Enterprise Ai Transformation Lead Jobs

About the Team OpenAI's GTM Partnerships team builds a strategic, global partner ecosystem to accelerate customer success, enable enterprise AI adoption, and drive durable growth in support of OpenAI's mission toward AGI. We work cross-functionally across Product, Engineering, Security, Legal, Marketing, Customer Success, and Sales to turn strategic partnerships into measurable business outcomes. This role sits within the GTM Partnerships organization and is responsible for leading OpenAI's strategic relationships with three of the world's largest Global Systems Integrators (GSIs): HCLTech, Wipro, and Cognizant . These partners play a critical role in helping enterprise customers design, deploy, and scale AI solutions by combining OpenAI's technology with deep industry expertise, consulting capabilities, and global delivery organizations. This role reports to the Head of GSIs and will be responsible for driving executive alignment, joint go-to-market strategy, commercial execution, and scalable partnership programs across these strategic accounts. About the Role We are hiring a Partner Director, HCL, Wipro & Cognizant to lead and grow three of OpenAI's most strategic Global Systems Integrator partnerships. You will own executive relationships, develop and execute joint business plans, and drive coordinated go-to-market motions that accelerate customer adoption and revenue growth. This is a highly strategic, externally facing role that requires a blend of executive relationship management, commercial leadership, operational excellence, and ecosystem expertise. You'll work closely with OpenAI Sales, Solutions Engineering, Customer Success, Product, Marketing, Legal, Security, and partner leadership teams to build repeatable motions that generate pipeline, enable successful customer deployments, and deepen long-term strategic alignment. The ideal candidate understands how large consulting organizations operate, has experience driving revenue through strategic partn

Client Onboarding Director, Inference and Agentic AI Location: Noida Company: Paytm About Paytm Paytm is a pioneer of digital payments in India, serving over 450 million consumers and 45 million merchants across payments, financial services, and commerce. Over the years, Paytm has built deep in-house capabilities across technology, data, and operations to operate at scale with high reliability. Paytm is building a full stack AI platform focussed on Inference and Agents, enabling large enterprises to deploy AI driven automation across sales, service, operations, and analytics. The Inference and Agentic AI team operates as a cross functional unit spanning engineering, product, data science, business management, and sales, and owns the full lifecycle of AI solutions from opportunity discovery to deployment and scale. Role Overview Paytm is looking to hire a Client Onboarding Director to own implementation delivery and client onboarding governance for Paytm’s AI Inference and Agentic AI products across enterprise clients. This is a managerial role that will lead Client Onboarding Managers and ensure that enterprise deployments move smoothly from sales closure to go live and early adoption. The role sits at the intersection of client teams, product, engineering, business, and sales, and is responsible for converting signed enterprise deals into successful, timely, and scalable deployments. The candidate will own delivery planning, integration governance, risk management, stakeholder communication, and post go live stabilization across enterprise AI agent deployments. The role requires strong program management, technical understanding, client handling, and ability to drive execution across multiple internal and external teams. Key Responsibilities Delivery Ownership and Implementation Governance Own end to end delivery governance for enterprise AI agent deployments from sales handoff to go live and stabilization. Lead the implementation planning process across scope

WHAT IS BOX? Box (NYSE:BOX) is the leader in Intelligent Content Management. Our platform enables organizations to fuel collaboration, manage the entire content lifecycle, secure critical content, and transform business workflows with enterprise AI. We help companies thrive in the new AI-first era of business. Founded in 2005, Box simplifies work for leading global organizations, including JLL, Morgan Stanley, and Nationwide. Box is headquartered in Redwood City, CA, with offices across the United States, Europe, and Asia. By joining Box, you will have the unique opportunity to continue driving our platform forward. Content powers how we work. It’s the billions of files and information flowing across teams, departments, and key business processes every single day: contracts, invoices, employee records, financials, product specs, marketing assets, and more. Our mission is to bring intelligence to the world of content management and empower our customers to completely transform workflows across their organizations. With the combination of AI and enterprise content, the opportunity has never been greater to transform how the world works together and at Box you will be on the front lines of this massive shift. WHY BOX NEEDS YOU We have a dynamic team of consultants and technologists who are dedicated to making our customers successful, but our customers' needs are getting even more sophisticated and technically complex. We are looking to add more consultative and technical muscle to the Technology Consulting team in order to solve our customers' most complex challenges through the application of thought leadership and technical domain expertise. WHAT YOU'LL DO Box is growing fast. Every business in the world is looking to modernize the way that they work. As the leader in cloud content management, Box has what it takes to enable enterprises to transform how people work together. We engage directly with the largest and most complex enterprises in the wo

Most PMs sit behind a roadmap. You'll be in the room where the AI actually gets deployed, then back at HQ making sure what you learned changes the product. The Company Sendbird is on a mission to build the AI workforce of tomorrow. For over a decade, we built the infrastructure behind conversations, chat, voice, video, messaging APIs, and became the #1 CPaaS platform for in-app communications. 4,000+ brands trust us. 7 billion messages flow through our platform every month. 300 million monthly active users. We powered conversations for DoorDash, Match Group, Noom, Yahoo Sports, Rakuten, and thousands of others. We were good at what we did. Really good. We also saw it early: AI would fundamentally reshape how businesses talk to customers. The infrastructure we'd spent a decade building would become commoditized. The value would move up the stack, into intelligence, into experience, into outcomes. We had a choice: protect what we built, or reinvent ourselves. We chose reinvention. In December 2024, we made the full strategic pivot to AI-first customer experience. By February 2025, we'd launched our AI agent for enterprise CX, built on a decade of conversation data, now with intelligence on top. And in November 2025, we rebranded to Delight.ai. The name says it all. AI's real promise isn't efficiency or cost savings. It's giving customers back something they lost, the feeling of being truly understood and cared for. Not satisfied. Delighted. The Product Delight.ai is the AI concierge for customer experience. Most AI agents forget you the moment the conversation ends. Ours doesn't. Delight.ai builds memory over time, learns preferences, and connects context across every channel, chat, SMS, email, voice, WhatsApp, without losing the thread. We're building AI that makes customers feel understood, seen, and remembered. Why Forward Deployed Product Manager Enterprise AI deployments don't fail because the technology is wrong. They fail because no one bridges th

About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Available Location: NYC Metro About the role The Enterprise AI and Digital Natives segment is Cloudflare's fastest growing and highest visibility market. This segment is dedicated exclusively to the largest organizations in the modern tech economy including premier SaaS platforms, hyperscale digital marketplaces, and leading AI labs. This is a deep infrastructure, developer centric play where technical alignment and deep engineering partnerships a

Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. For over 180 years, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers. The Senior Product Manager will lead the strategy, development, and management of AI-native products within our portfolio. This role involves driving product vision, market analysis, and cross-functional collaboration to deliver innovative solutions that meet customer needs and align with business goals. The Senior Product Manager will be responsible for overseeing the product lifecycle from ideation through to launch and beyond, ensuring the product’s success in the market.

About the Team The Applied AI team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and enterprises. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of GenAI use cases for their industry and drive them to production through strong technical guidance. As the leader of our ADEs in the Large Enterprise segment, you’ll help companies transform their business through solutions such as customer service, automated content generation, and novel applications that make use of our newest, most exciting models. About the Role We are seeking an Applied AI Engineering leader to ensure the technical success of our most strategic Large Enterprise customers across EMEA. In this role, you will manage the entire implementation journey, ensuring seamless platform integration. As the voice of our customers, you will align technical teams to deliver a consistent and exceptional experience throughout the customer lifecycle. Success will be measured by live production applications, increased API adoption, and impactful customer stories that demonstrate the value of our technology. This role is open in both our London and Munich offices. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own the strategy and operating model of the Large Enterprise Applied AI team, ensuring alignment with company objectives and the evolving needs of our customers. Lead, build, and mentor a team of high-performing ADEs to deliver exceptional customer outcomes, as demonstrated by production customer applications and increased API adoption. Serve as the technical advocate for our customers, synthesizing their needs to develop the Research and Applied Product/Engineering roadmaps. Act as the primary technical escalation point during development, fostering trust and maintaining direct communication with executive-level

Scale GP (Scale Generative AI Platform) is an enterprise-grade AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our core infrastructure in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will implement solutions across multiple cloud providers (GCP, Azure, AWS) for customers in diverse, highly-regulated industries like healthcare, telecom, finance, and retail. What You’ll Do: Architect multi-cloud systems and abstractions to allow the SGP platform to run on top of existing Cloud providers Implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Collaborate with platform, product teams and our customers directly to develop and implement innovative infrastructure that scales to meet evolving needs. Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly What We’re Looking For: 4+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) Excellent communication skills with the ability to explain technical concepts to both technical and non-technical audiences 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 fo

Scale GP is Scale's enterprise Generative AI platform—APIs and infrastructure for knowledge retrieval, inference, evaluation, and intelligent automation. We power mission-critical workflows for leading enterprises, helping teams turn complex data and models into reliable, production-ready AI systems. We're building a new AI Enablement team to create the next generation of agent-powered tools that ground AI in real operational workflows. Our goal: help internal teams demystify their own workflows, then deploy agentic systems that reason over data, take action, and deliver measurable outcomes. We don't build in a vacuum. You'll use our own platform to solve real business problems internally—then selectively commercialize that same stack for customers. What we run on is what we sell. This is a 0→1 team. We're looking for a sharp, product-minded engineer who thrives in ambiguity, moves fast, and loves building systems from scratch alongside customers and cross-functional partners. You'll work closely with product, forward-deployed engineers, data scientists, and applied AI teams to turn real-world problems into scalable production solutions. If you like shipping fast, owning outcomes, and working across the stack—from polished frontends to distributed backends to LLM integrations—this role is for you. What You’ll Do Own full-stack features and projects end-to-end — from design through production deployment — within a larger product area Sample surfaces - Accounting Agents, Finance Copilots, GTM Agents, Agentic Experimentation Platforms Develop reliable backend services in Typescript/Python, work with distributed systems, data pipelines, and AI/ML infrastructure Integrate LLMs, vector databases, and agentic frameworks to power intelligent workflows Ship quickly through tight experimentation loops while maintaining high quality and reliability Adapt across the stack and learn new tools as needed to solve real problems end-to-end Ideal Experience 3+ years of full-tim

We are seeking a highly skilled Staff IT Product Manager for Internal AI to drive the strategy, delivery, and adoption of AI-powered solutions across our enterprise IT landscape. This role will be pivotal in shaping how AI transforms our internal operations, from service delivery and knowledge management to automation and decision support. The ideal candidate has a proven track record of managing enterprise-scale AI/ML products, collaborating across IT and business functions, and delivering measurable impact. We are looking to speak to candidates who are based in San Francisco, CA or Palo Alto, CA for our hybrid working model. Key Responsibilities AI Product Strategy & Roadmap Define and execute the internal AI product strategy aligned with enterprise IT and business goals Own multiple product lines in the internal AI product space Prioritize high-value use cases across IT functions (helpdesk, infrastructure, security, applications, enterprise data) Balance quick wins (AI copilots) with longer-term bold initiatives (AI-driven automation and decision-making) Experience in implementing AI solutions for enterprises our size and scale. This should include enabling agentic platforms for organizations and bringing to the table the best practices, pitfalls and learnings from such experiences Product Management Execution Embrace the product mindset and own the lifecycle of AI products—from ideation, critical user journey definition, requirements gathering, vendor evaluation, prototyping, and implementation to scaling in production Define and manage product backlogs, roadmaps, and success metrics Drive adoption and ensure AI solutions are delivering measurable outcomes (efficiency, cost savings, user experience) Stakeholder Engagement Partner with IT leaders (Applications, Infrastructure, Security, Service Desk) to identify pain points and AI opportunities Collaborate with business stakeholders to ensure alignment and secure sponsorship for AI initiatives Communica

Job Details: Job Description: Intel's Design Quality and Reliability organization is seeking an AI Platform Engineer to architect and build an enterprise-grade AI platform for mission-critical engineering work. This platform will enable Intel engineers to analyze complex design, qualification, and reliability data; automate engineering workflows; access organizational knowledge; and make faster, evidence-based decisions throughout the product lifecycle. The successful candidate will combine strong software engineering fundamentals with expertise in AI-native and agentic development. They will be highly proficient with Agentic AI coding assistants and able to use these tools responsibly to accelerate architecture, implementation, testing, debugging, and documentation. This role requires close collaboration with Design, Quality and Reliability, Product Engineering, Manufacturing, IT, Information Security, and other Intel stakeholders. Responsibilities 1. Architect and develop Intel's reusable AI platform for Design Quality and Reliability. 2. Build AI agents and workflows for engineering data analysis, qualification planning, risk assessment, knowledge retrieval, reporting, and process automation. 3. Apply Agentic AI coding assistants to accelerate software development while maintaining rigorous engineering review and validation. 4. Integrate AI capabilities with Intel engineering databases, quality-management systems, internal APIs, spreadsheets, documentation repositories, and workflow tools. 5. Develop production-grade backend services, APIs, data pipelines, model gateways, and agent-orchestration components. 6. Establish shared platform capabilities for identity, access control, tool authorization, memory, observability, evaluation, and auditability. 7. Implement human approval, deterministic validation, and rollback controls for consequential engineering actions. 8.

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Join the Pure Solutions team as a Senior MLOps Solutions Engineer to architect and build high-scale, enterprise-grade AI/ML solutions. You will be instrumental in integrating Pure Storage platforms with the evolving open-source MLOps ecosystem (Kubeflow, MLflow, Ray) to operationalize the complete machine learning lifecycle. This role requires a creative technologist with deep Python expertise to drive innovation and enable our customers and partners to achieve production AI success. WHAT YOU'LL DO Design and Automate MLOps Pipelines: Lead the development of end-to-end MLOps workflows using CI/CD tools (Git/Jenkins) and orchestration platforms (MLflow/Kubeflow), specifically integrating Pure Storage's FlashBlade, FlashArray, and Portworx as the high-performance data plane for data ingestion, training, and inference. Build High-Performance AI/ML Reference Architectures: Create validated, repeatable deployment models using Infrastructure as Code (e.g., Ansible, Terraform) for AI/ML environments spanning bare metal, virtual machines, and GPU-accelerated Kubernetes clusters, ensuring optimal performance for distributed training. Optimize and Operationalize GPU Inference: Architect and implement solutions for high-throughput, low-latency model serving, utilizing technologies like NVIDIA Triton Inference Server and advanced optimization techniques (quantization, model sharding like DeepSpeed/Megatron-LM, and dynamic bat

- Proven experience deploying and managing Kubernetes clusters for AI/ML workloads. Experience of at scale deployments with Azure Kubernetes. Experience level - 5 Years or more Positions - 2 Proven experience deploying and managing Kubernetes clusters for AI/ML workloads. - Experience of at scale deployments with Azure Kubernetes Service, RedHat OpenShift, Microk8s and Helm Charts. - Expertise with infrastructure and resource management and virtualization tools such as VMWare/EXSi, KVM, Ansible, Redfish. - Strong understanding of Run:AI platform, including job scheduling, quota management, and GPU virtualization. - Knowledge of NVIDIA AI Enterprise components including, NIM, NeMO, TAO, Triton and Nucleus Servers - Familiarity with DGX systems, Jetson, and NVIDIA’s AI Factory components. - Proficiency in Python, C++, and optionally .NET/C# for enterprise integration.

AI Tech Lead – Manager Experience- 8-12 years Job Overview: We are seeking a highly experienced AI Tech Lead to design, develop, and deliver scalable AI-driven applications while leading cross-functional teams. The role involves end-to-end ownership of AI solutions, including architecture design, deployment, and optimization, ensuring alignment with business objectives. The candidate will collaborate with stakeholders, data engineering teams, and product management to build enterprise-grade AI systems leveraging modern cloud and AI technologies. Key Responsibilities / (Person Specifications): Lead implementation and delivery of AI applications across teams. Design end-to-end AI architectures integrating open-source and enterprise tools. Translate business requirements into scalable AI solutions. Define architecture roadmaps and best practices. Build data pipelines, CI/CD, and monitoring systems. Deploy scalable systems using Docker and Kubernetes. Ensure performance, scalability, and security. Mentor teams and drive knowledge sharing. Key Skills / Job Specifications (Mandatory): AI frameworks: LangGraph, AutoGen, CrewAI. Strong Python with TensorFlow, PyTorch, Keras. Knowledge of NLP & Deep Learning (RNN, CNN, LSTM, Transformers). Cloud platforms: AWS / Azure / GCP. Docker, Kubernetes, CI/CD tools. Terraform / CloudFormation (IaC). SQL & NoSQL databases. Distributed systems, REST APIs, GraphQL, microservices.

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. This role owns the EMEA go-to-market motion for NVIDIA's Agentic AI Platform, helping customers and partners adopt, deploy, secure, and scale agentic AI on NVIDIA. The role works across enterprise, AI-native, ISV, cloud provider, public sector, defense, and regulated environments, translating NVIDIA software into practical adoption motions for priority workloads. The person should bring strong breadth across open and sovereign models, Nemotron, NVIDIA Agent Toolkit, NeMo, NIM, secure agent runtimes, evaluation harnesses, guardrails, confidential computing, cybersecurity, legal/commercial guidance, and AI Factory reference architectures What you'll be doing: Execute the EMEA Agentic AI Platform GTM plan across open models, Nemotron adoption, regulated software hardening, confidential computing, cybersecurity, and secure AI deployment. Position NVIDIA Agent Toolkit, NeMo, Nemotron, NIM, Dynamo, CUDA-X libraries, evaluation harnesses, guardrails, DGX OS, and AI Enterprise as one adoption path. Refine the sales toolkit across technical, commercial, legal, support, and terms-and-conditions tracks so field teams and partners can confidently position