It Business Solution Manager Jobs

At Dscout, we’re building the most flexible and powerful UX research platform on the market—trusted by the world’s top brands in finance (JP Morgan Chase, Intuit, Charles Schwab, PayPal), healthcare (Aya, Headspace), consumer goods (Keen, Verizon, Target, Northface), and tech (Google, Amazon, Facebook, Meta, Spotify, AirBnB). Our tools help teams deeply understand the humans behind their products, so they can build better ones. We are expanding our smart and driven team and would love for you to join us. We're looking for an AI Product Manager who brings the full standard PM toolkit — user research, market and competitive analysis, roadmap and strategy, cross-functional delivery, and strong collaboration instincts - and applies it to products where the model underneath doesn't behave the same way twice. You have a real, hands-on feel for what different LLMs are actually good and bad at, and you use that to prototype ideas yourself, sometimes shipping small, production-quality AI features directly. You default to ownership: of the roadmap, of outcomes, of the quality bar that decides whether something's actually ready to ship, and of what an agent should be trusted to do on its own versus when a human needs to stay in the loop. That's because building AI-native products means quality is a distribution, not a pass/fail — a feature can work correctly most of the time and still need a real answer for the failure tail, since the underlying system is non-deterministic, not just complex. What you'll do Lead the roadmap and strategy for your product area, from problem discovery through delivery and post-launch iteration Lead the evaluation bar for the model-powered surfaces you're responsible for: define eval sets, identify failure modes, and know the rollback plan before a change ships Prototype product ideas directly using your own understanding of model strengths and weaknesses, and ship small, production-quality AI features yourself when that's the fastest path to

We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us! Your Opportunity At New Relic, we provide our customers with real-time insights, so they can innovate faster. Our software provides deep observability across the stack, enabling software teams to solve their customer’s problems, accelerate digital transformation, and make DevOps work. You will be at the heart of the teams supporting New Relic’s infrastructure and will work on a team that provides global service mesh and load balancing solutions. We provide these services on-premises, as well as using our multi-cloud infrastructure. We support each other to do our best work through positive communication and continuous improvement. What You’ll Do As a key member of our Infrastructure team, you will design and operate a scalable, resilient ingress data plane that directly impacts the value we provide to our customers. By ensuring the stability and performance of our global service mesh and load balancing solutions, you drive the foundational reliability that the entire New Relic organization depends on to deliver real-time insights. You will leverage advanced automation and infrastructure-as-code to accelerate development speed, allowing our engineering teams to ship safe, incremental changes across a massive fleet with confidence. Your work in evolving our DNS and CDN infrastructure is not just about maintenance; it is about creating a seamless, high-performance environment that enables innovation at scale. Through deep collaboration with Product, Design, and partner platform t

About the Team The Consumer Devices team at OpenAI builds end-to-end hardware and software systems that bring AI into the physical world. We work at the intersection of custom silicon, embedded systems, operating systems, cloud services, mechanical engineering, electrical engineering, and product design to deliver reliable, production-ready devices at scale. Within Consumer Devices, Hardware Engineering eXperience, or HEX, is a new bootstrapped team building the environments, applications, compute, product-data systems, and workflows that let hardware engineers do their work without needing to troubleshoot the machinery underneath. HEX owns virtual engineering environments, HPC/GPU compute, storage, networking, licensing, MCAD/ECAD/CAE applications, PLM, product data, automation, validation, and support as one connected system. About the Role As a Staff PLM & Engineering Applications Engineer, you will be one of the first technical builders of HEX and the primary counterpart to the HEX lead. You will own the engineering-application and product-data side of the hardware engineering experience, with an initial focus on NX, Teamcenter, licensing, parts import, integrations, packaging, validation, and user workflows. This is not a traditional Teamcenter administration role and not a Corporate IT application-support role. You will take complex, fragile workflows and turn them into reliable engineering systems. This role is highly hands-on and systems-oriented. You will not inherit a mature environment and support queue. You will help build a fresh one, replacing manual setup guides, tribal knowledge, repeated support issues, and team handoffs with tested automation and reliable workflows. In This Role, You Will Own the technical architecture, deployment, configuration, integration, validation, and long-term operation of NX and Teamcenter. Build reliable workflows for parts import, product-data migration, metadata quality, BOMs, revisions, lifecycle states, and releas

Location Details: Remote, India At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.​ This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. Join Our Team... This position is for a Staff Software Engineer within GoDaddy’s engineering organization, concentrating on developing scalable, fault-tolerant systems and promoting technical excellence across various teams and projects. As a Staff Software Engineer, you will serve as a technical leader at the division level. You will impact system design and architecture, as well as how engineering is carried out across teams. This position suits engineers who excel in uncertain environments, like tackling difficult technical problems, and can provide clarity, structure, and delivery for large projects. Our teams focus on greenfield and open-ended projects that require firm technical ownership, architectural vision, and collaboration across functions. You will assist in establishing engineering standards, support teams through mentoring, and create systems that boost reliability, scalability, and developer efficiency organization-wide. This role is important for encouraging innovation throughout the engineering organization. It includes promoting AI-assisted development workflows, modern cloud-native methods, and reusable platform features that speed up development across teams. What you'll get to do... Technical Execution & Delivery Lead delivery of complex engineering initiatives while driving predictable execution and long-term technical quality Architect and implement highly available, fault-tolerant distributed systems using AWS, PostgreSQL/Aurora, and MongoDB Architect and lead greenfield projects from concept to production, bringin

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. About The Team Global Innovation Center SE team (Presales): Over the last 3 years, Okta in Bangalore has fueled our growth around the world. The Global Innovation Center Presales team has been a crucial part of this growth. We are expanding this team made up of exceptional high-performing individuals. In this team, you will focus on being a customer-facing solution engineer crafting identity and security solutions for commercial segments in the US, ranging from digitally native start-ups to scaling SMBs. As a Solutions Engineer you will: Support our customers along their sales journey by showing them the value of the Okta technology through live demonstrations and sales presentations. Sell directly to IT managers, developers, product managers, and occasionally more senior executives across various industries.. Have a focus on our Okta Workforce Identity solutions and be able to model how this solution will support their current architecture requirements and use cases Execute well-defined, outcome-focused POCs Maintain a broad and deep technical understanding of the Okta product line and the underlying technologies and protocols Occasionally participate in local and regional events evangelising Okta as a presenter and an attendee. We are looking for: Ability to work in the EST Time Zone A minimum of 5 years of working experience in IAM or a related SaaS field as a pre-sales engineer. Expertise or hands-on experience in IAM, single sign-on, multi-factor authe

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Senior Engineering Manager, Continuous Deployment at GitLab, you'll build and manage a globally distributed team focused on Continuous Deployment capabilities within GitLab's artificial intelligence-powered DevSecOps platform. You'll hire engineers, shape how the team works, and guide delivery of a reliable product experience for customers. Your team will build a Continuous Deployment engine that goes beyond script execution. It will reconcile live state, coordinate durable workflows, and support artificial intelligence-native governance. You'll align technical direction with customer needs and busin

Datadog AI Research — Scholars Program with Carnegie Mellon University Datadog AI Research (DAIR) is partnering with Carnegie Mellon University to support a small number of PhD students working on open research problems grounded by ongoing efforts at Datadog/DAIR. You will frame a problem, run your own experiments, and write up what you find, with compute and data at a scale most academic labs cannot provide. You will collaborate with colleagues working on the same questions. The Lab And The Research: DAIR is an industrial research lab motivated by practical challenges in observability and software operation: detecting and diagnosing failures, understanding complex production environments, and helping engineers operate software more effectively. The lab focuses on creating specialized foundation models, post-training and evaluating AI agents, and building frontier-scale machine learning systems. By combining fundamental research with Datadog's large-scale, real-world data and infrastructure, the lab develops new AI capabilities and translates them into practical systems with meaningful impact. Internship projects are shaped with your DAIR mentor and your CMU faculty advisor. You do not need prior experience with observability, monitoring, or infrastructure. What You'll Do: Own a research project end to end: framing the question, running the experiments, writing it up Work directly with a DAIR mentor engaged in the same problem, and stay connected to your advisor and lab Publish, and use the work toward your dissertation See research reach production, when it works Who You Are: Currently enrolled in a PhD program at Carnegie Mellon in machine learning, computer science, statistics, or a related field Depth in at least one area relevant to the research above Comfort running real experiments — training models, working with GPUs, reading and reimplementing recent papers Evidence you can do research: conference or workshop papers, preprin

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role Sentry's issue platform processes billions of events every day to help millions of developers find and fix bugs. The hard part is deciding which events point to a problem, which belong together, and what a developer needs to know to investigate. As a Senior Software Engineer on the Issue Detection team, you'll design, build, and operate the systems that make those decisions. You'll work on real-time processing pipelines, monitors, and analysis systems that detect problems and turn them into issues. The work combines distributed systems with product engineering. Choices about detection accuracy and processing latency affect which problems developers see and how soon they can act. You'll help shape how developers monitor their applications and how Sentry groups related events into issues. You'll also build the context developers and AI agents need to investigate what went wrong. Keeping these systems reliable and fast as Sentry grows is part of the job, alongside making the issues they produce more useful. In this role you will Build and scale features on a product surface handling billions of events daily, where both query latency and correctness are immediately visible to users. Own the design and delivery of substantial projects end to end, scoping alongside product and design, making the technical calls within your scope, shipping, and instrumenting what you ship so the team can measure it. You will contribute to meaningful technical product decisions : grouping quality, search performance, migrations and backfills against enormous datasets, and making the surface work well for both humans and agents. Champi

About the Team pAGI Infra team builds and operates the systems that make large-scale model training and evaluation reliable, efficient, and easy to run. Our work spans distributed training infrastructure, inference and grading platforms, compute scheduling, and research tooling. We partner closely with researchers and engineering teams to turn new research needs into dependable infrastructure, improve GPU efficiency, and shorten the path from an experiment to a validated model. About the Role We’re looking for an AI Systems Engineer to help scale the infrastructure behind our training and evaluation workflows. You’ll own projects from identifying bottlenecks and designing solutions through deployment and operation. The work combines distributed systems engineering, performance optimization, and close collaboration with researchers. You might build a shared grading service, improve resource allocation across workloads, or bring a new training stack into production — directly improving how quickly and reliably research moves forward. In this role, you will: Build and operate infrastructure for large-scale training and evaluation, improving reliability, throughput, and resource efficiency. Develop shared inference and grading platforms with automated capacity management, health monitoring, and visibility into performance. Improve compute scheduling and resource allocation to reduce idle GPU time and help workloads recover quickly from failures. Diagnose bottlenecks across training, inference, and orchestration, and work across teams to improve end-to-end performance. Build self-service tools, automated validation, and observability that help researchers launch experiments, diagnose issues, and compare results with less manual intervention. You might thrive in this role if you: Are excited about the potential of personal AGI and want to build the infrastructure that enables it. Have strong software engineering fundamentals and experience building or operating large-scal

We are a team of engineers that translate our real-world experience to help our user communities solve problems. With a focus on service management, helping teams respond to incidents, run on-call, and automate their operations, you will work with practitioners and leaders across the industry and broaden your impact to the SRE, Engineer, DevOps, and Operations community at large. This is a unique opportunity to use both your engineering and creative storytelling skills to shape the landscape in cloud observability, incident response and service management. What You'll Do: Act as a subject matter expert for service management (incident response, on-call, IDP, Work Management, Workflow Automation, Agent Builder, and operational automation) for Datadog's advocacy and engineering teams Create content in one or more mediums to build Datadog's reputation as a leader in DevOps, Monitoring, Observability and Security e.g. building demos, public speaking, blogging, documentation, webinars, open source, research reports and more Partner with product engineering teams to build compelling demos, and coach internal engineering teams on effective communication and presentation Interface with open source communities to drive key messaging in the market and develop new integrations for Datadog Contribute to the product through feedback (bugs or product enhancements suggestions), documentation, or code Who You Are: Approximately 5+ years of experience as a Platform Engineer, Site Reliability Engineer, DevOps Engineer or Software Developer with hands-on experience as an on-call/incident responder and running production systems in complex IT environments You have a strong understanding of core service-management practices (incident response, on-call, post incident reviews, and SLOs), using tools like Datadog, PagerDuty, Opsgenie, http://incident.io , Rootly, Jira Cloud Platform, Cortex, or similar and know how to navigate operational challenges of different

About the Team OpenAI is building the next generation of advertising for an AI-powered world. As AI changes how people discover information, explore possibilities, and make decisions, we believe this presents a huge opportunity for small and medium-sized businesses to connect with customers in new ways. The SMB Ads Marketing team is building this opportunity from the ground up. We define how businesses discover OpenAI’s advertising platform, become successful advertisers, and grow their investment over time. Working closely with Product, Ads Engineering, Data Science, and Sales, we combine customer insight, rigorous experimentation, and fast execution to turn early opportunities into scalable growth. About the Role We are looking for an Audience & Content Growth Lead to build the global content and education programs that inspire, inform and engage SMB advertisers. This is a zero-to-one opportunity to shape how small businesses discover and understand advertising with OpenAI. You will turn customer needs, product capabilities and advertiser success stories into compelling content—from webinars and educational video series to case studies, industry-specific playbooks and creator-led programs. The role combines two areas of ownership: developing content specifically for SMB audiences and building effective ways to distribute it. You will lead programs directly while partnering with teams that own web, social, lifecycle marketing, growth and regional channels to reach the right audiences at scale. Success means building an engaged SMB audience and helping businesses move from awareness to understanding, confidence and action. In This Role, You Will Set the global SMB content strategy and editorial roadmap, grounded in customer needs, industry priorities, and advertiser maturity. Create compelling customer stories, case studies, vertical playbooks, guides, videos, and thought leadership that make advertising accessible and actionable. Launch repeatable education pro

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 The Cooperative AI team is scaling OpenAI with OpenAI. We are building a model-powered scaled automated workforce and knowledge system that evolves and learns alongside a human workforce. By leveraging OpenAI’s state-of-the-art models and technologies, some already in production, others still in the lab, we develop systems that reason and work autonomously for a wide variety of operational work. We leverage real workloads for critical systems across finance, sales, customer support, integrity, product insights, internal operations, and more in order to drive insights into product and industry. We partner closely with internal teams and external customers globally, operating in a hyper-fast feedback loop where many of our users are just a few steps away. This proximity allows us to iterate quickly, validate impact in real time, and accelerate industry impacting learnings and systems builds. We are a highly multidisciplinary, self-contained team focused on transforming the workplace via smart systems, knowledge, scalable and reliable primitives that apply world-class AI capabilities across domains. Our mission is to learn fast and transform how humans collaborate with AI at scale. About the Role We are looking for a hands-on Engineering Manager to lead a small, fast-moving team building AI-powered automation systems that redefine how work gets done across OpenAI. This role sits at the intersection of applied AI, research, and product engineering. You’ll lead a team that builds systems that know how to learn from humans, and carry real workloads across, sales, support, finance, IT, and more, while staying deeply involved in the technical work. You will operate in a highly iterative environment, deploying systems directly to internal users, gathering rapid feedback, and evolving solutions in real time. This is a high-ownership role for someone excited about building 0→1 systems, working closely with customers, and shaping how AI transforms operational wor

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