Engineering Enablement Manager in United States

Leidos Engineering LLC is a premier national engineering-based management consulting firm. We are seeking an experienced and motivated candidate to join our team as a Senior Energy Engineer. The position is ideal for a person with excellent technical skills and energy engineering experience with experience in calculating energy saving estimates, energy auditing, and communicating technical issues within the project team while working closely with contractors, suppliers, architects, and project engineers. Primary Responsibilities: Reviewing technical energy efficiency applications for incentives and rebates for Ameren Illinois electric and natural gas customers Review different types of energy using systems within the industrial and/or commercial markets (HVAC, Lighting, compressed air systems, energy management systems, etc) Research technology changes to support improvements to the energy efficiency program and provide solutions for implementation improvements Maintain working knowledge of the Illinois Technical Reference Manual and associated energy efficiency concepts. Review existing energy savings methods for quality control/improvements Utilize independent judgment to verify technical requirements are met throughout various energy savings initiatives Coordinate & provide guidance to supporting teams regarding energy efficiency programs Basic Qualifications Bachelor’s degree in engineering, Economics, Business Administration or related, with six plus (6+) years of relevant experience Prior experience in energy efficiency or similar technologies. Proficiency with Microsoft Office Products, especially Microsoft Excel Must be a

We anticipate the application window for this opening will close on - 16 Oct 2026 Careers that change lives start here. Medtronic is a global leader in healthcare technology with a Mission to alleviate pain, restore health, and extend life. Our 95,000 employees work across more than 150 countries to put patients first — developing innovative medical technologies that improve the lives of 72+ million patients each year. Your unique talents will help shape the future of healthcare while building a career grounded in purpose, growth, and impact. A Day in the Life The Quality Engineering function within Service and Repair is responsible for ensuring compliance, product quality, supplier quality technical support and continuous improvement across service center and field service operations. This team partners closely with Engineering, Regulatory, Supplier Quality, Post-Market Quality, and Operating Units to support quality system requirements, continuous improvement initiatives, supplier management, audit readiness, and the introduction and sustainment of products throughout the service lifecycle. The Service & Repair Quality Engineer II provides quality engineering support for a global Service and Repair organization. This role partners cross-functionally to maintain compliance with quality system requirements, support daily operations, drive resolution of quality issues, support supplied products and processes, and ensure audit readiness across service center and field service activities. The Quality Engineer II also plays a key role in Corrective and Preventive Action (CAPA) activities, process validation efforts, and continuous improvement initiatives that support operational performance and product quality. This role is based in Rice Creek, Minnesota and requires onsite presence 5 days per we

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team builds next-generation AI-native silicon and systems while working closely with software, research, and manufacturing partners to co-design hardware tightly integrated with AI models. In addition to delivering systems for OpenAI’s supercomputing infrastructure, the team develops the tools, methodologies, and strategic partnerships needed to accelerate hardware innovation. About the Role We’re seeking an experienced Hardware Strategic Sourcing Manager to own sourcing strategy and supplier partnerships for fiber and optical interconnect components across OpenAI’s next-generation AI infrastructure. Reporting to the Head of Partnerships & Strategic Sourcing, you will lead sourcing across fiber cable assemblies, internal optical harnesses, fiber shuffles, optical backplane assemblies, connectorized and standalone passive optical assemblies, fiber-array units (FAUs), fiber-to-chip and coupling interfaces, detachable connectors, optical routing, and assigned optical packaging, assembly, and test services. You will work closely with electrical engineering, optical engineering, systems engineering, mechanical and packaging engineering, quality, rack integration, data-center deployment,manufacturing, supply chain, finance, legal, and program management teams to translate demanding bandwidth, signal integrity, reliability, and scale requirements into resilient supplier partnerships and scalable commercial strategies. Your work will directly support the performance, reliability, manufacturability, and scale of the high-speed optical connectivity required for OpenAI’s next-generation AI systems. In this role, you will: Develop and execute a comprehensive sourcing strategy for fiber and optical interconnect components supporting high-bandwidth AI systems and infrastructure. Own sourcing across optical fiber cable assembli

About the Team OpenAI, in partnership with our capital and technology partners, is building a global network of advanced datacenters to support the most demanding AI workloads. The Industrial Compute team ensures that all datacenter systems are manufactured, delivered, and commissioned to the highest standards of quality, reliability, and performance. We work closely with manufacturing partners, engineering teams, and operations staff to ensure that every component is delivered ready for installation, startup, and long-term service. About the Role We are seeking an experienced Quality Engineer (QE) to drive Product and Site Quality initiatives across OpenAI’s infrastructure ecosystem. In this role, you will establish, implement, and manage a comprehensive, quality-focused program across our global supply chain network, ensuring excellence from design through deployment. You will be responsible for end-to-end quality of finished products, as well as maintaining and elevating manufacturing site quality standards. Working cross-functionally with Design (NPI) and Engineering teams, you will help achieve First Pass Yield (FPY), quality, and reliability targets. This includes leading site and fixture validation efforts, driving yield improvement initiatives (Yield Bridge, CPI), and implementing robust corrective and preventive actions (CAPA) to resolve issues at their root cause. In addition, you will play a key role in supplier quality management, assessing and qualifying new vendors, overseeing ongoing supplier performance, and ensuring readiness for future business awards. You will lead vendor audits, monitor key performance metrics, and coordinate corrective actions to ensure predictable delivery schedules, reduced operational risk, and high system reliability. By partnering closely with external suppliers and internal Engineering and Operations stakeholders, you will help ensure OpenAI’s datacenter infrastructure is delivered on time, meets the highest quality standa

About the Team The Systems Integration team is responsible for building the infrastructure, tooling, and validation systems that ensure our device software our device software is reliable, testable, and ready to ship. We design and maintain build systems, CI pipelines, automated test frameworks, and hardware-in-the-loop labs to enable rapid, safe product launches. Our work spans build systems, developer tools, systems integration, and cross-team collaboration to ensure developers can build reliably and ship with confidence. About the Role We are looking for an engineer to help evolve OpenAI’s Consumer Products build and continuous integration systems for a fast-growing engineering organization. This role sits at the intersection of developer productivity, build systems, distributed infrastructure, software quality, and on-device software. You will work on the systems that determine how quickly and confident engineers can move: Bazel-bazed builds, Buildkite pipelines, test coverage, remote caching and execution, CI observability, and tooling that helps engineers understand and fix failures quickly. Our mission is to enable OpenAI to ship software running on consumer devices rapidly with a high bar for correctness, reliability, and safety. The best version of this work is invisible when it succeeds: builds are fast, tests are trusted, CI failures are understandable, and engineers can focus on shipping products instead of fighting infrastructure. This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. In This Role, You Will Own and evolve Bazel and yocto-based build and test workflows in a polyrepo environment Design and maintain Starlark rules, macros, toolchains, and integrations that make builds hermetic, reproducible, and easy for teams to adopt Improve CI performance and reliability across Buildkite pipelines, including queue time, build time, cache hit rates, retry b

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: As a Senior Research Engineer in our Safety team, you will play a key role in helping develop safer, more secure, and more reliable models. Your primary focus will be on building tools to enable easy data synthesis, analysis, and management, for complex combinations of real and synthetic data that is used in both model training and evaluation. You will own the cohesive vision of these tooling repositories. You will work closely with a team of research scientists and engineers to create tooling that enables tighter experimentation cycles, better data coverage of the real world, and more scientific rigour. You will have a lot of autonomy and need to be opinionated about what areas of the codebase need elegance and standards, and where that would be overengineering. You will be given high level experimental problems that need to be solved with efficient pipelines, and design and implement the solutions. Your data analysis will collaboratively feed into modelling decisions and experimentation. This role combines expertise in software engineering, statistics, and data science. If any of these topics sound interesting t

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. The Security Governance, Risk, and Compliance (GRC) team is part of Plaid’s security organization, focused on enabling the business by proactively managing information security risks and maintaining effective controls. Our mission is to reduce the likelihood and impact of security risks while operating a robust assurance program that builds trust with our customers, consumers, and data partners. We own Plaid’s security compliance frameworks, run our audits and risk programs, and partner across the company to keep Plaid’s platform secure, resilient, and aligned with industry and regulatory expectations. GRC Engineering is how we make all of that scale — turning compliance into code, evidence into telemetry, and audits into a continuous, automated capability. The Role: You will own GRC Engineering at Plaid — a foundational, high-ownership role defining an emerging discipline from the ground up. Today most of our compliance work is manual and point-in-time; you will turn it into an engineered system that is continuous, data-driven, and scalable, and set the technical direction for the field. You will: Define the discipline and the architecture — how GRC Engineering works at Plaid, not just execute with

Datadog is expanding the Technical Solutions (TS) organization by seeking a customer-focused, deeply technical Distinguished Architect to join our Product Solutions Architecture (PSA) team. In this role, you will act as a technical multiplier for the world's leading AI labs and AI-native companies. You will bridge the gap between their bleeding-edge infrastructure aspirations and Datadog’s technology roadmap, ensuring our platform natively solves the unique observability challenges of training and deploying foundational models at scale. 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: Leadership : Demonstrate thought leadership in the AI/LLM space. Influence key decision makers and stakeholders by connecting technical capabilities to organizational and business impact. Advisory : Strategically partner with highly technical Founders, Heads of Infrastructure, and Research Lead peers. Guide them on best practices and emerging industry trends in the AI/LLM space. Lead high-level technical and architectural conversations around AI adoption. Presentations : Lead deep-dive architecture reviews and design engagements with customer teams and their leaders to share industry trends, best practices, and demonstrate how Datadog can support high-throughput hyper scale AI workloads. GTM : Identify emerging AI-native technology shifts and feed them directly back to Datadog Product Management. Co-create custom observability integrations and solutions alongside Product SAs to keep Datadog at the absolute forefront of the AI stack. Collaboration : Collaborate with Product Solutions Architecture (PSA), Sales, Sales Engineering and Marketing in providing high-quality technical resources to a broad audience of practitioners and economic buyers. Hiring : Assis

Join the engineering teams that bring OpenAI’s ideas safely to the world!! The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role We’re building the observability product for OpenAI—from scalable infrastructure to a rich, AI-powered UI. Our systems ingest over petabytes of logs and billions of time series metrics across our fleet. We're now layering intelligence on top—think agents that summarize SEVs, auto-generate dashboards, or help engineers debug through notebook-like UIs. We’re hiring software engineers across the stack—infra, backend, and product. You’ll join a small, gritty team building both foundational infra and novel internal tools to make OpenAI's production systems reliable, performant, and observable. What You’ll Do Own core observability infrastructure, including distributed logging, time series, and trace storage Build AI-native tools that help engineers detect, understand, and resolve issues autonomously. Contribute to UI experiences like dashboards, notebooking, or interactive debugging Collaborate closely with engineers, researchers, user ops, and other teams across the company to build the next generation observability product You Might Be a Fit If You: Have operated large-scale distributed systems in production. ( especially logging systems or some other time series databases) Thrive in ambiguous environments and roll up your sleeves to solve unscoped problems. Have full-stack chops or product sensibilities—you're excited to build real tools people use. Have strong fundamentals in systems, networking, and cloud infra (Kubernetes, AWS, etc). Bonus : built or contributed to observability systems (e.g. Prometheus, OpenTelemetry, etc). Why This Team We’re b

About the Team OpenAI, in partnership with our capital and technology partners, is building a global network of advanced datacenters to support the most demanding AI workloads. The Industrial Compute team ensures that all datacenter systems are manufactured, delivered, and commissioned to the highest standards of quality, reliability, and performance. We work closely with manufacturing partners, engineering teams, and operations staff to ensure that every component is delivered ready for installation, startup, and long-term service. About the Role We are seeking an experienced Quality Engineer (QE) to drive Product and Site Quality initiatives across OpenAI’s infrastructure ecosystem. In this role, you will establish, implement, and manage a comprehensive, quality-focused program across our global supply chain network, ensuring excellence from design through deployment. You will be responsible for end-to-end quality of finished products, as well as maintaining and elevating manufacturing site quality standards. Working cross-functionally with Design (NPI) and Engineering teams, you will help achieve First Pass Yield (FPY), quality, and reliability targets. This includes leading site and fixture validation efforts, driving yield improvement initiatives (Yield Bridge, CPI), and implementing robust corrective and preventive actions (CAPA) to resolve issues at their root cause. In addition, you will play a key role in supplier quality management, assessing and qualifying new vendors, overseeing ongoing supplier performance, and ensuring readiness for future business awards. You will lead vendor audits, monitor key performance metrics, and coordinate corrective actions to ensure predictable delivery schedules, reduced operational risk, and high system reliability. By partnering closely with external suppliers and internal Engineering and Operations stakeholders, you will help ensure OpenAI’s datacenter infrastructure is delivered on time, meets the highest quality standa

About the Role The Engineering Acceleration team builds and operates the foundational systems that engineers use to build, test, and ship ChatGPT, the API, and OpenAI's infrastructure. We are looking for an engineer to help evolve OpenAI's build and continuous integration systems for a fast-growing engineering organization. This role sits at the intersection of developer productivity, build systems, distributed infrastructure, and software quality. You will work on the systems that determine how quickly and confidently engineers can move: Bazel-based builds, Buildkite pipelines, test selection, remote caching and execution, CI observability, and tooling that helps engineers understand and fix failures quickly. Our mission is to make OpenAI one of the most productive engineering organizations in the world while preserving a high bar for correctness, reliability, and safety. The best version of this work is invisible when it succeeds: builds are fast, tests are trusted, CI failures are understandable, and engineers can focus on shipping useful systems instead of fighting infrastructure. In This Role, You Will Own and evolve Bazel-based build and test workflows across a large, polyglot monorepo. Design and maintain Starlark rules, macros, toolchains, and integrations that make builds reproducible, hermetic, and easy for product teams to adopt. Improve CI performance and reliability across Buildkite pipelines, including queue time, build time, cache hit rates, test sharding, retry behavior, and flake isolation. Build systems that reduce unnecessary CI work through affected-target detection, dependency graph analysis, test selection, caching, batching, and smarter scheduling. Improve local development workflows so engineers can reproduce CI behavior, debug build failures, and iterate quickly without learning every detail of the build stack. Operate and optimize build infrastructure across Docker/OCI images, Kubernetes-based runners, cloud resources, and remote cache/exec

About the Role The Engineering Acceleration Delivery / Continuous Deployment team builds and operates the systems that safely ship OpenAI’s infrastructure and product code to production. We own the deployment platform, release pipelines, and rollout safety mechanisms that allow engineers across OpenAI to deploy changes rapidly while minimizing operational risk. Our mission is to make production deployments fast, safe, and increasingly autonomous. This role sits at the intersection of developer productivity, distributed systems reliability, and large-scale infrastructure orchestration. In This Role, You Will Design and build continuous deployment infrastructure that safely rolls out changes across dozens of Kubernetes clusters and global regions. Develop systems for progressive delivery, including canary releases, staged rollouts, and automated rollback. Improve engineering velocity by reducing friction in the release pipeline and automating manual operational workflows. Work with product and infrastructure teams to ensure their services are deployable, observable, and resilient at scale. Implement and evolve deployment methodologies such as GitOps, infrastructure-as-code, and progressive delivery patterns. Build systems that automatically evaluate deployment health using metrics, logs, traces, and alerts to detect regressions and trigger safe rollbacks. Build systems that support agent-assisted or autonomous deployment workflows using modern AI tooling. Technologies commonly used in this environment include: Kubernetes for large-scale container orchestration and runtime infrastructure Python and FastAPI for internal services Terraform for infrastructure as code GitOps-based deployment workflows (e.g., ArgoCD, Flux, or similar systems) Buildkite for CI orchestration You may be a strong fit if you: Have worked with Kubernetes-based deployment systems at scale Have experience building or operating continuous deployment platforms Are familiar with GitOps tooling such as

The Performance Research Engineer will play a critical role in advancing TaylorMade's leadership in golf equipment performance. This role bridges physical testing, player testing, Tour-level data collection, and advanced analytics to deliver actionable insights that influence product design, product validation, and performance optimization. The ideal candidate is a hands-on engineer with strong mechanical aptitude, advanced data skills, deep golf intuition, and the ability to translate player feedback into clear engineering direction. Essential Functions and Key Responsibilities: Lead the design and execution of advanced performance testing protocols for golf clubs and balls, including lab, player, field, and Tour-based testing environments. Serve as a category-focused Performance Engineering owner for one or more product areas, with potential emphasis across Woods, Irons, Putter/Wedge, or cross-category initiatives. Support PGA/LPGA Tour and elite-athlete testing by collecting clean, repeatable, decision-ready data while operating professionally and respectfully in player-facing environments. Analyze large datasets from lab, player, and field testing to extract insights on ball speed, launch, spin, consistency, delivery, impact location, dispersion, and performance tradeoffs. Translate Tour and player-test observations into clear engineering recommendations, product questions, validation plans, and follow-up experiments. Develop and maintain automated data pipelines, dashboards, and reporting tools for performance tracking, project communication, and cross-functional decision-making. Collaborate with R&D, Product Development, Tour, Fitting, Consumer Insights, and Analytics teams to integrate player feedback and real-world data into product design.

TaylorMade Golf is looking for a Senior Manager of Facilities who leads from the front. This role owns HQ facilities planning, maintenance, engineering, and regulatory operations at our Carlsbad headquarters, working across three fronts: building and leading a high-performing Facilities and General Services team, running point as project manager on construction and infrastructure work, and serving as a trusted partner to business leaders across the company. Essential Functions and Key Responsibilities: People Leadership — Lead and develop the Facilities and General Services team, including performance management, coaching, and succession planning. Project Management — Own construction, space planning, employee moves, and infrastructure projects from bid to completion, managing budgets, timelines, and subcontractor performance. Facility Operations — Manage preventative maintenance, mechanical/HVAC systems, energy conservation, and facility drawings across TaylorMade's North America sites. Site Services — Oversee café, pantry, and mailroom operations at the Carlsbad HQ. Business Partnership — Partner closely with Legal, Security, Safety, and business leaders to keep projects and daily operations on track. Environmental Health & Safety — Serve as the primary contact for audits, inspections, and local permit renewals (AQMD, water, stormwater, CUPA, CERS) and lead chemical and hazardous materials policy, storage, and compliance. Emergency Preparedness — Co-own the Building Emergency & Safety Team (BEST) with Corporate Security, including training and drills. Knowledge & Skill Requirements Strong planning and organizational skills, including the ability to manage multiple concurrent projects, budgets, and timelines.

Where Performance Meets Purpose Join a team that values excellence and innovation, at a company known for its iconic golf brands. At Acushnet Company, your background and experience contribute to creating the best products for dedicated golfers worldwide. Here, your performance has purpose. What You Will Be Doing The Senior Industrial Engineer plays a vital role in advancing manufacturing and distribution excellence by driving efficiency, innovation, and continuous improvement across operations. This position applies industrial engineering principles to optimize production processes, facility layouts, material handling systems, and labor utilization while supporting East Coast manufacturing and distribution teams. The role leads projects involving equipment installation, relocation, and workflow redesign; develops labor and capacity models for global golf ball manufacturing; and identifies opportunities for cost reduction, productivity gains, and operational improvements. Through data-driven analysis, reporting, and cross-functional collaboration, the Senior Industrial Engineer helps ensure safe, efficient, and scalable operations that support long-term business growth. What You Bring Bachelor’s degree in Industrial Engineering or a related Engineering discipline required Minimum of 5 years of Industrial Engineering experience Proficient in the use of computers and engineering software Ability to sit, stand, walk, crawl, and climb for extended periods as needed Proficiency with AutoCAD and Microsoft Office applications Experience with facility layout design and optimization Strong knowledge of capacity planning and capacity analysis Experience with Lean manufacturing, process simp