Lead Technical Program Manager Knowledge Systems Salary India in United States

We’re looking for a Senior Engineering Manager who is ready to lead through ambiguity and improve how software gets built at MongoDB. This role leads teams focused on developer productivity, with an emphasis on measurable improvements to the software development lifecycle. This role can be based remotely in the United States. The Team The AXIS team (AI, X-functional tools, Insights, and Signals) sits within Developer Productivity and is responsible for overseeing the metrics and observability infrastructure of our expansive developer environment to help build a strong data-driven culture. You’ll also be a key partner in building the agentic ecosystem for AI-driven development across engineering. Candidate Profile We’re looking for an experienced leader with a passion for solving the big challenge of measuring developer productivity and providing the actionable signals that help teams improve their performance. They should be comfortable working collaboratively with other leaders and partners across our Engineering and Data teams in maximizing the use of data for insights and AI enablement. The right candidate for this role will have 4+ years of experience managing software engineers, including hiring, performance management, growth planning, and compensation; required for external candidates and preferred for internal candidates 8+ years of hands-on software engineering experience building and operating production systems; experience in developer tooling, platform engineering, observability, or data engineering is a strong plus Demonstrated the ability to lead through ambiguity, work across team boundaries, and deliver outcomes without close supervision Strong customer orientation and sound judgment in finding practical, high-leverage solutions Experience working with systems involving analytics, data pipelines, and metrics platforms Experience with AI tools development and enablement efforts Strong technical judgment, including the ability to evaluate t

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . As a principal engineer on the Online Systems team, you’ll join a team that powers Pinterest’s most business-critical online systems at massive scale, driving the reliability, efficiency, and evolution behind every core Pinner and Advertiser experience. You'll lead major efforts like multi-region deployment and Kubernetes migration, set the standard for operational excellence, and define the long-term vision for our online serving infrastructure, supporting machine learning and product innovation across the company. This is an opportunity for high-impact technical leadership, broad visibility, and cross-functional influence at the heart of Pinterest’s platform. What you’ll do: Improve reliability, scalability and infra efficiency for Pinterest’s critical online systems across storage and caching, online service and realtime analytics syste

About the Team The Ecosystem AI Deployment Engineering (ADE) team supports strategic partners as they build high-quality technical integrations into ChatGPT and Codex. Our goal is to create products users depend on, drive adoption and retention, and build an ecosystem where partners win when OpenAI wins. About the Role We are looking for an AI Deployment Engineer to help strategic partners design, build, evaluate, submit, launch, and maintain high-utility plugins for ChatGPT and Codex. This is a hands-on, partner-facing product engineering role for someone who can contribute to the platform itself, lead sophisticated partner engagements, and translate ambiguous product needs into production-ready integrations. You will work across partner product and engineering teams and OpenAI's product, engineering, partnerships, legal, policy, design, and go-to-market teams. You will identify the right use cases, prototype and review implementations, run evaluations, debug issues across systems, guide partners through submission and review, and support launch and post-launch iteration. The best person for this role moves fluidly between code, product judgment, project leadership, and clear communication with engineers and executives. This role is a fit for a product minded engineer who wants to stay close to users and partners while still going deep on code, reliability, evaluations, and developer experience. The goal is to help partners ship plugins that are not merely technically functional, but genuinely useful in ChatGPT and Codex. This role is based in our San Francisco office. 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 technical partner journey for priority B2B plugins—from pitch and readiness assessment through architecture, build, evaluation, submission, launch, and ongoing maintenance. Identify strong plugin use cases, define crisp user journeys and expected behaviors, and

We anticipate the application window for this opening will close on - 10 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 Neuromodulation Research & Development organization develops therapies and technologies that address chronic pain and other neurological conditions. Within the Interventional Pain portfolio, teams focus on minimally invasive therapies used to treat musculoskeletal pathologies, including vertebral compression fractures, nerve pain, metastatic bone tumors, and benign bone tumors. This role supports the development of system-level verification and validation strategies for new products and enhancements across mechanical, electrical, and software components. This position is based in Santa Clara, California, and follows an onsite work model. No travel is required for this role. As a Research & Development Test Engineer, you will lead and execute verification and validation activities that support the development of interventional pain therapies and associated medical device systems. You will collaborate with cross-functional partners to define test strategies, evaluate product performance, manage technical risks, and generate evidence needed to support product development and regulatory requirements. Primary Responsibiliti

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. CVS Health is seeking an SDET Manager to lead Quality Engineering and software delivery transformation across the Medicare Sales & Acquisition ecosystem. This role is critical to modernizing how we build, test, and deliver software, including embedding AI-driven capabilities into the SDLC. You will translate business workflows (Sales, Enrollment, Broker, and Telesales) into scalable, automated testing solutions that improve speed, quality, and operational efficiency. This is a hands-on technical leadership role responsible for driving test automation strategy, enabling intelligent SDLC pipelines, and building a high-performing engineering team aligned to enterprise goals. This role will also help shape the team's transition toward AWS-native test infrastructure and agent-orchestrated cycles, positioning the organization to scale automation alongside delivery volume in future years. Key Responsibilities Lead the design and implementation of AI-augmented Quality Engineering solutions — including agentic test generation, self-healing frameworks, and AI-assisted defect analysis — advancing the SDLC toward an AI-driven Automated Delivery Lifecycle (ADLC) Drive the migration of automation frameworks and test data management onto AWS-native services (e.g., Bedrock for model orchestration, Lambda/Step Functions for event-driven test pipelines), enabling

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. CVS Health is seeking an SDET Manager to lead Quality Engineering and software delivery transformation across the Medicare Sales & Acquisition ecosystem. This role is critical to modernizing how we build, test, and deliver software, including embedding AI-driven capabilities into the SDLC. You will translate business workflows (Sales, Enrollment, Broker, and Telesales) into scalable, automated testing solutions that improve speed, quality, and operational efficiency. This is a hands-on technical leadership role responsible for driving test automation strategy, enabling intelligent SDLC pipelines, and building a high-performing engineering team aligned to enterprise goals. This role will also help shape the team's transition toward AWS-native test infrastructure and agent-orchestrated cycles, positioning the organization to scale automation alongside delivery volume in future years. Key Responsibilities Lead the design and implementation of AI-augmented Quality Engineering solutions — including agentic test generation, self-healing frameworks, and AI-assisted defect analysis — advancing the SDLC toward an AI-driven Automated Delivery Lifecycle (ADLC) Drive the migration of automation frameworks and test data management onto AWS-native services (e.g., Bedrock for model orchestration, Lambda/Step Functions for event-driven test pipelines), enabling

Work Flexibility: Onsite It's Time to Join Stryker! Stryker is seeking a Staff Systems Engineer, Robotics to lead systems engineering activities for critical electromechanical components within a complex robotic medical platform. In this role, you will serve as a systems engineering owner for robotic end effectors , including powered surgical tools and future attachments that interface directly with the robotic system. You will help translate user and clinical needs into system architecture and requirements, define interfaces across electrical, mechanical, and software disciplines, and guide the product from requirements development through integration and verification. This role requires a highly collaborative engineer who can bring together input from multiple technical disciplines and maintain a system-level view throughout development. What You Will Do Systems Engineering Own systems engineering activities for robotic end effectors and related electromechanical subsystems. Translate user, clinical, and product needs into clear, verifiable system requirements and design inputs. Develop and refine system architectures, interfaces, and functional requirements across electrical, mechanical, software, and controls disciplines. Allocate and decompose system requirements to appropriate subsystems and engineering disciplines. Lead technical trade studies, design assessments, performance analyses, and other systems engineering activities used to guide design decisions. Support concept development and architecture definition for new end effectors, features, and product capabilities. Requirements, Integration, and Verification Establish and maintain requirements traceability throughout the product development lifec

Help shape the technology that enables a global organisation to do its best work. As Senior Manager, Platform Engineering, you’ll lead the team responsible for Diligent’s Atlassian and Microsoft platforms while setting the architectural direction for the wider internal IT estate. You’ll combine people leadership, enterprise platform strategy and hands-on technical judgement to create secure, reliable and scalable experiences for employees worldwide. From modernising service management and automating joiner, mover and leaver processes to enabling AI safely through Microsoft Copilot and Atlassian Rovo, your work will reduce friction, strengthen governance and deliver measurable business impact. Working across IT, Security, HR, Finance, Legal, Compliance and business teams, you’ll turn complex requirements into well-governed platforms that are easy to use, resilient and ready for the future. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead, coach and grow a global team of platform engineers and systems administrators, building a high-performing and inclusive culture. Own the strategy, architecture, governance and roadmap for Atlassian Cloud, including Jira, Jira Service Management, Confluence, Atlassian Guard and Rovo. Set the direction for Diligent’s Microsoft 365 E5 estate, including Teams, SharePoint, Exchange Online, Intune, Defender, Purview, Power Platform and Copilot. Design scalable integration and automation patterns across identity, HRIS, ITSM and business systems using APIs, event-driven automation, Okta Workflows, Power Platform and scripting. Partner with IT Support to improve self-service, automate repetitive work and reduce ticket volume, escalation effort and time to resolution. Establish strong standards for security, access governance, AI adoption, reliability, compliance and business continuity across the internal technology estate. These are the essentials you’ll need to get an interview Significant experience in i

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore fosters continuous learning and innovation. Job Summary Reporting into the Systems Engineering organisation, the Distinguished Engineer, End-to-End Security Architect will define and lead the security architecture for Graphcore’s inference service platform. This role is responsible for establishing a comprehensive security strategy spanning platform, infrastructure, networking, service operations, customer assurance, and compliance readiness. Working across multiple engineering and operational functions, the successful candidate will provide technical leadership, drive security requirements, and ensure the platform delivers robust protection, resilience, and trust for customers. The Team You will work closely with teams across security architecture, infrastructure engineering, networking, site reliability engineering, platform software, firmware, data centre operations, compliance, legal, customer engineering, and customer security. The team collaborates across the business to deliver secure, reliable, and scalable AI infrastructure and services while supporting customer assurance, regulatory requirements, and operational excellence. Responsibilities and Duties Own the end-to-end security a

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 New York. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. 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 Python, JavaScript, or c

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 San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. 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 Python, JavaScript,

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 Seattle. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. 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 Python, JavaScript, or co

About the Team The Applied AI Engineering team partners closely with customers to help them move from experimentation to production with OpenAI’s technologies. We act as trusted technical advisors, working across customer strategy, architecture, deployment, and adoption to help organizations realize meaningful impact from frontier AI. The Startups segment serves fast-moving, high-growth companies that are often building new products, workflows, and businesses directly on top of AI. These customers move quickly, operate with high ambiguity, and expect practical, creative, and technically rigorous partnership. About the Role We are looking for an Applied AI Engineering Manager, Startups to lead and scale the Startups Applied AI Engineering motion. This team helps high-growth startups move quickly from experimentation to production, unlock meaningful usage, and build durable technical partnerships with OpenAI. This leader will operate in a high-velocity customer segment where founders, CTOs, and technical teams expect speed, judgment, and hands-on problem-solving. They will balance team leadership, technical depth, customer prioritization, and cross-functional influence across Sales, Product, Engineering, Research, and broader go-to-market teams. In this role, you will define how OpenAI supports startup customers at scale: identifying where deep technical engagement can unlock outsized impact, building repeatable deployment mechanisms, and ensuring the team can serve a broad and dynamic customer base without losing quality or strategic focus. In this role, you will: Craft and continuously refine the strategic vision and operating model for the Startups Applied AI Engineering team, aligning it with OpenAI’s broader company objectives and the evolving needs of high-growth startup customers. Lead, mentor, and grow a team of high-performing technical ICs supporting startup customers across AI-native, developer-led, and product-led companies. Help startups move from early e

About the Team OpenAI’s GTM Partnerships team builds a strategic, global partner ecosystem to accelerate customer success, enable responsible enterprise AI adoption, and drive durable growth in support of OpenAI’s mission. We work cross-functionally across Sales, Solutions, Product, Engineering, Security, Legal, Finance, Marketing, Operations, and Customer Success to translate strategic partnerships into measurable outcomes for customers. Global consulting and advisory partners are essential to helping enterprises move from AI strategy to production deployment. PwC brings global reach, deep industry and functional expertise, technology and transformation capabilities, and longstanding relationships with complex and regulated enterprises. This role will lead OpenAI’s global partnership with PwC and create the strategy, operating model, and field motions needed to turn that relationship into repeatable customer and commercial impact. This role is based in San Francisco, New York City, or Seattle. We use a hybrid work model of three days in the office per week. About the Role We are hiring a Partner Director, PwC to serve as the single accountable owner of OpenAI’s strategic relationship with PwC globally. You will define the partnership thesis and joint business plan, build executive alignment, activate PwC’s industry, advisory, technology, sales, and delivery organizations, and develop repeatable go-to-market motions that accelerate enterprise AI adoption. This is a strategic and hands-on leadership role. You will move fluidly between senior executive engagement, joint account and opportunity strategy, solution and delivery alignment, field enablement, governance, and day-to-day execution. Success requires a strong understanding of how a large, matrixed professional-services organization operates, commercial discipline, technical fluency, and the ability to align teams without relying on formal authority. The ideal candidate has led a high-impact global alliance with

About the Team We’re hiring Software Engineers to join our broader Infrastructure organization, which supports multiple high-impact teams. Depending on your interests and experience, you could work on one of several focus areas—including Core Distributed Systems, Reliability Engineering, Observability, Developer Productivity or Cloud Infrastructure. About the Role All teams are deeply collaborative, work on mission-critical services, and are responsible for building distributed, scalable infrastructure to bring OpenAI’s technology to the world through products like ChatGPT and the OpenAI API. You’ll work closely with stakeholders to understand infrastructure, data and compute needs, setting the technical strategy that supports cutting-edge research and product development. This is a critical role for someone who is passionate about solving complex engineering problems at scale, ensuring their performance, scalability and reliability Team Focus Areas Distributed Systems: Owning and building important, highly scalable, available, performant, and reliable distributed systems (and their building blocks) to power the entire stack at OpenAI Systems Engineering: Work across layers of the stack—debugging system bottlenecks, evolving core infrastructure, and solving novel problems in performance and scalability. Reliability Engineering: Build scalable, fault-tolerant systems and lead efforts around service health, incident response, and resilience. Observability: Design and maintain observability tooling (metrics, logs, tracing) to give teams visibility into production systems at scale. Developer Productivity: Create tools, environments, and workflows that help engineers ship high-quality software faster and more safely. Cloud Infrastructure: Own the cloud-native infrastructure (compute, networking, storage) that underpins all services and research workloads. Databases: Building high performance, distributed database systems that power all of OpenAI's product stack. In this