Tool Install Engineer Jobs

The Solutions Org drives customer acquisition and accelerates revenue growth through a mastery of strategic sales and Asana platform expertise. We are trusted advisors for our prospects and clients. Our team bridges the gaps between the voice of business and voice of customer, gathering first-party insights to fuel & inspire further evolutions of our software platform, thereby enabling the world’s teams to work effortlessly today and into the future. As a Solutions Consultant you will play a critical role in supporting our prospects within the UKI region to understand the value of Asana. Through your deep product knowledge and ability to translate customer needs and pains into a tool-based solution, you will support our EMEA Sales teams as a co-seller and ensure they constantly move towards close. This role is based in our London 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 the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Be a thought leader in AI-powered Collaborative Work Management Partner with Sales teams to develop and drive account strategy for key accounts Develop deep understanding of customer needs and articulate how Asana can address those pain points by presenting a solution and its business impact Identify and scale solution-selling best practices to the broader Revenue organisation Position yourself as a trusted advisor for colleagues and customers Be a key player in helping Asana achieve its revenue goals Be a storyteller and help customers imagine completely new ways of working Support our presale scale motions such as office hours and content generation About you Minimum 3+ years in Presales, Solutions Consulting, Technical Sales, Sales Enginee

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Primary Responsibilities AI-Driven Process & Yield Innovation Initiate and lead new AI/data solutions to uncover process, test, and design improvement opportunities, with specialization including but not limited to: UE_ROW & all quality indices Front End-PTS integration High-value-bits (PG2+) yield Any yield improvement area spanning process, equipment, test, and design domains Develop AI-enabled modeling, monitoring, and benchmarking frameworks that push tool performance to best-in-class standards Champion process equipment prognostics and process integration optimization through machine learning and agentic AI frameworks Identify test optimization opportunities that directly translate into higher product grade yield Proactively discover and pursue new yield improvement vectors through data-driven insights and AI-assisted root cause analysis AI Agent Skill Development & Management Take end-to-end ownership of AI agent skill development — from requirements gathering and skill design to testing, deployment, and continuous improvement Architect and manage a portfolio of AI agents and skills tailored to semiconductor engineering use cases — including process monitoring, yield analysis, equipment diagnostics, and test optimization Prototype AI-assisted solution mock-ups, validate feasibility, and demonstrate measurable

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Key Responsibilities Capacity Optimization & Advanced Analytics Develop optimization models to improve factory capacity utilization, throughput, cycle time, tool loading, and bottleneck management. Build mathematical models for capacity planning, production allocation, constraint identification, and investment prioritization. Apply operations research techniques such as linear programming, mixed-integer programming, constraint programming, stochastic optimization, and simulation-based optimization. Design algorithms to support factory maxout strategies and identify opportunities to unlock additional capacity without unnecessary capital investment. Semiconductor Manufacturing Problem Solving Partner with manufacturing, industrial engineering, planning, equipment, process, and business teams to understand capacity constraints and operational challenges. Analyze tool capability, process flows, product mix, WIP movement, cycle time, dispatching rules, and factory constraints to recommend optimization opportunities. Support scenario analysis for capacity expansion, product mix changes, technology transitions, and capital planning decisions. Develop data-driven recommendations that improve decision quality

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. Replit is experiencing extraordinary demand and seeking an Account Executive with strong communication skills to drive our hyper-growth. Candidates with SaaS experience, particularly with some technical background (i.e. having some coding knowledge or prior experience at other developer tool companies) are ideal. This full-cycle sales position encompasses new client acquisition. We believe this role offers a distinctive opportunity for people who excel in client-facing situations and have a passion for driving sales and AI. You'll leverage your skills to effectively communicate Replit's value proposition: a world where anyone can create software using natural language. In this role you will: Evangelize a future where anyone can create software in natural language, ushering in a change in the nature of the firm on par with the PC era Serve as the primary point of contact for prospects and customers, guiding them through the buying journey Conduct compelling product demonstrations and help realize the art of the possible by orchestrating non-engineering hackathons Articulate Replit's value proposition and align it with customers' business objectives Collaborate with product and engineering teams to ensure technical accuracy and successful delivery Prepare tailored quotes and skillfully negotiate deals Maintain accurate customer and forecasting data in Replit’s CRM (Hubspot) Foster strong relationships with existing clients while identifying opportunities for expanded adoption Optimize customers' use of the Replit platform through ongoing collaboration and support Gather and communicate valuable customer feedback, championing their interests within Replit Required skills and experience: Experience in AE or SE/technical sa

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. Replit is experiencing extraordinary demand and seeking an Account Executive with strong communication skills to drive our hyper-growth. Candidates with SaaS experience, particularly with some technical background (i.e. having some coding knowledge or prior experience at other developer tool companies) are ideal. This full-cycle sales position encompasses new client acquisition. We believe this role offers a distinctive opportunity for people who excel in client-facing situations and have a passion for driving sales and AI. You'll leverage your skills to effectively communicate Replit's value proposition: a world where anyone can create software using natural language. In this role you will: Evangelize a future where anyone can create software in natural language, ushering in a change in the nature of the firm on par with the PC era Serve as the primary point of contact for prospects and customers, guiding them through the buying journey Conduct compelling product demonstrations and help realize the art of the possible by orchestrating non-engineering hackathons Articulate Replit's value proposition and align it with customers' business objectives Collaborate with product and engineering teams to ensure technical accuracy and successful delivery Prepare tailored quotes and skillfully negotiate deals Maintain accurate customer and forecasting data in Replit’s CRM (Hubspot) Foster strong relationships with existing clients while identifying opportunities for expanded adoption Optimize customers' use of the Replit platform through ongoing collaboration and support Gather and communicate valuable customer feedback, championing their interests within Replit Required skills and experience: Experience in AE or SE/technical sa

About Paytm Group: Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm’s mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology. About the Role- Expectations/ Requirements: -Own marketing campaign operations & implementation design logic end to end in alignment with the marketing strategy decided upon -Own the monitoring and tracking of metrics useful for performance analyses of campaigns -Set up and run experiments on campaigns -Streamline operations for reduced errors and increased efficiency -Run root cause analyses and narrow down the cause(s) in cases of deviations from expected campaign behavior Superpowers/ Skills that will help you succeed in this role: -Familiarity with any CLM tool. Prior experience with CleverTap will be an added advantage. -Aptitude – good with logical reasoning, breaking down problem statements, and hypothesis formation and validation -Ownership – Own campaigns end to end from execution to assessment to accommodating learnings – the candidate should be interested in the role or else it will be difficult to gather ownership and excel -Previous experience in operations is preferred - not mandatory Why join us? A collaborative output driven program that brings cohesiveness across businesses through technology Improve the average revenue per use by increasing the cross-sell opportunities A solid 360 feedback from your peer teams on your support of their goals Respect, that is earned, not demanded from your peers and manager Compensation: If you are the right fit, we believe in creating wealth for you With enviable 500 mn+ registered users, 17 mn+ merchants and depth of data in our ecosystem, we are in a unique position to democratize credit for deserving consumers & merc

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. OMT Metro Application M1 Job Description Summary OMT Metro Applications M1 leads the team to drive yield improvement and metrology tool path expansion to support scaling needs and improve process window margin through advanced application development, cross-fab standardization, and team capability build-up. This is an outstanding opportunity to be part of a world-class engineering team that is dedicated to pushing the boundaries of technology and innovation. Responsibilities Drive metrology application strategy to improve yield, detection capability, and cost efficiency Develop and optimize metrology recipes and methodologies to improve sensitivity, accuracy, and robustness Enable shift-left defect detection and accelerate yield learning Align with suppliers on technology roadmaps, capability gaps, and new solution development Establish and standardize BKMs and guidelines across fabs Lead cross-functional execution to close technical gaps and deliver key initiatives Build and develop team capability, including a clear ownership structure and strong technical depth Requirements GJS: E3 with two years of expe

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, Artifacts, you will train frontier models to create polished, useful work products: documents, spreadsheets, slide decks, dashboards, reports, analyses, and other interactive or editable artifacts. You will help teach our models to move from a vague user goal to a finished artifact with strong structure, visual taste, domain judgment, correctness, and low latency. This work will require owning improvements across our post-training stack, including RL, data pipelines, graders, reward signals, evals, and behavioral analysis. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you will: Design and run experiments that improve agentic model behavior for complex so

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, Computer Use, you will teach models to operate computers. You will help train models that can navigate browsers and desktops, use tools and applications, reason through complex workflows, collaborate with users and other agents, and complete long-horizon tasks with reliability and judgment. This work sits at the intersection of frontier model training, product behavior, evaluation, and systems engineering, and will directly shape the computer-use capabilities shipped in OpenAI’s next generation of agents. Currently, our models are the best in the world at this behavior! You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might Design and run experiments th

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, Connectors, you will teach models how to interface with the top professional software using code. You will help train agents to use code, APIs, tools, and structured integrations to operate across applications like Slack, Google Workspace, GitHub, Notion, Linear, Salesforce, and other core systems of work. You will help enable models to take useful actions across a user’s digital context: finding information, updating systems, coordinating work, generating artifacts, and completing multi-step workflows through the tools teams already use. You will train models to be supercharged by the world’s most important productivity and enterprise software, turning connected tools into a powerful action surface for our agents. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people.

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role We believe that the final enabler for AGI is spending compute on context. As a Context Researcher on Agent Post-Training, you will scale compute spent on context. You will get to work in our frontier training stack on enabling the next paradigm of model training with a clear product interface for iterative deployment (Codex Chronicle). You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might Design and run experiments that improve scaling of compute on context. Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis. Build evals and environments that expose the next set of model failures,

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a researcher working on Frontier Evals & Environments, you will help build north star model environments to drive progress towards safe AGI/ASI. Your work will directly guide the research programs of the most ambitious training runs happening at OpenAI. Some prior open-sourced evaluations built by researchers in this role include GDPval , SWE-bench Verified , MLE-bench , PaperBench , and SWE-Lancer . If you are interested in feeling firsthand the fast progress of our models, and steering them towards good outcomes, this is the role for you. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might Create ambitious RL environments to push our models to their limits, and measure frontie

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team builds the data, environments, graders, training methods, and feedback loops that shape what OpenAI’s next agents can do and what they are like to work with, then carries those improvements through major training runs and into products used by people every day. About the Role As a member of the Agent Post-training Personality team, you will help make OpenAI’s agents exceptional collaborators. You will study what makes an agent thoughtful, clear, perceptive, appropriately proactive, and genuinely easy to work with, then translate those insights into evals, training data, reward signals, and model improvements. We use “personality” to mean much more than writing style or general likability. It includes whether an agent understands what the user is trying to accomplish, communicates with good judgment, adapts to context, asks useful questions, handles disagreement honestly and takes initiative at the right moments. The goal is to create a strong, tasteful default that can adapt to different people and situations. This work combines behavioral research, product thinking, research and communication taste. You will collaborate with product teams, human experts, and researchers across post-training and pretraining to ensure that improvements survive the full trai

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of this API & power-users team, you will improve the capabilities, reliability, and product fit of OpenAI’s agentic models for power users and API developers. You might design evals from real developer workflows, build training environments around production-like tool use, turn qualitative model failures into training data, evals, or post-training interventions, or drive a behavior improvement from discovery through post-training, integration, and launch. This role is intentionally broad. The strongest candidates are comfortable turning ambiguous model behavior problems into concrete progress, whether that means improving tool use, planning, instruction following, recovery from mistakes, or how models behave in API-based workflows. You should be excited to work across research, engineering, data, evals, and product to make models better at acting in real workflows. You will work closely with researchers, engineers, API/product teams, Codex, infrastructure, and safety/align

The team + the role Pendo's Applied AI team turns AI infrastructure into real business outcomes across Sales, Marketing, and Customer Engineering. AI here isn't a feature we bolt on — it's how we scale GTM capability across the company. We build AI that makes GTM teams measurably faster and more effective, and we measure success by whether those teams are actually using what we ship and getting real value from it. As an Applied AI Engineer, you'll own the full lifecycle of AI-powered solutions — from problem definition and prompt design through to production deployment and ongoing iteration. You'll work directly with GTM stakeholders to identify high-value problems, set realistic expectations about what AI can and can't do, and ship solutions that stick. The best person for this role has a strong engineering instinct, deep curiosity about how businesses operate, and the judgment to know when AI is the right tool — and when it isn't. This role is based in Raleigh, NC and follows Pendo's hybrid model: in-office 3 days per week. What this looks like day-to-day Own AI solutions end-to-end: problem definition, prompt design, production deployment, monitoring, and iteration — you ship, you watch, you improve. Build and manage GTM workflow automations that reduce manual work across Sales, Marketing, and Customer Engineering systems, including Slackbots and other integrations. Partner directly with GTM stakeholders to surface high-value problems, validate solutions, drive adoption, and set honest expectations about AI capabilities and limitations. Develop and maintain prompt management practices that make AI outputs reliable, auditable, and improvable over time — treat prompts as production code, not experiments. Work with the Data Platform and Systems teams to identify foundational tooling gaps and contribute clear, actionable requirements based on what you encounter in production. Share reusable AI workflow patterns and tool findings with the broader team — your impact sh