Ai Business Solutions Architect Jobs

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 Every time Claude runs code, uses a computer, or works as an agent, it does so inside a sandbox. Our Sandboxing team builds the isolation layer behind that work. The same systems run the code Claude writes for users, the environments we train and evaluate models in, and the agents our customers deploy. These workloads are untrusted by design, and there are a lot of them. Sandboxes need to start in milliseconds, hold up under adversarial code, and scale to a very large number of concurrent sessions. You will work at the boundary between the Linux kernel, virtualization, and the container ecosystem. You will partner with research, product, and security teams to make sure that safe and fast do not trade off against each other. Key responsibilities Design, build, and operate the sandboxing infrastructure that runs untrusted, model-generated code and agent workloads at scale Improve sandbox startup time, density, and throughput, including snapshot and restore, checkpointing, and warm pools Strengthen isolation across compute, filesystem, and network, including egress controls and per-session credential handling Investigate and fix performance, reliability, and security issues at the kernel, hypervisor, and container runtime level Build the monitoring, tracing, and debugging tools that show where time and resources go inside a sandbox Work with researchers to support reinforcement learning environments and evaluations that need fast, reproducible, isolated execution Work with product and platform engineers to expose sandboxes as a dependable, well-designed capability for Claude products and customers Partner with security tea

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 Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. The RL Scaling team works on how RL scales: what happens to throughput, stability, and learning efficiency as models get larger, episodes get longer, and compute grows by orders of magnitude, and what has to change in our algorithms and systems to keep getting returns from that scale. This role sits squarely across research and engineering. You'll develop next-generation architectures and RL algorithms, take them from a small-scale result to a frontier-scale run, and understand every place they behave differently along the way. You'll build the systems that set how fast the team can iterate: how many experiments, at what scale, and how quickly we can trust the results. And you'll work on Anthropic's largest and fastest RL runs, where the gap between a good idea and a working one is often a problem no one has solved yet. Key responsibilities Study how RL training and sampling scale with model size, context length, and compute, and find the algorithmic and systems changes that keep scaling efficient Develop next-generation model architectures and RL algorithms, and make them run efficiently at frontier scale Take promising small-scale results to frontier-scale runs, and diagnose why they behave differently when they get there, whether the cause is numerical, algorithmic, or systemic Build the experimental infrastructure that sets research velocity: fast, reproducible comparisons of architecture and algorithm variants at meaningful scale Own end-to-end performance of our largest RL runs, from research code down to th

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 a Field Executive Architect, you will serve as Anthropic's senior technical voice with our most strategic customers. You'll engage directly with C-suite executives and senior technical leaders at the world's largest enterprises to understand their business, align stakeholders around a clear vision for how AI fits into their strategy, and create momentum toward adoption of Anthropic's products. This is not a hands-on-keyboard engineering role. Your job is to walk into a room full of executives, quickly understand their business and technical landscape, and help them see a clear path forward with Claude. You'll then partner with Sales and Applied AI teams to ensure that vision translates into execution -- checking in on high-momentum accounts, maintaining executive relationships, and keeping deals on track. Internally, you'll serve as a sponsor for enterprise customer needs, working with Product to ensure that what matters most to our largest accounts is heard and prioritized. You'll bring deep experience in enterprise technology and a track record of operating at the intersection of business strategy and technical execution. Whether you've been a CTO, VP of Engineering, Field CTO, or a world-class senior technical salesperson, what matters is that you've seen how large organizations make technology decisions and can meet executives where they are -- with credibility, clarity, and conviction. Responsibilities: Engage directly with C-suite and senior technical leaders at Anthropic's largest and most strategic accounts, aligning business and technical stakeholders around a clear vision for AI adoption Prepare for and le

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 Frontier research runs on more than research alone. Behind every model launch, review, and cross-team program is a web of decisions, priorities, and follow-through that keeps hundreds of researchers moving in the same direction. Research Operations owns that work: we bring clarity to ambiguity, provide stability during change, and continually deepen our domain knowledge so that researchers can spend their time on the problems only they can solve. It is one of the highest-leverage functions at Anthropic. We are hiring an experienced operator to embed with the leadership of our reinforcement learning (RL) organization, the team responsible for training Claude to be more capable, more reliable, and more aligned. You will shape what leadership spends its time on, make sure priority decisions reach the right decision-makers and get made quickly, and clear the path so leaders can focus on the work that matters most. You will report to the Manager of Research Operations and work daily with RL org leaders and their teams. Key responsibilities Own leadership's time. Shape the week around the leaders' specific, most timely priorities, set agendas so meetings are spent on decisions that move the org forward, and cut what isn't critical so leaders stay focused on the areas that are highest-leverage for them. Triage what reaches leadership. Resolve what you can, route what belongs elsewhere, and thoughtfully escalate the rest. Enable wise decision-making and follow through. Give leaders what they need to decide quickly, communicate those decisions to collaborators, and track commitments through to completion. See problems coming. Su

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: The Encodings Infra team maintains the libraries that engineers and researchers across Anthropic use to encode text and multimodal data into a form that Claude can consume. It also determines Claude’s prompt shape: how a user’s turn is represented to the model, how Claude calls tools and receives tool results, and so on. As a Software Engineer on this team, you'll own the design and maintenance of these libraries—keeping their APIs intuitive, their performance sharp, and their abstractions solid enough that most of the org never has to think about encodings or prompt structures at all. You’ll have the satisfaction of knowing that your work enabled Claude to learn new ways of understanding the world. This role is unusually broad: your work will touch systems across the codebase, from pretraining to finetuning to the API, and you'll collaborate closely with both researchers and engineers to make sure new encoding ideas can move quickly from experiment to production. Responsibilities: Maintain and improve the encoding libraries used by engineers and researchers across Anthropic Run experiments to determine the optimal way to feed structured data into Claude without confusing it Design data structures and abstractions that shield most of the organization from the details of how encoded data works while enabling “power users” Adapt the encoding libraries to support new research directions as they emerge, and make sure that we can ship these research ideas to production Optimize encoding performance across the systems that depend on these libraries You may be a good fit if you: Have 5+ years of software engineering experienc

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 We're building Anthropic's search platform team to create scalable, efficient search capabilities that power Claude's ability to access and retrieve information. In this role, you'll design and implement core search systems from the ground up. Responsibilities: Work with a small, senior team of engineers and researchers to build Anthropic’s search platform from scratch Establish metrics and tooling to measure and improve search quality Enhance search algorithms and indexing mechanisms to boost search accuracy and efficiency You may be a good fit if you: 5+ years building complex distributed systems in production Solid grasp of search fundamentals: indexing, retrieval, ranking Strong coding skills in Python, Go, Java, or similar languages Hands-on experience with high-volume data processing architectures 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: $320,000 — $405,000 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, s

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. Performance Engineer, Inference Engine About the Role Anthropic's inference engine is the software between the accelerator kernels and the routing layer. It manages the entire token path in between: batching requests, laying the model out across chips, managing memory for weights and activations, coordinating every forward pass, and managing model state across requests. Built in-house, it runs on all of our accelerator platforms, serving Claude to millions of users and running our research workloads. You will work on building and optimizing this system at Anthropic scale: improving throughput, cost, reliability, and latency across all accelerator and cloud platforms. You are intimately familiar with the hardware and bandwidth numbers (FLOPs, HBM, PCIe, RDMA, network links, etc.) and can model a problem quickly: where the time and bytes go, and what sets the bound. The role is deeply technical and high-impact, and suits engineers who enjoy working across accelerator programming, high-performance systems that seamlessly coordinate between host and device, and large-scale distributed systems. Familiarity with the transformer architecture is a plus. Some example recurring themes: Keep device utilization high. Accelerators should never be waiting due to other overheads. Reuse instead of recompute. Keep model state cached and reuse it whenever that is cheaper than computing it again. Measure, model, then change. We build the observability to see where the gaps are, model the impact of potential improvements, deploy them, and go around again, with Claude speeding up every turn of that loop. Tokens you can trust. Ensuring model quality matter

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 Anthropic is building the Forward Deployed Engineering team to help the world's most ambitious organizations adopt Claude in ways that are transformative, safe, and lasting. Our Technical Deployment Leads (TDLs) and Forward Deployed Engineers (FDEs) embed with strategic customers to ship production AI applications that solve real business problems. Our delivery model pairs two roles: FDEs own the technical artifact, and TDLs own the engagement end-to-end — from statement of work (SOW) through production deployment. As a Manager of Technical Deployment for Financial Services, you own engagement portfolio health across your vertical. You set the bar for delivery quality and build the playbooks and evaluation frameworks that let the practice scale. Your work will directly influence Anthropic's product direction and establish Anthropic as the trusted partner for AI transformation across the Fortune 100. This is a player-coach role. You need to be credible in architecture conversations with a customer's engineering leads and equally comfortable in sales conversations in front of executive sponsors, and you will lead the most complex engagements yourself when the stakes call for it. Most of your impact will come through the people you hire and the standard you hold them to. You won't write production code, but you will pressure-test the technical decisions your TDL team makes with FDEs. Responsibilities Hire, develop, and retain a team of TDLs embedded in Financial Services engagements. Set a high bar for delivery judgment, technical fluency, and customer presence, and run the interviews that hold it. Manage each TDL directly

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 Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We believe powerful AI can compress a century of scientific progress into a decade. Claude Science is a big part of building toward that future. Claude Science is an AI workbench that gives researchers a single environment for work that today spans dozens of disconnected tools — literature, specialized databases, scientific computing, analysis, and publication-ready outputs. Claude Science already renders protein structures, genome tracks, and chemical structures natively, and coordinates multi-agent workflows with built-in review for citation and calculation errors — and we're just getting started. Much of this is being built 0→1 right now, in a category no one has defined yet. We're growing the Claude Science product team. As a Product Manager on Claude Science, you will own a major area of the roadmap end to end — think expanding into new scientific fields, landing new model capabilities with researchers, or making the workbench ready for enterprise R&D teams — and help shape the overall product direction alongside the rest of the team. You'll spend real time with researchers in academic labs, biotech and pharma R&D, and research institutes to understand how science actually gets done — from hypothesis to analysis to publication and beyond— and turn what you learn into shipped product. You'll partner directly with our research teams to make the models better at science, help decide which fields and workflows we go after next, and shape what it takes for Claude Science to be trusted in enterprise and regulated research environm

We take play seriously. We’re looking for curious adventurers ready to find their party, fueled by imagination and drive to build what’s never been built before. At Hasbro and Wizards of the Coast, you’ll collaborate with passionate teams to reimagine our iconic brands and create experiences that spark joy, connection, and community through the magic of play. This is your chance to shape legendary play that lasts a lifetime. We're building something new inside our AI Studio, and we're looking for a Customer Success Engineer to help shape it with us. This role sits at the center of a new and constantly evolving business area. The problems are still taking shape, and the systems are actively being built. What excites us is the opportunity to push the boundaries of what stories and characters can be and to use technology to bring iconic IP to life in ways never before imagined. We work where storytelling, imagination, and technology converge. Our focus is on defining and building the core systems that transform characters and worlds from something audiences watch into something they can interact with and engage over time. This role is the bridge between our platform and the partners building on it. Working within the engineering team, this Customer Success Engineer will help customers take character experiences from first prototype through production, then turn what they learn in the field into a platform that needs less hand-holding each time. Success here means partners shipping faster, and the internal team never being surprised by what customers are experiencing. What You'll Do Knowing is half the battle. Implementing is the other. One week you're pairing with a partner team to get their first character experience working; the next you're turning that engagement's rough edges into a better SDK, a clearer code example, or documentation that answers the questio

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 Anthropic's RL Data Platform team builds the systems that produce, move, and serve the human data Claude learns from: the interfaces humans use to give feedback, the pipelines that turn raw feedback into training signal, and the tooling researchers use to launch, monitor, and inspect data collection. Every RL run depends on a steady supply of high-quality data - human feedback, expert demonstrations, graded transcripts - and when a researcher has an idea for new data on Monday, our job is to make it collectable by Wednesday and in the training mix by Friday. This is a full-stack, ownership-heavy role on a small, senior team. You'll design and ship web interfaces used by thousands of expert annotators, build the backend services and data pipelines behind them, and work directly with RL researchers to understand what data they need and why. You'll scope your own projects, make architectural calls, and see them through to production. We're looking for engineers who treat researchers as their users, build for reliability first, and care as much about the shape of the data leaving the system as the UI going into it. Key responsibilities Design, build, and operate the feedback and data collection interfaces used by human annotators, domain experts, and internal researchers. Build and maintain the backend services, APIs, and pipelines that route model samples to humans and return structured feedback to training. Own the reliability, latency, and usability of systems that run continuously against live model endpoints. Partner with RL researchers to translate loosely specified data needs into well-scoped collection campaigns and

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 Anthropic's Life Sciences team is building a research group focused on biological discoveries by combining AI with hands-on biological research. We're seeking research scientists with deep medicinal chemistry expertise to join the team. Our goal is to speed up progress in the life sciences by an order of magnitude, and this role puts that mission into practice. You'll be an expert medicinal chemist with hands-on experience designing, synthesizing, purifying, and characterizing small molecules. Above all, you'll close the loop between AI-generated hypotheses and experimental data to share with the community. Working alongside AI researchers and engineers, you'll drive experimental programs end to end and pressure-test AI-designed molecules and AI-proposed synthetic routes against real chemistry. This role is fully on-site in the San Francisco Bay Area. Key responsibilities Design multi-step synthetic routes for small molecules and oversee their execution end to end, including route selection, reaction optimization, purification strategy, and interpretation of full characterization data (NMR, LC-MS, HPLC) Coordinate synthesis and biological evaluation with external contract research organizations and academic partners Evaluate AI-designed molecules and AI-proposed synthetic routes, drive them to experimental readout, and feed results back to research teams Apply medicinal chemistry principles, including SAR analysis and physicochemical property optimization, to compound design and prioritization Ensure experimental data across programs is high quality and well documented, including procedures, spectra, and failure modes C

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 Anthropic is building the Applied AI team to help the world's most ambitious organizations adopt Claude in ways that are transformative, safe, and lasting. Our Forward Deployed Engineers embed directly with strategic customers to ship production AI applications that solve real business problems. As this practice grows, we need a founding leader to build and scale it. As the first FDE Manager, you'll own the team that sits at the frontier of enterprise AI deployment. You'll hire and develop a high-performing team of FDEs, set the technical and operational bar for customer engagements, and build the playbooks that turn one-off successes into repeatable patterns. You'll work hand-in-hand with Engagement Managers who own delivery logistics and stakeholder management, while you ensure your team is shipping quality code, growing technically, and representing Anthropic at the highest level in customer environments. This is a player-coach role with a strong bias toward leadership. You'll stay close enough to the technical work to review architectures, debug production issues, and pair with your team when it matters — but your primary impact will come from the people you hire, the standards you set, and the culture you create. You'll partner cross-functionally with Sales, Product, and Engineering to shape how Anthropic serves its most strategic customers, and your team's field insights will directly influence product direction. This role requires someone who thrives in ambiguity and is energized by building from zero to one. You'll be defining what good looks like for FDE management at Anthropic — there is no existing playbook t

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 Code RL at Anthropic drives reinforcement learning efforts behind Claude's coding capabilities, creating and scaling agentic coding environments. This is an engineering role with unusual latitude to set technical direction and standards. You'll be part of a team solving the engineering side of research efforts such as embedding with research teams, getting up to speed on their systems and needs, and designing the frameworks, APIs, and infrastructure that let researchers move faster, then rotating off, leaving behind well-oiled systems those teams can understand, own, and maintain themselves. Your remit also includes the ongoing health of production RL runs: maintainable, monitored, and straightforward to triage. The team's problem space spans the client side of sandboxed execution for agentic RL environments, large-scale data processing jobs, the lifecycle of production datasets, and the frameworks researchers build environments on. You won't own all of this yourself, you'll take on the slices where your depth matters most. You'll be a strong fit if you have deep expertise in Python, a refined sense of taste for API and framework design, and hard-won intuition for how complex systems fail — especially silently. You should be comfortable diving into messy research code, finding the load-bearing abstractions, and improving them incrementally while researchers continue to build on top of your work. Key responsibilities Design widely-used APIs, frameworks, and abstractions that other engineers and researchers build on, with careful attention to interface legibility and principled defaults Embed with research teams on a rota

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 Anthropic's Environments organization builds and maintains the infrastructure that improves Claude’s capabilities through reinforcement learning. That includes the frameworks researchers use to build environments and the infrastructure responsible for running them. The team's mission is to productionize research. You'll embed with research teams, get up to speed on how they work, and design the frameworks and APIs that let them move faster, building systems the team can understand, own, and maintain themselves. Scope also includes keeping production RL runs healthy, maintainable, monitored, and easy to triage. You'll be a strong fit if you have deep expertise in Python, a refined sense of taste for API and framework design, and good intuition for how complex systems fail, especially silently. It's a bonus if you've built and operated a stateful distributed system, such as a workflow engine, actor framework, or durable-execution runtime, where correctness depends on getting shared state and recovery right. You should be comfortable diving into messy research code, finding the abstractions that matter, and improving them incrementally while researchers continue to build on your work. You should also be comfortable using AI tools to accelerate your own development, but have an impulse towards deep verification. Key responsibilities Design widely used APIs, frameworks, and abstractions that other engineers and researchers build on, making correct usage the default and ruling out entire classes of errors structurally Own the platform layers that sit beneath every environment, including the agent runtime Build the