Team Member Gcc in United States

Become a part of our caring community The Strategy Advancement Advisor is a member of Humana’s People Innovation team, which helps shape and advance the future of HR by translating enterprise and workforce priorities into focused strategies and measurable outcomes. This role partners with HR and business leaders to frame complex challenges, develop fact-based recommendations, and move high-priority initiatives from strategy through execution. The Advisor will work across a varied portfolio of enterprise people priorities and transformation efforts, bringing structure to ambiguity, connecting work across functions, and helping leaders make informed decisions that improve business, workforce, and associate outcomes. Humana is seeking an experienced strategy professional to join the People Innovation team. The team serves as a strategic partner to HR and the business, helping identify, shape, and advance high-impact opportunities that support Humana’s people strategy and broader enterprise transformation. Our work spans emerging workforce priorities, talent and organizational strategies, operating model and work redesign, and other cross-functional initiatives that require enterprise perspective, disciplined problem solving, and coordinated execution. As a Strategy Advancement Advisor, you will lead and support a portfolio of complex, high-visibility initiatives from early problem definition through recommendation and activation. You will work with senior leaders, HR partners, subject matter experts, and cross-functional teams to clarify business needs, synthesize internal and external insights, evaluate strategic choices, and translate direction into practical plans. The role requires the ability to move between strategy and execution, build alignment across a matrixed organization, and produce clear, executive-ready recommendations that enable timely decisions and

A Career with Point72’s Technology Team As Point72 reimagines the future of investing, our Technology team is constantly evolving our firm’s IT infrastructure and engineering capabilities, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision making and enhance how we build and operate our platforms and applications. As a member of Point72’s Technology team, we encourage and support your professional development from day one—helping you advance your technical skills, contribute innovative ideas, and satisfy your own intellectual curiosity—all while delivering real business impact for our multi-billion-dollar global business. What you’ll do Develop and maintain the information security policy and standards library, aligning it with business priorities, regulatory expectations, and control objectives Lead independent assessments of the information security program, including regulatory examinations and third-party evaluations Identify technology risks across a complex business environment and drive mitigation aligned with our firm’s standards and control expectations Investigate data privacy inquiries and privacy-related events, assess business impact, and coordinate timely response activities Partner with technology, legal, compliance, and business stakeholders to translate risk findings into practical remediation plans Advise control owners on policy interpretation, risk treatment, and evidence expectations for assessments and examinations Prepare clear reports for management on team activity, emerging risks, remediation progress, and key decisions Maintain accurate risk, policy, priv

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

NVIDIA is looking for an experienced software engineer with infrastructure experience to become a senior member of the Cloud Foundations Automation - Development Team. We build and manage the automation ecosystem supporting NVIDIA's GPU Cloud and NVIDIA SuperPod deployments. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most hard-working and dedicated people on the planet working for us. If you're creative and autonomous, we want to hear from you! What you'll be doing: Developing software to enable efficient network design, deployment and day 2 management. Building product focused software solutions, used by internal and external customers. Helping us as we transform our workflows and organization into a centrally orchestrated configuration management framework, operating at scale across geographies. Owning and driving integrations with various service APIs such as Cloud Service Providers, to automate creation of environments and auto populate data sources in turn. Building on open source software, designing and implementing data structures and UI interfaces to automate processes from equipment purchase to device config generation to deployment to operations. Streamlining deployment mechanisms and life cycle operations Developing modern service architectures around streaming data and event pipelines. Working with infrastructure domain experts on true, zero touch deployment solutions and utilizing best of breed high performance computing management solutions. Be a proactive problem solver, looking out for new opportunities to improve our services and customer experience. Communicate readily with your peers across the organization, b

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, Connectors, you will teach models how to interface with the top professional software using code. You will help train agents to use code, APIs, tools, and structured integrations to operate across applications like Slack, Google Workspace, GitHub, Notion, Linear, Salesforce, and other core systems of work. You will help enable models to take useful actions across a user’s digital context: finding information, updating systems, coordinating work, generating artifacts, and completing multi-step workflows through the tools teams already use. You will train models to be supercharged by the world’s most important productivity and enterprise software, turning connected tools into a powerful action surface for our agents. 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.

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 builds the data, environments, graders, training methods, and feedback loops that shape what OpenAI’s next agents can do and what they are like to work with, then carries those improvements through major training runs and into products used by people every day. About the Role As a member of the Agent Post-training Personality team, you will help make OpenAI’s agents exceptional collaborators. You will study what makes an agent thoughtful, clear, perceptive, appropriately proactive, and genuinely easy to work with, then translate those insights into evals, training data, reward signals, and model improvements. We use “personality” to mean much more than writing style or general likability. It includes whether an agent understands what the user is trying to accomplish, communicates with good judgment, adapts to context, asks useful questions, handles disagreement honestly and takes initiative at the right moments. The goal is to create a strong, tasteful default that can adapt to different people and situations. This work combines behavioral research, product thinking, research and communication taste. You will collaborate with product teams, human experts, and researchers across post-training and pretraining to ensure that improvements survive the full trai

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 this API & power-users team, you will improve the capabilities, reliability, and product fit of OpenAI’s agentic models for power users and API developers. You might design evals from real developer workflows, build training environments around production-like tool use, turn qualitative model failures into training data, evals, or post-training interventions, or drive a behavior improvement from discovery through post-training, integration, and launch. This role is intentionally broad. The strongest candidates are comfortable turning ambiguous model behavior problems into concrete progress, whether that means improving tool use, planning, instruction following, recovery from mistakes, or how models behave in API-based workflows. You should be excited to work across research, engineering, data, evals, and product to make models better at acting in real workflows. You will work closely with researchers, engineers, API/product teams, Codex, infrastructure, and safety/align

About the Team Our Applied team brings OpenAI technologies to consumers and businesses around the world. We collaborate across research, engineering, design and business functions to turn cutting-edge AI advancements into impactful real-world applications. Our team has been behind notable product launches ( ChatGPT , API , Sora ), creating tools that help developers write code, enable businesses to operate more efficiently, and empower individuals to learn and create. As AI capabilities rapidly evolve, we focus on ensuring that our products are safe, accessible, and beneficial to all. About the Role As a Data Scientist on the Applied Product team, you will contribute to a data-driven product development culture for consumer and enterprise products at OpenAI. This is critical as our products reach millions of users and businesses worldwide. We are focused on aligning both research and product development to drive measurable impact for these individuals and organizations alike. You should expect to define our north-star metrics, design A/B tests, and establish source-of-truth dashboards that the entire company can use to answer their own product questions. Most importantly, you should expect to be a core member of the product development team. This role is based in San Francisco, CA or Seattle, WA. 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: Embed with the product development team as a trusted partner, uncovering new ways to improve the product and drive growth Define and interpret A/B tests that help answer critical questions about the impact of model and UX changes to our product Establish a data-driven product development culture by defining, tracking, and operationalizing feature-, product-, and company-level metrics Develop and socialize dashboards, reports, and other ways of enabling the team and company to answer product data questions in a self-serve way You might thrive

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, Computer Use, you will teach models to operate computers. You will help train models that can navigate browsers and desktops, use tools and applications, reason through complex workflows, collaborate with users and other agents, and complete long-horizon tasks with reliability and judgment. This work sits at the intersection of frontier model training, product behavior, evaluation, and systems engineering, and will directly shape the computer-use capabilities shipped in OpenAI’s next generation of agents. Currently, our models are the best in the world at this behavior! 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 might Design and run experiments th

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 Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models and their deployment in the real world. Building on the many years of our practical alignment work and applied safety efforts, Safety Systems addresses emerging safety issues and develops new fundamental solutions to enable the safe deployment of our most advanced models and future AGI, to make AI that is beneficial and trustworthy. Learn more about OpenAI’s approach to safety About the Role As an Analytics Engineer in Safety Systems, you will play a pivotal role in building a data-centric culture, enhancing decision-making processes, and driving strategic initiatives through analytics. You will partner closely with Engineering, Research, and Data Science to develop and maintain canonical data sources and source-of-truth dashboards that enable both people and AI agents across the organization to derive trustworthy, actionable insights. You will own the consumption layer for safety metrics: defining intuitive, reliable ways for stakeholders across Safety Systems, partner teams, and leadership to understand the safety of our products, answer safety-related questions independently, and inform product decisions and company strategy. Most importantly, you will be a core member of the Safety Systems team, collaborating with researchers and engineers to advance our goals of safe, robust, and reliable AI. 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 and maintain canonical datasets that serve as sources of truth for safety metrics. Develop and refine data products such as dashboards, reports, agent-enabled workflows, and machine-readable interfaces that empower stakeholders to extract and analyze data independently. Work closely with stakeholders in Engineering, Research, and Data Science to understand their decision-making n

Become a part of our caring community The Market Finance Lead is a key member of the Gulf South Region’s finance team responsible for connecting market financial performance with operational effectiveness. This role will partner closely with Corporate Finance, Network Performance, Network Contracting, and regional Health Services teams. This individual will manage a team covering a diverse set of responsibilities around Medicare Advantage financial business operations with a heavy focus on value-based providers. This role reports to the Market Finance Director. This role analyzes financial results, claims experience, utilization trends, contract performance, membership, and provider performance data to identify opportunities, influence business decisions, and support market growth and operational improvement. The Market Finance Lead will partner closely with regional leadership, actuarial, corporate finance, clinical, risk adjustment, market operations, network performance, network contracting, sales/MarketPoint, and value-based care providers. This individual will translate complex financial and operational data into meaningful insights, recommendations, and action plans that improve performance across the market. As the Market Finance Lead, you will: Manage a team to review value-based providers’ financial performance, membership, cost and utilization trends, contractual results, and opportunities for improvement. Lead the financial portion of provider engagement prep sessions prior to joint operating committee meetings to advise the Network Performance team on contract performance and opportunities for improvement. Lead analysis and reporting related to value-based provider and contract performance, including financial results, utilization, claims experience, membership, and operational trends. Leverage data analytics, business ins

A Career with Point72’s Technology Team As Point72 reimagines the future of investing, our Technology team is constantly evolving our firm’s IT infrastructure and engineering capabilities, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision making and enhance how we build and operate our platforms and applications. As a member of Point72’s Technology team, we encourage and support your professional development from day one—helping you advance your technical skills, contribute innovative ideas, and satisfy your own intellectual curiosity—all while delivering real business impact for our multi-billion-dollar global business. What you’ll do Optimize cloud financial operations to maximize value from cloud investments, including rapidly growing artificial intelligence (AI) and machine learning workloads Provide actionable insights on cloud spend, SaaS license optimization, and emerging AI cost drivers, including model inference and usage-based consumption Implement tooling, tagging standards, and processes that improve cost visibility and optimization across cloud, SaaS, and AI workloads Monitor large language model API consumption and GPU-intensive infrastructure to identify cost trends, anomalies, and optimization opportunities Build financial models to forecast cloud, SaaS, and AI expenditures for budgeting cycles, commitment decisions, and vendor negotiations Design cost allocation, tagging, showback, and chargeback models that attribute spend to the teams, applications, and use cases driving it Educate engineering and business owners on cloud financial management practices th