Agentic Ai Platform Senior Account Manager Uk And in United States

About the Team The Solutions Engineering team is made up of trusted technical advisors who help organizations adopt OpenAI’s technology safely, effectively, and responsibly. We partner closely with customers, Sales, Product, Engineering, and Security to translate frontier AI capabilities into practical workflows that create real-world impact. Cybersecurity is one of the most urgent areas where AI can help. As frontier models become more capable at reasoning over code, logs, infrastructure, and security evidence, organizations need guidance on how to evaluate, validate, and deploy these systems safely. Our goal is to help customers move from identifying risks to implementing solutions. About the Role We are committed to bringing together people from diverse backgrounds and perspectives who are excited to help build and deploy safe, useful AI. We are seeking a solutions engineer to partner with our Enterprise customers and ensure they achieve tangible business value from our models through the OpenAI suite of products. You will partner with senior business stakeholders to understand their pre-sales needs, guide their AI strategy, and identify the highest value use cases and applications. You will work with business and technical teams to demonstrate the value of our solutions and recommend architectural patterns to kickstart their implementation and development. You will work closely with Enterprise Sales, Security, and Product teams. We are looking for a Field Security Specialist to help security leaders and hands-on practitioners understand how OpenAI models, APIs, Codex, and agentic workflows can be applied to real cybersecurity use cases. This is a customer-facing specialist role for someone who can move fluidly between CISO-level conversations, practitioner-level technical depth, and hands-on solution design. You’ll help customers evaluate OpenAI for workflows like secure code review, vulnerability triage, threat modeling, remediation, SOC workflows, detection en

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, you will improve the capabilities, reliability, and product fit of OpenAI's agentic models. You might own a research direction, build the infrastructure that makes large training runs faster and more trustworthy, create evals that reveal where models fail, or drive a capability from an idea through experimentation, integration, and launch. This role is intentionally broad. The strongest candidates are not defined by one method or subfield; they are people who can take an ambiguous capability problem and make progress across research, engineering, data, evals, and product. You should be excited to work on models that act in the world: writing and debugging code, using tools, calling functions, operating computers, collaborating with other agents, and completing valuable work on behalf of users. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, meas

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, Artifacts, you will train frontier models to create polished, useful work products: documents, spreadsheets, slide decks, dashboards, reports, analyses, and other interactive or editable artifacts. You will help teach our models to move from a vague user goal to a finished artifact with strong structure, visual taste, domain judgment, correctness, and low latency. This work will require owning improvements across our post-training stack, including RL, data pipelines, graders, reward signals, evals, and behavioral analysis. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you will: Design and run experiments that improve agentic model behavior for complex so

About the Team The Codex Research team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of the Codex Research team, you will improve the capabilities, reliability, and product fit of OpenAI's agentic models. You might own a research direction, build the infrastructure that makes large training runs faster and more trustworthy, create evals that reveal where models fail, or drive a capability from an idea through experimentation, integration, and launch. This role is intentionally broad. The strongest candidates are not defined by one method or subfield; they are people who can take an ambiguous capability problem and make progress across research, engineering, data, evals, and product. You should be excited to work on models that act in the world: writing and debugging code, using tools, calling functions, operating computers, collaborating with other agents, and completing valuable work on behalf of users. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measu

About the Team The Agent Safety team works to ensure that increasingly capable AI agents act safely, exercise sound judgment, and remain aligned with user intent. Our mission is to reduce the probability of severe unintended outcomes from increasingly capable AI agents while preserving their ability to act effectively and autonomously. Our work spans three areas: Training: Create training methods, environments and data that teach agents to make better decisions in consequential situations. We turn real-world failures into training signals that prevent similar incidents, and identify precursor behaviors and mitigations to address emerging risks. Measurements: Build evaluations and production metrics that identify emerging risks and measure whether our interventions work. Oversight : Develop oversight and system mitigation mechanisms that reduce harmful actions while preserving useful agent autonomy (for example future versions of auto-review ). About the Role This role focuses on oversight and system-level mitigations that enable increasingly capable agents to operate safely and autonomously in real environments. We prioritize building oversight systems that are used in practice today, both internally and externally (see our recent work on action monitoring for codex and former code review ). We also study longer-term questions about how increasingly capable agentis systems can be supervised, constrained, and corrected. We’re looking for a safety&security minded researcher or engineer who can reason rigorously about security boundaries and agent behavior, then build and test practical mitigations. A background in AI control or security is welcome but not required. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, build, and evaluate system-level controls for agent actions like agent-based review. Plan how they fit in a broader syste

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary The Manager - Process Engineering leads high-impact process improvement and Business Process Management (BPM) initiatives across Information Security and Technology Solutions (ISTS). This role is accountable for enabling operational excellence by designing, standardizing, improving, and governing ISTS processes using agentic workflows, Lean Six Sigma, and Business Process Management disciplines. The Manager- Process Engineering serves as both a delivery leader and capability builder, ensuring that ISTS has well-documented, measurable, and continuously improving processes with clear ownership, performance indicators, and controls. This role partners closely with technology tower leaders, Experience Owners, Process Owners, and risk, security, and compliance stakeholders to reduce operational friction, increase capacity, mitigate risk, and strengthen enterprise controls. Key Responsibilities: Apply DMAIC and Lean Six Sigma methodologies to solve complex, cross‑funct

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Plaid’s Consumer team owns all of Plaid’s consumer facing surfaces. This includes Link, Plaid’s flagship product, which has been used by over half of all US adults to share their information safely and securely with financial applications. Link drives the vast majority of Plaid’s revenue. We’re also building out Plaid’s first B2C product, which is an exciting, 0-1 space for us. Both areas are top business priorities. Responsibilities As the Plaid Account PM, you will own everything related to the consumer identity on Plaid. This includes: User authentication (UX and risk models) Launching a surface for users to manage their connections and permissioning with various applications. This spans across both traditional fintech and agentic fintech. Leading company-wide workstreams around establishing a first party relationship with consumers Roadmap around creating deeper and richer network of consumer profiles on Plaid Define the roadmap for sign up for quarterly / half year goals and partner with cross-functional team to hit them Drive prioritization and execution (build, measure, iterate) Identify opportunities through consumer feedback and staying close to our data / dashboards Part