carries ownership across two interconnected domains: Billing, which manages five distinct billing platforms, and Data, which owns ingestion and transformation pipelines built on GCP and BigQuery. The team is distributed across Eastern Europe, LATAM and North America; this role works Eastern or Central time hours. As a Senior PO at NMI, you are the subject matter expert for every feature your team builds. You do not hand off context to others, you carry it. You are present in the details: writing sharp user stories, validating acceptance criteria, conducting UAT, and ensuring releases meet the bar. You are the go-to person for your engineering team, your product manager, and your stakeholders when questions arise about how the platforms work, what is in flight, and what is coming next. This is a hands-on delivery role: the Product Manager owns strategy and roadmap; the Senior PO owns execution, stories, UAT and releases. We do not expect deep expertise in both domains on day one. We expect deep expertise in one and a track record of becoming credible in the other. Growth from this role is toward Staff PO, with broader value-stream ownership, not away from delivery. AI is part of how this role works, not an add-on: we expect you to use AI tools heavily and daily to reach a first version of almost everything faster, while the judgment stays with you. You validate what AI produces, and you are accountable for it. About NMI NMI, a global leader in payment technologies, allows software and sales professionals to deliver payment innovations to their clients without having to build payment expertise in house. NMI enables our partners with choice, and challenges the one-size-fits-all approach to payments. You've probably used NMI in the last 24 hours

Overview We are seeking a hands-on Director of AI Software Engineering to lead and scale AI engineering efforts supporting multiple business units across Governance, Risk, and Compliance (GRC). This role sits at the intersection of product delivery, platform evolution, and applied AI—driving real-world impact across core workflows. This is not a pure management role. We are looking for a builder who leads from the front, someone who has recently written production code, shipped systems end-to-end, and can operate comfortably in ambiguity while aligning teams and stakeholders. What You’ll Do Lead AI Engineering Across GRC Own delivery of AI-powered capabilities embedded directly into business unit workflows (e.g., risk analysis, compliance automation, reporting, due diligence) Partner with product, data, and platform teams to translate business problems into scalable AI systems Stay Hands-On Contribute to architecture, code reviews, and critical path implementation Prototype and validate new approaches (LLMs, agents, retrieval systems, classification pipelines, etc.) Set engineering standards for performance, reliability, and cost efficiency Build and Scale Teams Lead and mentor a high-performing team of AI/ML and software engineers Drive hiring, coaching, and career development Establish a culture of ownership, speed, and technical excellence Drive Execution Deliver production-grade systems—not experiments Balance speed with rigor (security, privacy, compliance) Operate across multiple concurrent initiatives with clear prioritization Communicate and Influence Act as a bridge between engineering and business stakeholders Clearly articulate trade-offs, risks, and outcomes to senior leadership Align cross-functional teams around shared goals and timelines What We’re Looking For Proven Builder 10+ years in software engineering, with recent hands-on coding experience Demonstrated track record of shipping production systems at scale Experience with modern

About the Role: The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding, and ads optimization that shape the future of streaming. We are seeking a Director of Machine Learning Engineering and Infrastructure to lead a hybrid team bridging advanced ML engineering with world-class infrastructure design. In this role, you will own the strategic direction and execution for scaling our machine learning capabilities while ensuring our distributed systems and infrastructure can support innovation at massive scale. You will combine technical depth with leadership excellence to guide teams that deliver both foundational ML systems and high-performance distributed services. This is a hybrid role for our Toronto office. What You'll Do: Lead and manage high-performing teams across ML engineering and ML infrastructure, fostering a culture of innovation, collaboration, and growth. Define and execute the strategic roadmap for ML systems, including recommendation, personalization, and ads optimization. Oversee the design, development, and deployment of scalable ML pipelines: data ingestion, feature engineering, model training, evaluation, and serving. Architect distributed systems to support ML workloads at scale, ensuring reliability, observability, and operational excellence. Partner closely with Product, Engineering, and Content teams to align on business goals and deliver impactful ML-driven experiences. Support best practices in experimentation, evaluation, and ML system monitoring. Ensure cost efficiency, scalability, and performance in ML infrastructure investments. Your Background: 10+ years of industry experience spanning machine learning engineering and distributed systems. 3+ years of leadership and management experience, with a proven ability to build and lead strong t