Engineering Effectiveness Manager Jobs

As a Senior Enterprise Sales Engineer, you’ll serve as a trusted technical advisor and strategic partner to both customers and Sales. You’ll lead complex technical evaluations, align solutions to business outcomes, and help shape deal strategy in high-impact opportunities. This role goes beyond delivering demos - you’ll own the evaluation experience end-to-end, influence key stakeholders, and help drive successful outcomes across enterprise accounts. What You’ll Do: Own the technical strategy across your accounts as a peer to the Account Executive - a standing weekly 1:1 with each AE you support, and a standing weekly account team call with the full ecosystem where you carry POV status, technical blockers, and the explanation behind any usage movement. Own the technical explanation behind consumption movement in your accounts. Work with the CSM and TAM to separate legitimate growth from misconfiguration, make sure legitimate growth gets quantified before renewal, and flag forward-looking usage the customer has signalled rather than explaining it backwards a month later. Lead discovery in every meeting, not only in discovery meetings - including meetings where you were invited to present. Leave each meeting knowing something about their business you did not know going in. Deliver engaging product demos, technical presentations, solution workshops, etc. that connect platform capabilities to customer outcomes for diverse stakeholder audiences including executives Full ownership of the technical evaluations (POVs) end-to-end: scoping use cases and requirements, defining competitive success criteria, building a project plan with clear timelines, and holding all participants accountable to the process Identify, develop, and leverage technical champions across multi-stakeholder environments, building a structured plan for champion cultivation and influence throughout the deal cycle and beyond Contribute to product direction through active participation in structured

As an Enterprise Sales Engineer, you'll partner with Sales to help customers understand the value of Datadog and how it solves their most important technical and business challenges. You'll lead technical evaluations, deliver compelling demos, and guide customers through the journey from discovery to successful adoption. You'll act as a trusted advisor, bridging business goals with technical solutions, and play a key role in winning new business and expanding existing accounts. 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: Own the sales process in partnership with Account Executives by leading and shaping the technical strategy across opportunities from PG to Closed Won Lead customer discovery to uncover technical challenges, business goals, and success criteria, then translate those needs into tailored Datadog solutions Deliver engaging product demos, technical presentations, and workshops that connect platform capabilities to customer outcomes Project manage technical evaluations (POVs) end-to-end: scoping use cases and requirements, defining success criteria, building a project plan with clear timelines, and holding all participants accountable to the process Identify and cultivate technical champions within customer accounts, empowering them to advocate for Datadog adoption and drive consensus internally Participat e actively in structured product and engineering field feedback sessions, serving as the technical voice of the customer to help shape product direction Maintain operational excellence by ensuring activity, deal progress, and customer interactions are accurately documented and up to date in related systems Collaborate cross-functionally with Product, Support, and GTM teams to address customer needs and resolve

About the Team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role This is a founding role. As Singapore’s first Deployment Lead (DL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the Role This is a founding role. As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. This is not a management role, however you'll own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in Singapore. We use a hybrid model of 3 days in office and offer relocation assistance. Travel up to 25-50% is required. In this role, you will: Own the technical delivery plan for multiple interdependent workstreams. Translat

National Security Hackathon Attendees – Stay Connected with Scale AI This posting is for candidates who attended National Security Hackathon and connected with a member of the Scale AI team. It was great meeting you at the Hackathon! Whether we spoke at our booth or on the floor, we always enjoy connecting with people who are passionate about advancing AI and machine learning. At Scale AI, our mission is to develop reliable AI systems for the world's most important decisions. For the past ten years, Scale has been the leading AI data foundry, supporting some of the most exciting advancements in AI, including generative AI, defense applications, robotics, and autonomous systems. We’re continuing to grow our team across a range of technical and mission-focused roles. If you're excited about the problems we’re tackling, feel free to share your information here. A member of our team will reach out if there’s a strong fit with one of our open opportunities. And even if the timing isn’t right today, we’d love to stay connected. We look forward to continuing the conversation. In the meantime, you can learn more about our work at scale.com . Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: c

About the Team The DoorDash Research Fellowship is a 3-month program (extendable to 6 months) looking for Summer and Fall 2026 cohorts, for researchers and engineers who want to work on the hardest applied ML and AI problems in local commerce. Fellows are given the resources, autonomy, and access to real-world operational data needed to pursue ambitious research directions — with the goal of producing work that influences both the field and how DoorDash operates at scale. This program is modeled on the best external research fellowships: fellows are treated as independent researchers, not as junior employees on a product team. You pick the problem (within a set of priority areas), you own the direction, and you publish or ship the outcome. You’re excited about this opportunity because you will receive… Dedicated compute allocation sized to the research agenda — GPU clusters for training and inference budgets for experimentation Full access to DoorDash's research infrastructure — our internal RL stack, training and evaluation pipelines, RL environments built on real operational systems, agent evaluation harnesses, and the tooling our own research teams use day-to-day. Fellows are first-class users, not sandboxed visitors. Access to DoorDash operational data — real-world datasets spanning logistics, merchant operations, consumer behavior, and marketplace dynamics, under appropriate data governance Research mentorship from senior researchers and engineering leaders at DoorDash, plus a named research sponsor for each fellow who meets with you weekly and is accountable for unblocking your work Speaker series featuring leading researchers and practitioners from academia and industry — faculty from top ML programs, research leads from frontier AI labs, and senior operators from across tech. Fellows get dedicated 1:1 time with speakers when possible. A cohort of fellows working alongside you — a small, tight-knit group of researchers tackling different problems but sharing

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 Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. Decisions in production training depend on knowing how the model is really behaving. Our team's mission is to have the best observability into production post-training runs at Anthropic: to be the clearest, most trusted view of model quality during training. We shape what gets measured, keep the signal trustworthy and timely, and get to the bottom of surprising results to inform post-training and release decisions. In this role you will lead the science of how we evaluate production training runs. You'll work out which measurements tell us something real about the model, notice when they stop doing so, and find what we should be measuring but aren't. You'll partner with research teams across every RL domain, bringing their priorities into what we measure and setting the standard for what makes an eval trustworthy across post-training. You'll also be hands-on with the eval fleet day to day, because the best questions about measurement come from watching real results come in during a live run. Responsibilities Steer the eval strategy for production Claude models: study and optimize the eval mix so it gives the most accurate and complete assessment of model quality Run and monitor the eval fleet live to understand how each Claude model is developing as it trains Advise teams across post-training on eval methodology, and help eval authors bring new evals up to the bar for production Investigate regressions in production runs and inform training interventions when appropriate Build the

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. Anthropic Fellows Program overview The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience. Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers. We run multiple cohorts of Fellows each year and review applications on a rolling basis. Submit your application to the Economics & Policy workstream at the bottom of this page. We are accepting applications on a rolling basis for the next cohort expected to start in January 2027. In some circumstances, we can accommodate fellows starting outside the usual cohort timelines — please note in your application if the January 2027 start date doesn't work for you. What to expect 4 months of full-time research Direct mentorship from Anthropic researchers Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country) Substantial funding for compute and other research expenses Interview process The interview process will include an initial application, assessments, and interviews. We may ask for references later in the process as well. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing i

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 The RL Velocity team owns the efficiency and reliability of our RL Science stack - the infrastructure, tooling, and systems that let researchers iterate quickly on training runs. As a Research Engineer on the team, you'll build and improve the core platform that underpins how we do RL at Anthropic, removing bottlenecks that slow down research and making it easier for the broader org to ship better models faster. This is high-leverage work: small improvements to velocity compound across every researcher and every run. Responsibilities Build and improve the RL training infrastructure that researchers depend on day-to-day Identify and remove bottlenecks across the RL stack: debugging, profiling, and rearchitecting where needed Partner closely with researchers and with adjacent engineering teams (inference, sandboxing, and many more) to understand pain points and ship tooling that makes them faster Own the reliability and performance of research runs end-to-end Contribute to design decisions that shape how Anthropic does RL at scale You may be a good fit if you Have strong software engineering fundamentals and a track record of building performant, reliable systems Have worked on ML infrastructure, distributed systems, or research tooling Care about enabling other people's work and find leverage through platforms rather than individual experiments Are comfortable operating across the stack, from low-level performance work to RL algorithms Have a bias toward shipping and iterating quickly, with a mix of high agency and low ego Strong candidates may also have Experience with large-scale distributed training (RL, pre-training,

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 The RL Velocity team owns the efficiency and reliability of our RL Science stack - the infrastructure, tooling, and systems that let researchers iterate quickly on training runs. As a Research Engineer on the team, you'll build and improve the core platform that underpins how we do RL at Anthropic, removing bottlenecks that slow down research and making it easier for the broader org to ship better models faster. This is high-leverage work: small improvements to velocity compound across every researcher and every run. Responsibilities Build and improve the RL training infrastructure that researchers depend on day-to-day Identify and remove bottlenecks across the RL stack: debugging, profiling, and rearchitecting where needed Partner closely with researchers and with adjacent engineering teams (inference, sandboxing, and many more) to understand pain points and ship tooling that makes them faster Own the reliability and performance of research runs end-to-end Contribute to design decisions that shape how Anthropic does RL at scale You may be a good fit if you Have strong software engineering fundamentals and a track record of building performant, reliable systems Have worked on ML infrastructure, distributed systems, or research tooling Care about enabling other people's work and find leverage through platforms rather than individual experiments Are comfortable operating across the stack, from low-level performance work to RL algorithms Have a bias toward shipping and iterating quickly, with a mix of high agency and low ego Strong candidates may also have Experience with large-scale distributed training (RL, pre-training,

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in Singapore. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. 50% travel is expected. In this role you will Own technical delivery across multiple deployments from first prototype to stable production. Build full-stack systems that deliver customer value and sharpen how we learn. Embed closely with customer teams, understand their needs, and guide adoption of what you build. Scope work, sequence delivery, and remove blockers early. Make trade-offs between scope, speed, and quality; adjust plans to protect delivery. Contribute directly in the code when progress or clarity depends on it. Codify working patterns into tools, playbooks, or building blocks that others can use. Share field feedback that helps Research and Product understand where the models succeed and where they can improve. Keep teams moving through clarity and follow-through. You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work. Have scoped and delivered complex systems in fast-moving or ambiguous environments. Write and review production-grade code across frontend and backend using P

The Site Reliability Engineering team designs and builds the global infrastructure on which we deploy our services, focusing on the above mentioned flagship MongoDB Atlas platform. As our customers grow and globalize, our services must satisfy demands for low-latency requests around the globe, and comply with various data sovereignty requirements. The SRE Team’s mission is to build this increasingly complex infrastructure, while continually lowering the operational burden associated with it, and increasing our internal visibility into the health of the system. We are strong believers in infrastructure-as-code and self-healing systems. The SRE Team is fully integrated with all the other engineering teams, and the teams work closely together with a soft and traversable boundary between their areas of responsibility. We are looking to speak to candidates who are based in New York City for our hybrid working model. Responsibilities Design and build the infrastructure for a global cloud service that comprises hundreds of thousands of MongoDB clusters, processes a billion metrics per day, and replicates tens of billions of database writes to our backup service Design, implement, and troubleshoot the automation and monitoring of services that seamlessly spans the globe - including several cloud providers Become an expert in infrastructure performance, helping us optimize from the application level all the way through the firmware Build for resilience. Our goal is that nobody’s pager goes off, ever. Are we there yet? No. Are we really close? Very. While we work on that - participate in a weekly on-call rotation Improve our infrastructure capabilities, optimizing for cost, simplicity, and maintainability Requirements 3+ years of experience running a mission critical service at scale in a Linux environment Firm grasp of at least one modern programming language, beyond basic scripting Familiarity with web and network protocols and standards (HTTP, TLS, DNS, etc) Bachelor’s deg

As an Enterprise Sales Engineer, you will provide technical expertise through sales presentations, product demonstrations, and supporting technical evaluations (POVs). Sales Engineers help qualify and close opportunities with customers and partners and have a voice with the product team to help prioritize features based on input from customers, competitors, and partners. At Datadog, we place value in our office culture—the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Partner with the Sales team to articulate the overall Datadog value proposition, vision and strategy to customers Own technical engagement with customers during the trial phase. Communicate Datadog’s value based on activities and work with customers on any identified issues or concerns to successful conclusion Technically close complex opportunities through advanced competitive knowledge, technical skill, and credibility Deliver product and technical briefings / presentations to potential clients Maintain accurate notes and feedback in CRM regarding customer input both wins and losses Proactively engage and communicate with customers and Datadog business/technical teams regarding product feedback and competitive landscape Who You Are: Passionate about educating customers on observability risks that are meaningful to their business, and able to build and execute an evaluation plan with a customer Someone with strong written and oral communication skills. This role requires an ability to understand and articulate both the business benefits (value proposition) and technical advantages of our offering Experienced in programming/scripting with any of the following: Java, Python, Ruby, Go, Node.JS, PHP, and .NET etc. Someone with a minimum of 3+ years in a Sales Engineering or DevOps Engineering role Role requires regular travel to client si

Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Site Reliability Engineer As a part of Sony Computer Entertainment, the Gaming, Developer & Future Technology Group ( GDFT ) is leading the cloud gaming revolution, putting console-quality video games on any device, from TVs to consoles to mobile devices and beyond. Our Site Reliability Engineering team plays a significant role in delivering on the promise of a great cloud gaming experience to our customers. We do this by influencing design and operational decisions towards the overall stability of the gaming service. Our SREs focus on three main things: overall ownership of production, production code quality, and deployments. The successful candidate will be self-directed and able to participate in the way we make decisions at different levels. We expect our SREs to have opinions on the state of our service and provide critical feedback during different phases of the operational lifecycle. We are engaged throughout the software development lifecycle, ensuring the operational readiness and stability. What you'll be doing: Lead team technical discussions, especially around ongoing improvements in Reliability and Scalability Be involved in creating High Level Designs (HLDs) for new products and platforms Mentor junior SRE staff and enable t

Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Senior Service Reliability Engineer As a part of Sony Interactive Entertainment, the Gaming, Developer & Future Technology Group ( GDFT ) is leading the cloud gaming revolution, putting console-quality video games on any device, from TVs to consoles to mobile devices and beyond. Our Site Reliability Engineering team plays a significant role in delivering on the promise of a great cloud gaming experience to our customers. We do this by influencing design and operational decisions towards the overall stability of the gaming service. Our SREs focus on three main things: overall ownership of production, production code quality, and deployments. The successful candidate will be self-directed and able to participate in the way we make decisions at different levels. We expect our SREs to have opinions on the state of our service and provide critical feedback during different phases of the operational lifecycle. We are engaged throughout the software development lifecycle, ensuring operational readiness and stability. What you'll be doing: Taking a leadership role in ongoing improvements in Reliability and Scalability Work closely with SRE Management to define KPIs, processes and drive continuous improveme