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Location: Dhahran, Saudi Arabia; Riyadh, Saudi Arabia; Lusail, Qatar; Dubai, United Arab Emirates We are seeking an experienced Lead Digital Solutions Analyst to support advanced AI technology initiatives and contribute to the development of next-generation AI solutions. The successful candidate will work on AI modules, scalable data pipelines, backend infrastructure, and real-time data processing systems, supporting the development of Large Language Models (LLMs), Large Time-Series Models, and Large Vision Models. Key Responsibilities Develop and implement AI modules, pipelines, solutions, and services for advanced AI technologies. Design and develop scalable backend infrastructure to support real-time data ingestion, AI model inference, and user access. Build real-time data processing components using event-driven architecture. Apply microservices and agentic AI architectures to support scalability and flexible system development. Develop data pipelines for data preprocessing, normalization, labelling, transformation, feature engineering, and storage. Support research and development initiatives for sovereign AI technologies, including Large Language Models, Large Time-Series Models, and Large Vision Models. Collaborate with cross-functional teams to develop, integrate, and optimize AI-driven solutions. Requirements Bachelor's degree in Graphic Design or an equivalent qualification, as specified for the position. Minimum 10 years of relevant professional experience in graphic design, data science, AI technologies, or a related field. Experience in AI solution development, data pipelines, or AI technology implementation. Knowledge of backend infrastructure, real-time data processing, and event-driven architectures. Familiarity with microservices, agentic AI architectures, and scalable AI applications. Understanding of data preprocessing, transformation, feature engineering, and data storage. Exposure to Large Language Models, time-series models, or computer vision technologies is an advantage. Strong analytical, problem-solving, and collaboration skills.

Location: Dhahran, Saudi Arabia We are seeking an experienced Enterprise Architect to define, develop, and govern the enterprise architecture strategy, frameworks, standards, and roadmaps, ensuring alignment between business objectives, technology capabilities, and organizational priorities. The role will drive enterprise-wide architecture across computing and cloud platforms, communications and network infrastructure, data and artificial intelligence, cybersecurity, and business architecture. The successful candidate will provide architectural leadership, establish target-state architectures and reference designs, and ensure that enterprise solutions are scalable, secure, resilient, compliant, and aligned with the organization’s strategic goals. Key Responsibilities Define and maintain enterprise architecture frameworks, principles, standards, reference architectures, and technology roadmaps aligned with business strategy. Lead the design and evolution of enterprise technology architectures covering on-premises infrastructure, private and public cloud, high-performance computing (HPC), AI infrastructure, and enterprise platforms. Develop communications architecture across data networks, transmission networks, and satellite communications. Establish enterprise data architecture and governance frameworks, enabling trusted analytics, artificial intelligence, machine learning, and MLOps capabilities. Define and govern cybersecurity architecture to ensure the protection of enterprise systems, infrastructure, applications, and data in accordance with applicable security controls and standards. Translate business strategy, operating models, and business processes into architecture artifacts that support enterprise transformation and technology alignment. Provide architectural assurance and governance for major programs, projects, and technology solutions, ensuring compliance with approved standards and design principles. Identify technology opportunities, assess emerging technologies, and recommend solutions that enhance operational efficiency, scalability, resilience, security, and business value. Collaborate with business stakeholders, technology teams, cybersecurity specialists, and program leaders to ensure cohesive, integrated enterprise solutions. Maintain architecture documentation, identify capability gaps, and develop transition roadmaps to support the organization’s target-state architecture. Qualifications and Experience Bachelor’s degree in Computer Engineering, Computer Science, Business Management, or a related discipline; a Master’s degree is preferred. 10 to 15+ years of relevant professional experience in enterprise architecture, technology architecture, infrastructure, communications, data and AI, cybersecurity, or business architecture. Demonstrated experience developing enterprise architecture strategies, target-state designs, standards, governance frameworks, and implementation roadmaps. Strong understanding of enterprise technology environments, business capabilities, architecture governance, and technology-to-business alignment. Proven ability to lead cross-functional architecture initiatives and engage effectively with senior stakeholders. Excellent analytical, strategic planning, communication, and stakeholder management skills.

Location: Almaty, Kazakhstan Workplace: OnSite Almaty, Kazakhstan · Trust & Safety Engineering Why this role exists Our ML and analytics teams already work on fraud detection and risk analysis. This role owns the backend that turns their signals into reliable protections across accounts, credits, payments, and generation. You'll integrate risk checks into product flows, build enforcement services and operator tools, and make sure controls work correctly in production. We're looking for an engineer we can trust to take a backend problem from an unclear starting point to a working solution. What you'll actually do - Risk integrations: connect existing ML scores and risk signals to account creation, credit usage, payments, and generation flows, with clear timeouts and fallback behavior. - Enforcement services: implement configurable rules, rate limits, account restrictions, and credit or payment controls with consistent behavior across services. - Operator tooling: build APIs and workflows for reviewing cases, inspecting decision history, and safely applying or reversing restrictions. - Production reliability: handle retries, duplicate events, concurrent requests, and safe rollouts; add monitoring and audit trails so failures can be traced and fixed. - Work in other teams’ codebases to add signals or interventions without hurting their stability or architecture. - Ownership: clarify the control with ML, analytics, and operations → scope the smallest useful implementation → ship → verify production behavior and review impact with the team. Our release cycle is days, not quarters, so your first shipped protection happens fast. Must-haves 1. You've taken a difficult problem from an unclear starting point to a working system used in production, and can explain your own decisions, contribution, and results. 2. You can build reliable backend services: APIs, data models, queues, transactions, idempotency, and concurrency. You can integrate external services and debug failures across the request and event lifecycle. 3. You choose the next steps, remove blockers, and ask for help when needed. You cut scope to test an idea, adapt from evidence, and keep working through difficult problems. 4. You work with ML, analytics, and operations to turn risk requirements into clear backend behavior. You use operator feedback and customer cases to improve controls and learn unfamiliar systems quickly. 5. You take feedback, change your mind when the evidence changes, and do the work the team needs. You share knowledge and responsibility so others can operate and extend what you build. Who this is not for - You prefer problems where requirements stay stable after launch. - You prefer work centered on training models or producing analysis rather than building and operating backend services. Nice to have - Fraud prevention, payments risk, or platform abuse experience. - Integrating risk-scoring services or building rules engines and rate limiters. - Case management, appeals, and risk operations tooling. - Familiarity with Stripe. - Experience building real-time scoring, graph-based account linkage systems. - Python/Go experience. Interview process 1. Recruiter screen: role expectations, logistics, and fit. 2. Technical interview: a difficult system you shipped, what you personally decided and built, and how your work made the team more capable without leaving it dependent on you. 3. Additional technical interview, if needed: a deeper discussion of technical skills and open questions. 4. Product fit interview: take an existing risk signal and an operator need, scope a backend protection, and work through failure cases and effects on legitimate customers. 5. Offer. What we offer Competitive base in USD, equity, relocation support, and ownership of protections that preserve both company revenue and customer trust.

Location: Almaty, Kazakhstan Workplace: OnSite Almaty, Kazakhstan · Trust & Safety Engineering Why this role exists An agent needs more than a model response to complete useful work. It needs tools, durable execution, permissions, context, and a way to recover when something fails. You'll build the backend that lets Higgsfield agents carry creative tasks from a user's request to a finished result. We're looking for an engineer we can trust with a problem: work out what is worth building, build it, and carry it through to users. What you'll actually do - Agent execution: build orchestration for multi-step tasks, tool calls, streaming updates, and cancellation. - Durable workflows: implement checkpoints, resumability, retries, and recovery without duplicating actions. - Tools and integrations: connect agents to generation, editing, and external services through clear, validated interfaces. - Execution boundaries: enforce user permissions, tenant isolation, resource limits, and approval requirements for consequential actions. - Evaluation and observability: trace failures, build regression cases, and improve task completion, latency, and cost. - Ownership: understand a real user task → define success and build evaluation cases → scope the simplest useful workflow → ship → measure completion, reliability, and dollar impact → improve from failed runs. Our release cycle is days, not quarters, so your first shipped agent capability happens fast. Must-haves 1. You've taken a difficult problem from an unclear starting point to a working system used in production, and can explain your own decisions, contribution, and results. 2. You can build reliable agent execution: state machines, concurrency, queues, recovery, model APIs, secure tool calls, and repeatable evaluations. You learn unfamiliar tools quickly and understand what you ship. 3. You choose the next steps, remove blockers, and ask for help when needed. You cut scope to test an idea, adapt from evidence, and keep working through difficult problems. 4. You investigate real user tasks and failed agent runs, use feedback to choose what to automate, and stop workflows that do not help users finish their work. 5. You take feedback, change your mind when the evidence changes, and do the work the team needs. You share knowledge and responsibility so others can operate and extend what you build. Who this is not for - You prefer deterministic application behavior without investigating model uncertainty. - You prefer prototyping without owning evaluation, recovery, and production reliability. Nice to have - Production agents, workflow engines, or developer tools. - High-throughput systems with heavy traffic, large data volumes, or many long-running jobs. - Agent context management, memory, subagents, or parallel tool calls. - Sandboxed execution and scoped authorization. - Multimodal workflows involving images, video, or audio. Interview process 1. Recruiter screen: role expectations, logistics, and fit. 2. Technical interview: a difficult system you shipped, what you personally decided and built, and how your work made the team more capable without leaving it dependent on you. 3. Additional technical interview, if needed: a deeper discussion of technical skills and open questions. 4. Product fit interview: scope a useful tool-using workflow, evaluate failures, and explain when user feedback would lead you to change or stop it. 5. Offer. What we offer Competitive base in USD, equity, relocation support, and ownership of systems that turn AI capabilities into completed creative work.

Location: Almaty, Kazakhstan Workplace: OnSite Almaty, Kazakhstan · Trust & Safety Engineering Why this role exists Higgsfield builds tools for AI creators: creative workflows, collaborative projects in Cinema Studio, and a community for sharing work. We need a backend engineer who combines deep database and architecture expertise with the initiative to own product outcomes, from the first idea to production. What you'll actually do - Build AI creation workflows, Cinema Studio collaboration, and community features: sharing, discovery, contests, profiles, and follows. - Own features and bugs through release and follow-up. Define API contracts and coordinate frontend work to deliver the complete feature. - Deliver responsive UX: live progress, timely updates, and clear failure recovery, even when it takes more engineering effort. - Remove database and service bottlenecks under high traffic; improve correctness, latency, and reliability. - Define success metrics, build dashboards and alerts, and track adoption and system health after launch. Must-haves 1. Deep database expertise: data modeling, indexes, query plans, partitioning, transactions, and locking. You diagnose production bottlenecks and understand the trade-offs behind your fixes. 2. Strong architecture judgment: service boundaries, APIs, asynchronous workflows, caching, and failure handling. Hands-on Kubernetes and CI/CD experience, from design and testing to deployment and debugging. 3. A track record of shipping and operating backend systems across multiple projects, including high-traffic workloads. You can explain your decisions and measurable results. 4. API security: authentication, object-level authorization, and tenant isolation. You prevent IDOR in reads and writes, including resource IDs in request bodies, and test access across users and workspaces. 5. You've built or studied social networks and collaborative tools, and can explain design trade-offs in feeds, follow graphs, notifications, sharing permissions, real-time sync, and concurrent edits. 6. High agency and ownership: you find worthwhile problems, propose improvements, remove blockers, and follow through without waiting for assignments. 7. Low ego: you welcome direct feedback, admit mistakes, change your mind with evidence, and help wherever the team needs you. 8. Ambition and optimism: hard goals and rapid growth energize you. You challenge assumptions constructively and commit to making ambitious ideas work. 9. Energy for an intense pace, shifting priorities, and urgent launches or production issues that can require work outside regular hours. Our tech stack - Languages and frameworks: Python (FastAPI), Go (Gin), and TypeScript (React/Next.js on the frontend). - Data: PostgreSQL and Redis; analytical databases such as BigQuery or ClickHouse. - Messaging: Kafka, Amazon SQS, and RabbitMQ; event-driven services and asynchronous workers. - AWS: S3, DynamoDB, ECR, and Secrets Manager. - Infrastructure: Docker, Kubernetes on Amazon EKS, Helm, Argo CD, and GitHub Actions. - Observability: Prometheus, Grafana, OpenTelemetry, and Sentry. Interview process 1. Recruiter screen: role expectations, logistics, and fit. 2. Technical interview: a difficult system you shipped, what you personally decided and built, and how your work made the team more capable without leaving it dependent on you. 3. Additional technical interview, if needed: a deeper discussion of technical skills and open questions. 4. Product fit interview: turn a user problem into a small first release, decide what to leave out, and explain how feedback would change the solution. 5. Offer. What we offer Competitive base in USD, equity, relocation support, and ownership of product experiences that directly shape how people create with AI.

Identify, generate, qualify, and close new business for customers and prospects in a defined territory. Responsible for managing the full sales lifecycle, and building the go-to-market.

Own the value plan for each account in your portfolio, connecting the business problem that led the customer to buy Mixpanel with the outcomes they measure. Build relationships with business and technical stakeholders, aligning Mixpanel's capabilities to what customers care about most.

Responsibilities: — Manage a pipeline of institutional clients including crypto treasuries, DAOs, and crypto funds — Identify, pitch, and create product demos — Coordinate with marketing to develop BD strategies and initiatives — Own end-to-end client relationships from onboarding to commercialization — Collaborate cross-functionally with internal stakeholders across teams and geographies Requirements: — Minimum 3 years in a client-facing role — Bachelor’s degree in a related field — Rigorous self-starter with excellent communication and interpersonal skills — Passion for real-world assets and OpenEden’s mission — Entrepreneurial, relentless, with a strong work ethic — Familiarity with the crypto and DeFi industry — Proven ability to commercialize deals and build partnerships Benefits: — Early-employee opportunity at a crypto-finance/fintech startup — Learn about cryptocurrencies and crypto assets from industry veterans — Solve fast-moving, challenging, and unique business problems — Large responsibilities from Day 1 with ownership of your learning curve — Flat, dynamic, and fast-paced environment — Competitive compensation including equity

Location: Remote, United States 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. As a Manager, Customer Success , you will lead a North America-based team that helps customers realize value from GitLab through strong adoption, measurable outcomes, and trusted partnership. You will partner closely with both executive sponsors and day-to-day end users/practitioners to drive adoption and measurable outcomes. Reporting to the Director of Customer Success, , you will coach Customer Success Managers and Customer Success Architects to support account health across onboarding, adoption stages, executive business reviews, and renewals, while also improving how the team works. This is a people leadership role with broad scope: you will develop talent, strengthen customer relationships, and partner across Sales, Product, Engineering, and other teams so customers are supported through growth, change, and escalation. What you'll do Lead a team of Customer Success Managers and Customer Success Architects focused on customer adoption, account health, customer satisfaction, and advocacy. Coach team members through regular feedback, development support, and career growth conversations to strengthen knowledge, communication, and execution. Partner with the Director of Customer Success to define team goals, clarify responsibilities, and align priorities with company direction. Manage resource assignments, staffing levels, and hiring activity to support team coverage and customer needs. Develop senior-level relationships with customers and support the team in building trusted advisor partnerships. Collaborate with Sales, Product Management, Engineering, Professional Services, and other internal teams to create a consistent customer experience. Support customers during escalations by working with other leaders to coordinate clear, effective responses. Improve the processes and tools used by the team and oversee initiatives tied to objectives and key results. What you'll bring Experience leading customer-facing teams in software, technology, consulting, sales, or customer success environments. Ability to guide teams that drive software adoption and manage customer relationships across onboarding, adoption, business reviews, and renewals. Knowledge of software development lifecycle practices, related tools, and agile or DevOps ways of working. Familiarity with cloud or container technologies such as Kubernetes and Docker, application security concepts such as static application security testing (SAST) and dynamic application security testing (DAST), or cloud platforms such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. Skill in translating strategy into clear initiatives, coordinating execution, and tracking delivery across competing priorities. Capability to lead distributed teams across regions, cultures, and lines of business, while working effectively with senior executives and external stakeholders. Willingness to travel occasionally for customer meetings and team events, as needed. Strength in communication, coaching, feedback, delegation, planning, and process improvement. Warmth and care in your leadership approach—able to coach with empathy and build trust on a human level. Interest in candidates with transferable experience who can connect technical concepts to business value and collaborate well across functions. About the team On the Customer Success team, we are accountable for customer adoption, measurable outcomes, customer satisfaction, and building customer advocacy across GitLab. We also act as a key connection point between customers and the broader GitLab ecosystem, helping streamline collaboration with Product Management, Engineering, Sales, Professional Services, and other partners. In this role, you will manage a team in North America while collaborating asynchronously with stakeholders across regions, with a focus on helping customers succeed at scale and improving how the organization supports them. How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Location: San Francisco, CA | New York City, NY | Washington, DC About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Integrity and Authenticity Policy Manager, you will be responsible for developing, refining, and maintaining policies that prevent the misuse of AI systems for deception, manipulation, and unauthorized monitoring at scale. You will serve as the policy owner for risks related to inauthentic behavior, influence activity, surveillance, and the profiling of individuals and groups, and you will help shape policy frameworks across several areas, including authenticity, information integrity, and privacy and surveillance. Your initial focus will be on translating the Integrity and Authenticity risk framework into clear, enforceable policies, ensuring policy language addresses emerging threats identified by partner teams, and establishing guidelines that enable consistent enforcement decisions. Many of the most serious harms in this space begin with upstream steps that look routine on their own, such as compiling records about a person, automating account creation, or sorting users by inferred identity. Part of your work will be defining where those steps become prohibited. The role will expand as AI capabilities advance. Safety is core to our mission. You will help ensure our products cannot be used to deceive people at scale, monitor and profile people without their knowledge or consent, or sort and target populations based on sensitive characteristics. Important context for this role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature, as well as detailed descriptions of privacy violations, surveillance abuses, and deceptive campaigns targeting vulnerable people. Key responsibilities Develop and define policy boundaries for covert monitoring, tracking, and surveillance across different contexts, drawing the distinction between malicious behaviors and compliant dual-use scenarios Write policy guidance on facial recognition, voice cloning, and geolocation inference, specifying which uses require consent and which are prohibited outright Map the surveillance lifecycle, from target selection and data collection through analysis and covert deployment, and define the policy line at each stage so that interventions can occur early in the chain Design and oversee evaluations that measure the model's capability to support social media monitoring, people-finding, predictive profiling, and the identification or tracking of specific people, to build, develop and improve safeguards with cross-functional partners to prevent malicious behaviors Write and refine external-facing Usage Policy language and develop training guidelines, assessment rubrics, and evaluation protocols for enforcement teams, with emphasis on indicators of covert monitoring and population-level targeting Validate enforcement decisions and automated assessments, provide policy guidance on complex edge cases such as investigative research into surveillance tools, coordinate with civil society, privacy experts, threat intelligence researchers, and academics, and serve as the escalation point for complex integrity and surveillance cases Minimum qualifications Working knowledge of how deceptive campaigns and covert monitoring operate in practice, including account networks, bot operations, data aggregation pipelines, and attribution methods Familiarity with surveillance technologies and their misuse, including social media monitoring tools, people-search services, location tracking, spyware, facial recognition, and open-source intelligence techniques used against individuals General knowledge of the global regulatory landscape around data protection, privacy, platform regulation, and digital services accountability Strong policy writing skills, with the ability to translate complex threat frameworks into clear, enforceable guidelines Experience designing policies and workflows that enable both clear human enforcement decision-making and technical implementation in ML classifiers and detection pipelines Strong collaboration skills and extensive experience partnering with Engineering, Data Science, Legal, Threat Intelligence, and Policy teams on cross-functional initiatives Excellent written and verbal communication skills, with the ability to explain deceptive tactics, surveillance methods, and policy rationales to diverse audiences, including non-specialists and policymakers Preferred qualifications 5+ years of experience in policy development, trust and safety, threat intelligence, or platform integrity, with hands-on work on inauthentic behavior, surveillance-related abuse, or data misuse Experience in privacy policy, privacy engineering, or data protection work, including familiarity with privacy impact assessments and data minimization principles Experience in intelligence roles, state-aligned monitoring operations, or covert data collection campaigns Experience investigating inauthentic networks, covert monitoring, or surveillance abuses at a platform, research organization, or government body Background in digital forensics, open-source intelligence, or threat attribution Knowledge of persuasion theory, cognitive biases, and deceptive communication techniques, including social engineering and pretexting methods Familiarity with human rights and privacy frameworks as they apply to surveillance, including protections for journalists, activists, and marginalized communities Experience with trust and safety operations involving content moderation evasion, bot detection, or platform scraping enforcement Experience working with EU institutions, regulatory bodies, or policy organizations on AI governance or digital platform regulation Experience conducting adversarial testing, red teaming, or vulnerability assessments for AI systems or platforms, particularly for misuse involving monitoring or profiling Familiarity with generative AI capabilities and an understanding of how LLMs can be used for synthetic personas, social engineering, predictive profiling, or surveillance at scale The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $245,000 — $285,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Join Anthropic's Customer Success team in a high-visibility & high-impact role driving AI adoption across a small number of enterprise accounts in our Enterprise Tech segment. As our dedicated Customer Success Manager for Enterprise Tech Customers you’ll be their partner and trusted advisor helping them harness the full potential of all our Claude capabilities - API, Claude Code, Cowork, and other surface areas. You'll work with a book of global technology leaders to actively deploy AI and reshape the technology landscape. You’ll be working with key partners who are moving fast and pushing the boundaries of what's possible with LLM technology. Your role will entail developing genuine partnerships with the customer and key stakeholders, gaining a deep understanding of their multi-pronged business objectives, strategic direction, AI vision, and technical needs. You'll draw on both your business acumen and technical expertise to serve as a strategic advisor throughout their journey with us. In partnership with the broader account team, you will help customers identify the right Claude capabilities for their specific business objectives, working closely with them to provide best practices and guidance while supporting them as their usage grows and evolves. Your role focuses on helping customers scale their usage effectively, drive model and use case optimizations, implement change management strategies, and maximize the value of their investment through expanded use cases across their organization. The insights you gather from your customers will directly inform our research priorities, product development, and go-to-market strategies — making you a key voice in shaping how we build and deliver ongoing value as a business. Responsibilities: Build trusting, strategic relationships with key customer decision makers in complex, matrixed organizations; understand their business and objectives and identify opportunities for optimization and expansion Own customer operations across the lifecycle of each account, maintaining a structured operational assessment (customer readiness, operational health, strategic alignment, enablement strategy, adoption intelligence) that grounds comprehensive account and success plans and Executive Business Reviews Become an expert in Anthropic's products across API, Claude Code and Cowork, understanding the technical nuances and best practices for each to guide customers to the right solutions Leverage your deep knowledge of each customer, and the patterns you see across your other Tech accounts, to proactively drive consumption planning and the value story behind it, developing credible ROI hypotheses and quantifying outcomes that build the case for continued and expanded investment. Monitor usage patterns and identify optimization opportunities across Claude surface areas (API, Claude Code, Cowork) to drive full value from contracted commitments Serve as the customer’s thought partner, enhancing their knowledge of Claude products by socializing Anthropic’s product roadmap, driving awareness on new products and engaging Product PMs Develop and execute change management strategies to drive end-user adoption and maximize value within customer organizations, including Train the Trainer programs, Center of Excellence development, and organizational enablement Ruthlessly prioritize across the account's many business units and workstreams, building programmatic, repeatable motions You may be a good fit if you have: 6+ years of experience in Customer Success, Technical Account Management, Solutions Engineering, or Strategy Consulting Experience working with F500 technology companies, SaaS platforms, or digital-first businesses at the exec level—ideally including high-growth and established tech companies. You understand what it means to lead organization-wide change or adoption programs (multiple functions, hundreds of users) for a product that requires C-suite sponsorship Technical fluency with ability to understand and articulate AI/ML concepts, API integrations, and software implementation patterns across a set of diverse stakeholders—from developers and product managers to executives and end users Proven track record managing a portfolio of accounts while maintaining strong relationships and driving measurable outcomes — you can run multiple enterprise motions in parallel without letting any account go quiet. Cross-functional collaborator who represents the customer in a positive, proactive manner, rallying everyone around paths forward that solve customer needs Passion for AI and interest in responsible development of advanced systems. You have built with Claude Code, automating your own workflows with agents, skills, and tooling. A knack for bringing order to chaos and an enthusiastic "roll up your sleeves" mentality The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $200,000 — $265,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About The Anthropic Institute The Anthropic Institute (TAI) is a function within Anthropic that works to advance the public conversation around AI. The Institute is comprised of research teams tackling some of AI's most consequential societal challenges: the Frontier Red Team, which stress tests our systems against catastrophic risks; Societal Impacts, which studies how Claude is used by millions of people; Economic Research, which tracks AI's impact on people's jobs and the larger economy; the Rule of Law team, which studies AI's impacts to democracy; and more. The Institute's mission is to reduce information asymmetries between Anthropic and the outside world, name and answer the hard questions implied by powerful AI systems, and publish these findings so that policymakers, researchers, technology leaders, and the public can reckon with what's here and what's to come. About the role The role. You will build and lead the Institute’s tabletop exercise program and the team that runs it. Based on trends visible in the exponential and in consultation with technical experts, you will set the research agenda: which questions the exercises should answer, which scenarios to run, with which audiences, and what each run is meant to test. You will own the methods that make results comparable across runs and turn them into findings people outside the room can use. You will hire and manage a team plus a bench of facilitators, and you will be the program’s public voice. Why tabletop exercises? If RSI arrives, the hardest problems will be about making decisions under uncertainty. The people making them may not trust each other, and the authorities they work under may not be fit-for-purpose. A tabletop exercise (TTX) allows the people who would face that situation practice it before it is real. It also shows us what tools and information they reach for, including what they would need that does not exist yet. Tabletop exercises are also a research method. You can run the same scenario many times, with different groups of people (and with many more AI agents playing in silico), and you start to see the distribution of decisions people make. This is one of the few ways to generate empirical evidence about the future, i.e., how people and institutions will respond to situations that have not happened yet. Key responsibilities Set the program’s research agenda: the questions exercises should answer, the scenarios to run, and the audience for each Design exercises as empirical studies: define what each run tests, standardize scenarios and data capture so results are comparable, and use repeated play to map the range of outcomes Build the program’s measurement: pre- and post-exercise assessments, decision logs, transcript analysis and after-action reports Turn results into findings: publish on what the exercises show, and brief senior people inside and outside Anthropic on the gaps they expose Hire, manage and develop a team and a bench of facilitators Make the program scalable: maintain a library of tested scenarios that the team reuses most of the time, refreshed on a regular cadence so they stay timely Build a facilitator kit ("TTX in a box") so other internal teams or external partners can run exercises to the same standard Create and direct the tools behind the exercises, including Claude-driven simulations that generate a live outside-world feed during play Minimum qualifications Have designed and run tabletop exercises, wargames, or simulations for senior decision-makers and published on the subject Have training in a discipline that uses simulation, experimental methods or structured analysis Have 10+ years of experience in national security, government, technology policy, or strategy Can keep the scenarios technically grounded with a strong grasp of AI capabilities and safety research Have managed a team, including hiring, setting direction, giving feedback and developing people Use Claude and other AI tools extensively in your own work Care about AI safety and Anthropic's public benefit mission Preferred qualifications Published research on wargaming methods, simulation or crisis decision-making Run exercises that fed into real policy or crisis-response decisions Run multi-iteration or experimental wargames and analyzed results across runs Used AI agents or language models as players, adjudicators or analysts in simulations Led a research program or team through a period of growth Existing relationships across national security, government, policy and AI, and are trusted in those communities Published widely read work on AI, emerging technology, strategy or crisis decision-making We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $295,000 — $295,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Baghdad, Iraq Toters is an on-demand e-commerce and delivery platform and operates a service that enables customers to get anything in their city at the highest level of convenience. At Toters, technology is at the heart of everything we do. We have product teams that are working hard every day to create products that make our customers' lives easier. Our engineers are also continuously creating solutions to make our processes more efficient, all in an effort to get to our customers fast and at the best cost. If you are interested in working in a high growth startup environment, and look to be part of a team that will potentially change the way customers shop in the Middle East, apply now. Role Overview The Site Engineer is responsible for overseeing the day-to-day execution of renovation, construction, and fit-out activities of Toters Fresh Warehouses . The role ensures that works are executed according to approved designs, specifications, quality standards, safety requirements, approved budget and project timelines. Key Responsibilities Supervise daily construction, renovation, and fit-out activities on site. Monitor contractors and subcontractors to ensure works are executed according to approved  specifications, plan and budget. Conduct regular site inspections and identify quality, technical, or safety issues. Review technical drawings and ensure accurate implementation on site. Coordinate civil, electrical, HVAC, plumbing, and other MEP activities. Track project progress and report delays, issues, and deviations to the Management. Verify measurements and quantities of completed works. Assist in reviewing BOQs, quotations, variations, and contractor submissions. Coordinate with contractors and suppliers to ensure timely delivery of materials and completion of works. Ensure proper housekeeping, safety, and compliance with site requirements. Support testing, commissioning, snagging, and final handover of facilities. Maintain site records, progress reports, inspection reports, and relevant documentation. Support the preparation and updating of warehouse layouts and floor plans when required. Supervise maintenance projects when required Coordinate with the Maintenance team to improve the finishing quality and overall execution of renovation projects. Requirements Bachelor’s degree in Civil Engineering, Electro-Mechanical Engineering, or related field . Experience in renovation, construction, or fit-out project execution . Experience in retail, commercial, warehousing, or similar environments is preferred. Good understanding of civil and MEP works. Ability to read and interpret technical drawings. Strong site supervision and problem-solving skills. Good organizational and communication skills. Ability to work on-site and manage multiple activities simultaneously.

Location: United States About Gramian Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role We are seeking experienced U.S.-licensed attorneys with tax law expertise to support the training and evaluation of next-generation AI systems. You will analyze tax law scenarios, review AI-generated legal analyses and documents, identify errors or gaps in legal reasoning, and provide structured feedback to improve accuracy and completeness. This role is ideal for attorneys with strong legal judgment, excellent written communication, and experience interpreting complex legal issues. Prior AI experience is not required. SENIORITY: Experienced Legal Professional LANGUAGE: Excellent written English LOCATION: Remote — United States only Key Responsibilities Analyze tax law scenarios, identify key legal issues, assess risks, and apply sound legal judgment. Review AI-generated legal analyses, arguments, and documents for legal accuracy, completeness, and consistency. Identify legal errors, missing information, unsupported conclusions, and weaknesses in legal reasoning. Evaluate the application of relevant federal and state tax laws to complex factual scenarios. Provide clear, structured feedback and corrections to improve AI-generated legal outputs. Apply consistent review standards while maintaining strong attention to detail and professional judgment. Requirements Juris Doctor (J.D.) degree from a U.S. law school. Active license to practice law in at least one U.S. state or the District of Columbia. More than 3 years of substantive legal practice, preferably with experience in tax law. Strong legal reasoning, issue-spotting, and legal document review skills. Excellent written English communication and the ability to explain complex legal concepts clearly. Strong analytical skills, attention to detail, and the ability to work independently.

Location: United Kingdom; Germany; Poland; South Africa; United Arab Emirates; Egypt About Gramian Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role We are seeking an accomplished Scientific Research Expert with deep expertise in computer science, computational physics, or related theoretical and mathematical disciplines to contribute to an advanced AI research project. In this role, you will work with frontier AI models and agents to investigate open research problems, evaluate theoretical and computational results, and establish rigorous standards for measuring scientific progress. You will help guide multi-step research workflows involving proofs, algorithms, numerical experiments, simulations, and high-performance computing, while documenting model limitations and identifying promising directions for further investigation. Prior AI industry experience is not required; exceptional research expertise and rigorous scientific judgment are the priorities. SENIORITY: Principal / Research Leader LANGUAGE: Excellent written English LOCATION: Remote — Worldwide Key Responsibilities Identify and formulate foundational open problems, theoretical bounds, and computational challenges where progress can be rigorously demonstrated. Guide AI models and agents through complex, multi-step research workflows involving mathematical proofs, algorithm development, numerical experiments, and high-performance simulations. Validate research results using proof verification, computational reproduction, formal methods, and other rigorous evaluation techniques. Assess the novelty, correctness, and scientific significance of research outputs against established findings and current literature. Prepare concise research memos documenting attempted solutions, partial progress, model limitations, and recurring reasoning failures. Recommend promising research directions, subfields, and open problems suitable for investigation using advanced AI models and computational tools. Apply critical judgment when reviewing technical work beyond your immediate research specialization. Help establish evaluation standards that distinguish genuine scientific progress from plausible but unsupported results. Requirements Approximately 7–10+ years of active research experience in computer science, mathematical physics, computational physics, or a closely related discipline. Strong record of scholarly contributions, including publications in leading conferences, journals, or other recognized research venues. Deep hands-on experience with computational research methods, such as numerical analysis, simulation, algorithm implementation, or high-performance computing. Demonstrated ability to evaluate technical claims rigorously, verify results, and identify gaps in mathematical or computational reasoning. Strong familiarity with the research literature and established results in your field. Excellent analytical, technical writing, and research communication skills. Ability to work independently, assess ambiguous problems, and communicate findings clearly.

Location: Brazil; Argentina; Colombia; Chile; Peru; Uruguay About Gramian Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role We are seeking an accomplished Scientific Research Expert with deep expertise in computer science, computational physics, or related theoretical and mathematical disciplines to contribute to an advanced AI research project. In this role, you will work with frontier AI models and agents to investigate open research problems, evaluate theoretical and computational results, and establish rigorous standards for measuring scientific progress. You will help guide multi-step research workflows involving proofs, algorithms, numerical experiments, simulations, and high-performance computing, while documenting model limitations and identifying promising directions for further investigation. Prior AI industry experience is not required; exceptional research expertise and rigorous scientific judgment are the priorities. SENIORITY: Principal / Research Leader LANGUAGE: Excellent written English LOCATION: Remote — Worldwide Key Responsibilities Identify and formulate foundational open problems, theoretical bounds, and computational challenges where progress can be rigorously demonstrated. Guide AI models and agents through complex, multi-step research workflows involving mathematical proofs, algorithm development, numerical experiments, and high-performance simulations. Validate research results using proof verification, computational reproduction, formal methods, and other rigorous evaluation techniques. Assess the novelty, correctness, and scientific significance of research outputs against established findings and current literature. Prepare concise research memos documenting attempted solutions, partial progress, model limitations, and recurring reasoning failures. Recommend promising research directions, subfields, and open problems suitable for investigation using advanced AI models and computational tools. Apply critical judgment when reviewing technical work beyond your immediate research specialization. Help establish evaluation standards that distinguish genuine scientific progress from plausible but unsupported results. Requirements Approximately 7–10+ years of active research experience in computer science, mathematical physics, computational physics, or a closely related discipline. Strong record of scholarly contributions, including publications in leading conferences, journals, or other recognized research venues. Deep hands-on experience with computational research methods, such as numerical analysis, simulation, algorithm implementation, or high-performance computing. Demonstrated ability to evaluate technical claims rigorously, verify results, and identify gaps in mathematical or computational reasoning. Strong familiarity with the research literature and established results in your field. Excellent analytical, technical writing, and research communication skills. Ability to work independently, assess ambiguous problems, and communicate findings clearly.

Location: India; Australia; Japan; Singapore; Philippines; New Zealand About Gramian Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role We are seeking an accomplished Scientific Research Expert with deep expertise in computer science, computational physics, or related theoretical and mathematical disciplines to contribute to an advanced AI research project. In this role, you will work with frontier AI models and agents to investigate open research problems, evaluate theoretical and computational results, and establish rigorous standards for measuring scientific progress. You will help guide multi-step research workflows involving proofs, algorithms, numerical experiments, simulations, and high-performance computing, while documenting model limitations and identifying promising directions for further investigation. Prior AI industry experience is not required; exceptional research expertise and rigorous scientific judgment are the priorities. SENIORITY: Principal / Research Leader LANGUAGE: Excellent written English LOCATION: Remote — Worldwide Key Responsibilities Identify and formulate foundational open problems, theoretical bounds, and computational challenges where progress can be rigorously demonstrated. Guide AI models and agents through complex, multi-step research workflows involving mathematical proofs, algorithm development, numerical experiments, and high-performance simulations. Validate research results using proof verification, computational reproduction, formal methods, and other rigorous evaluation techniques. Assess the novelty, correctness, and scientific significance of research outputs against established findings and current literature. Prepare concise research memos documenting attempted solutions, partial progress, model limitations, and recurring reasoning failures. Recommend promising research directions, subfields, and open problems suitable for investigation using advanced AI models and computational tools. Apply critical judgment when reviewing technical work beyond your immediate research specialization. Help establish evaluation standards that distinguish genuine scientific progress from plausible but unsupported results. Requirements Approximately 7–10+ years of active research experience in computer science, mathematical physics, computational physics, or a closely related discipline. Strong record of scholarly contributions, including publications in leading conferences, journals, or other recognized research venues. Deep hands-on experience with computational research methods, such as numerical analysis, simulation, algorithm implementation, or high-performance computing. Demonstrated ability to evaluate technical claims rigorously, verify results, and identify gaps in mathematical or computational reasoning. Strong familiarity with the research literature and established results in your field. Excellent analytical, technical writing, and research communication skills. Ability to work independently, assess ambiguous problems, and communicate findings clearly.

Location: United States; Panama; Guatemala; Mexico; Costa Rica; Canada About Gramian Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role We are seeking an accomplished Scientific Research Expert with deep expertise in computer science, computational physics, or related theoretical and mathematical disciplines to contribute to an advanced AI research project. In this role, you will work with frontier AI models and agents to investigate open research problems, evaluate theoretical and computational results, and establish rigorous standards for measuring scientific progress. You will help guide multi-step research workflows involving proofs, algorithms, numerical experiments, simulations, and high-performance computing, while documenting model limitations and identifying promising directions for further investigation. Prior AI industry experience is not required; exceptional research expertise and rigorous scientific judgment are the priorities. SENIORITY: Principal / Research Leader LANGUAGE: Excellent written English LOCATION: Remote — Worldwide Key Responsibilities Identify and formulate foundational open problems, theoretical bounds, and computational challenges where progress can be rigorously demonstrated. Guide AI models and agents through complex, multi-step research workflows involving mathematical proofs, algorithm development, numerical experiments, and high-performance simulations. Validate research results using proof verification, computational reproduction, formal methods, and other rigorous evaluation techniques. Assess the novelty, correctness, and scientific significance of research outputs against established findings and current literature. Prepare concise research memos documenting attempted solutions, partial progress, model limitations, and recurring reasoning failures. Recommend promising research directions, subfields, and open problems suitable for investigation using advanced AI models and computational tools. Apply critical judgment when reviewing technical work beyond your immediate research specialization. Help establish evaluation standards that distinguish genuine scientific progress from plausible but unsupported results. Requirements Approximately 7–10+ years of active research experience in computer science, mathematical physics, computational physics, or a closely related discipline. Strong record of scholarly contributions, including publications in leading conferences, journals, or other recognized research venues. Deep hands-on experience with computational research methods, such as numerical analysis, simulation, algorithm implementation, or high-performance computing. Demonstrated ability to evaluate technical claims rigorously, verify results, and identify gaps in mathematical or computational reasoning. Strong familiarity with the research literature and established results in your field. Excellent analytical, technical writing, and research communication skills. Ability to work independently, assess ambiguous problems, and communicate findings clearly.