Technical Support Specialist Jobs

- 8+ years of SAP experience with strong expertise in SAP MDG (Master Data Governance), including Solution Architecture, Data Models, Workflows, Integrations, and SAP S/4HANA. - Hands-on experience in SAP MDG technical development using ABAP, OO ABAP, Workflow, BADI, User Exits, CDS, UIBB, Data Model Enhancements, Derivation, Validation, and Debugging. - Proven experience in end-to-end SAP MDG implementations, including requirement gathering, technical design, development, testing, UAT, cutover, Go-Live, and post-production support. - Strong knowledge of Data Quality Management (DQM) with the ability to design, implement, and optimize master data governance solutions. - Excellent stakeholder management and communication skills. Techno-functional profile only (Functional consultants will not be considered). Immediate to short notice joiners preferred.

About Team The IT SaaS Engineering Team is the backbone of MongoDB's go-to-market operations. We build and run the Salesforce platform — with the automation, security, and governance that Sales Operations, Revenue Operations, Security, and Compliance rely on daily to manage customer relationships and drive business growth. Role Overview Join us as a Senior Salesforce Engineer and take ownership of the CPQ and CLM systems that power MongoDB's quote-to-contract lifecycle. You'll design and build scalable pricing, quoting, and contract automation solutions end-to-end — from first design conversation to production support — working alongside senior engineers and stakeholders across Sales, Deal Desk, and Legal. This is a role for an engineer who enjoys solving hard technical problems, cares deeply about accuracy and compliance in revenue-critical systems, and wants to bring modern, AI-augmented development practices into how enterprise Q2C solutions get built. What you’ll do Design, build, and maintain scalable CPQ configuration (product rules, price rules, bundles, discounting logic) and CLM workflows (clause libraries, approval chains, e-signature integration) Partner with Sales, Deal Desk, Legal, and Finance stakeholders to translate quote-to-cash requirements into secure, maintainable technical solutions Own delivery across the full solution lifecycle — design, development, testing, deployment, documentation, and production support Collaborate with globally distributed engineering teams to deliver reliable, well-governed CPQ/CLM solutions in an Agile environment Drive strong engineering practices across code quality, documentation, release management, and platform governance Identify opportunities to simplify pricing logic, reduce legacy quote template debt, and strengthen the overall Q2C operating model Troubleshoot complex pricing, approval, or contract-generation issues and deliver sustainable, long-term fixes Stay current on CPQ/CLM platform capabilities and appl

About the team OpenAI’s mission is to build safe artificial general intelligence (AGI) which benefits all of humanity. This long-term undertaking brings the world’s best scientists, engineers, and business professionals into one lab together to accomplish this. In pursuit of this mission, our Go To Market (GTM) team is responsible for helping customers learn how to leverage and deploy our highly capable AI products across their business. The team is made of Sales, Solutions, Support, Marketing, and Partnership professionals that work together to create valuable solutions that will help bring AI to as many users as possible. About the role Our Sales team has a unique mission to help customers understand the deep impact that highly capable AI models can bring to their business and users. This role is a mixture of technical understanding, vision, partnership, and value-driven strategy. You’ll be a key driver of opportunities through the entire sales cycle, from pipeline generation to closure. You’ll work with researchers, engineers, and solution strategists to help customers evolve their industry with AI. This role is based in Seoul, South Korea. 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'll: Manage a ~dozen key accounts, developing and executing strategies for a comprehensive account plan Lead our enterprise prospects’ journeys from consideration to successful deployment Partner with solutions and research engineering to build and execute complex customer programs and projects Own a consumption revenue target Manage consumption revenue forecasts Analyze key account metrics to create reports and provide insights to internal and external stakeholders Closely monitor the industry landscape (people, competitors, partners, etc.) to contribute to product roadmap and other corporate strategies Collaborate with solutions, marketing, communications, business operations, people operations, fina

As a Senior Backend Engineer on Coder's Enterprise Experience team, you'll build the systems that help large organizations run Coder in production with confidence. You'll improve how Coder scales, how it's upgraded, and how reliably it performs in regulated, air-gapped, and enterprise environments. You'll work on a genuinely cross-functional team of backend, platform, and QA engineers who own the end-to-end experience for Coder operators. From designing new features to evolving Coder's architecture, you'll partner across engineering and product to solve complex problems and ship software that operators trust. What you'll do here Design and build new features end to end, from technical design through production rollout. Design and implement backend architecture changes that support Coder's long-term scalability goals. Investigate and resolve scalability bottlenecks under production-like load, from database access patterns to concurrency handling in coderd. Improve database migration safety and upgrade reliability through schema compatibility, background migrations, and safe rollback strategies. Own the backend side of issues surfaced by Coder operators and administrators. Document the design, implementation, and operational tradeoffs of the systems you build. Participate in code reviews, RFC-style design discussions, and on-call rotations for the services you own. What we're looking for 5+ years of professional software engineering experience, including significant production experience with Go. Deep understanding of Go's concurrency model, including goroutines, channels, the sync package, and debugging race conditions under real-world load. Experience designing and operating relational databases in production, including schema design, migrations, and transactions. Strong verbal and written communication skills. Exceptional debugging and troubleshooting skills, with the persistence to drive complex problems to resolution. A self-motivated, analytical engineer who enj

The Development Infrastructure team builds the tooling and systems our Asana engineers use every day to bring their ideas to production quickly and reliably. We build and operate the software that drives Asana’s roadmap. Each day, we combine industry best practices and innovation to support this product-focused company. We’re looking for an experienced Software Engineer with a passion for developer infrastructure. You will work with a world-class team of engineers on deploying and operating existing developer tooling, and building new tools to support our global, growing development team. You will have a unique opportunity to design and develop the systems and applications that drive the Asana development experience, lead complex technical projects, and work on cross-functional initiatives to help define the future of software engineering at Asana. This role is based in our Reykjavík 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 Innovate the architecture of our development sandboxes to accelerate development iteration. Modernize our build system, tighten iteration loops, and polish frequent cycles in the developer experience. Lead complex developer infrastructure projects from technical design through implementation, rollout, and operation. Partner with engineering teams to identify opportunities to enable teams to develop faster at Asana and help the company achieve our goals faster. Analyze complex developer infrastructure systems to uncover issues, root causes, and areas for improvement. Keep Asana up to date on open-source trends and identify new opportunities for improved development infrastructure. Champion co

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. As the Advocacy & Content Strategist, you will serve as the program architect and content engine that mobilizes Okta and Auth0 experts, customers, partners, developers, and security practitioners into vocal brand advocates. Operating as an individual contributor within Customer Acceleration, you are responsible for building structured customer programs and co-creating content with power users that amplify our post-sales experiences across learning, badging, certification, support and customer success, while driving product adoption and customer success. Job Duties and Re sponsibilities Scale & Activate Customer Champions: Operationalize and grow structured advocacy frameworks, like the Champions Program, complete with badging milestones, gamified recognition, and tiered perks that incentivize long-term participation. Build repeatable processes to systematically surface champion expertise and route these user voices into high-impact content formats, GTM initiatives, and key business moments. Co-Create Content with Technical Users: Partner directly with internal, partner and customer champions, developers, and practitioners to co-produce user-generated content (UGC), technical deep-dives, AMAs, expert Q&As, and customer-led blogs. Develop Customer Success Storytelling: Identify, interview, and write compelling customer success stories, case studies, and advocate spotlights that prove the business value of our post-sales experiences (E

About the Team The Applied AI Engineering team is responsible for helping developers and enterprises safely and effectively deploy OpenAI technologies in production. We act as trusted technical advisors and thought partners for customers, working side by side with their teams to identify high-value use cases, design practical architectures, and move from prototype to durable deployment. Cybersecurity is one of the most urgent domains where AI can help. Security teams are under pressure to reason across code, logs, infrastructure, tickets, alerts, and vulnerability data faster than ever. As frontier models become more capable, organizations need deep technical guidance on how to evaluate, validate, and safely deploy AI systems in security-critical workflows. About the Role We are looking for a Cybersecurity Applied AI Engineer to partner with customers and help them apply OpenAI models, APIs, Codex, and agentic workflows to real cybersecurity use cases. You will work with CISOs, security executives, application security leaders, SOC teams, security engineering teams, and hands-on practitioners to identify where AI can create measurable security outcomes. This is a customer-facing technical role for someone who can move fluidly between executive strategy, practitioner-level cyber depth, and hands-on solution design. You will help customers evaluate and deploy workflows such as secure code review, vulnerability triage, threat modeling, remediation, SOC and incident response workflows, detection engineering, cloud security, GRC automation, and security validation. You will collaborate closely with Sales, Solutions Engineering, Product, Engineering, Research, and Security to turn customer needs into safe deployment patterns, reusable field assets, and product feedback. This role is based in our Dublin Office. We offer relocation support to new employees. In this role, you will: Deeply embed with strategic customers as the technical lead for AI-enabled cybersecurity workf

About the Team The Applied AI Engineering team is responsible for helping developers and enterprises safely and effectively deploy OpenAI technologies in production. We act as trusted technical advisors and thought partners for customers, working side by side with their teams to identify high-value use cases, design practical architectures, and move from prototype to durable deployment. Cybersecurity is one of the most urgent domains where AI can help. Security teams are under pressure to reason across code, logs, infrastructure, tickets, alerts, and vulnerability data faster than ever. As frontier models become more capable, organizations need deep technical guidance on how to evaluate, validate, and safely deploy AI systems in security-critical workflows. About the Role We are looking for a Cybersecurity Applied AI Engineer to partner with customers and help them apply OpenAI models, APIs, Codex, and agentic workflows to real cybersecurity use cases. You will work with CISOs, security executives, application security leaders, SOC teams, security engineering teams, and hands-on practitioners to identify where AI can create measurable security outcomes. This is a customer-facing technical role for someone who can move fluidly between executive strategy, practitioner-level cyber depth, and hands-on solution design. You will help customers evaluate and deploy workflows such as secure code review, vulnerability triage, threat modeling, remediation, SOC and incident response workflows, detection engineering, cloud security, GRC automation, and security validation. You will collaborate closely with Sales, Solutions Engineering, Product, Engineering, Research, and Security to turn customer needs into safe deployment patterns, reusable field assets, and product feedback. This role is based in our Tokyo office. We offer relocation support to new employees. In this role, you will: Deeply embed with strategic customers as the technical lead for AI-enabled cybersecurity workfl

About the Team The Applied AI Engineering team is responsible for helping developers and enterprises safely and effectively deploy OpenAI technologies in production. We act as trusted technical advisors and thought partners for customers, working side by side with their teams to identify high-value use cases, design practical architectures, and move from prototype to durable deployment. Cybersecurity is one of the most urgent domains where AI can help. Security teams are under pressure to reason across code, logs, infrastructure, tickets, alerts, and vulnerability data faster than ever. As frontier models become more capable, organizations need deep technical guidance on how to evaluate, validate, and safely deploy AI systems in security-critical workflows. About the Role We are looking for an Applied AI Engineer, Cyber to partner with customers and help them apply OpenAI models, APIs, Codex, and agentic workflows to real cybersecurity use cases. You will work with CISOs, security executives, application security leaders, SOC teams, security engineering teams, and hands-on practitioners to identify where AI can create measurable security outcomes. This is a customer-facing technical role for someone who can move fluidly between executive strategy, practitioner-level cyber depth, and hands-on solution design. You will help customers evaluate and deploy workflows such as secure code review, vulnerability triage, threat modeling, remediation, SOC and incident response workflows, detection engineering, cloud security, GRC automation, and security validation. You will collaborate closely with Sales, Solutions Engineering, Product, Engineering, Research, and Security to turn customer needs into safe deployment patterns, reusable field assets, and product feedback. This role is based in our Singapore office. We offer relocation support to new employees. In this role, you will: Deeply embed with strategic customers as the technical lead for AI-enabled cybersecurity workflow

The Electrical Engineering Lead manages electrical engineering activities to ensure cohesive project execution and alignment with project requirements. They provide progress updates, handle change requests, and conduct risk assessments, ensuring compliance with industry standards. The role involves leading technical meetings, reviewing and updating technical specifications, and overseeing procurement activities. The Electrical Engineering Lead monitors project documentation, budgets, and progress, presenting status reports and identifying cost-saving measures. They provide on-site support during construction, oversee electrical systems' installation and testing, and ensure adherence to safety standards and regulations. The Electrical Engineering Lead facilitates communication among stakeholders and manages the daily performance and development of the electrical team. Source: Adani Group | Job ID: 40198

About the Team Our mission at OpenAI is to discover and enact the path to safe, beneficial AGI. To do this, we believe that many technical breakthroughs are needed in generative modeling, reinforcement learning, large-scale optimization, active learning, and other areas. The team builds the performance-critical systems that allow OpenAI's models to run efficiently across a diverse set of AI accelerators. We work across the inference stack, from low-level kernels and compilers through model execution, to unlock the full capabilities of the underlying hardware. About the Role As a Software Engineer, Trainium, you will help bring OpenAI's inference workloads to AWS Trainium and build the software stack required to run cutting-edge frontier models efficiently on the platform. This is a deeply technical, cross-stack role spanning kernels, compilers, and model execution. You will work on the systems needed to support OpenAI's inference stack on Trainium, including developing and optimizing high-performance kernels, improving compiler support, and enabling efficient execution of the model forward pass. You'll work closely with engineers across inference, compilers, kernels, and ML systems to identify performance bottlenecks and build the software needed to take full advantage of Trainium. The work may range from low-level hardware-specific optimization to compiler and runtime improvements to integrating new model architectures into the inference stack. If you enjoy working at the intersection of ML systems, compilers, kernels, and accelerator hardware, this role is for you. We're looking for engineers who are self-directed, comfortable operating across abstraction layers, and excited to solve challenging performance problems for frontier-scale AI systems. In This Role, You Will Build and optimize OpenAI's inference stack for AWS Trainium. Develop high-performance kernels for critical model operations and workloads. Extend and improve compiler support to efficiently target

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're hiring a Compute Strategy and Operations lead to own how Modal plans for and acquires GPU and CPU capacity. You'll size our infrastructure needs ahead of demand, source supply across hyperscalers, neoclouds, and datacenter operators, and negotiate and close the contracts to secure it. The compute you secure directly determines what Modal can sell and build. In this role, you will: Own end-to-end procurement of GPU and CPU capacity across hyperscalers, neoclouds, and datacenter operators Build and maintain a strong pipeline of supplier relationships Evaluate supply options on price, availability, hardware specs, networking capabilities, and SLA terms Negotiate and close contracts: reserved capacity agreements, spot arrangements, MSAs, DPAs, and order forms Work closely with our engineering teams to translate technical requirements into procurement specs Track

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role We're looking for an Engineering Manager to lead a team of highly experienced engineers building the infrastructure that powers Modal's serverless GPU platform. This is a hands-on leadership role — expect to split your time between technical contribution and people management depending on what the team needs. You'll set direction, remove blockers, and build a strong engineering culture as your team tackles hard problems in distributed computing, large-scale data handling, and performance optimization. Who You Are You're an experienced engineering leader who stays close to the work and builds alongside your team when it counts. You earn trust through technical depth, not title. You communicate clearly, help strong engineers move fast without cutting corners, and stay calm and pragmatic under pressure. You care as much about how your team gets to an answer as the answ

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for Forward Deployed Engineers on our engineering team who want to work at the intersection of deep infrastructure work and direct customer impact. As an FDE, you'll partner with leading AI companies and foundation labs on cloud architecture, networking, storage, containerization, sandboxing, and more — helping them design and ship production infrastructure on Modal's platform. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the infrastructure stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and deploy massive-scale production workloads on Modal Lead technical discovery and architect