Currently tracking 241 active AI roles, down 26% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $123k–$392k (avg $231k).
Capital One currently has 293 active AI-related job listings. The majority of these roles are focused on serving infrastructure, accounting for 28% of the total, followed closely by agents at 26% and post-training at 23%. Engineering is the dominant function, with 234 roles, and hiring is primarily concentrated in the United States. Frequent tech tags include model_serving, vector_db, and llm_observability, suggesting a focus on the operational aspects of AI deployment. In the last 30 days, Capital One posted 124 new AI roles, representing a 22% increase compared to the previous 30-day period.
Capital One currently has 305 active AI-related roles in our index. The most common open titles are: Senior Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) (9), Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) (8), Applied Researcher I (6), Distinguished Engineer (6), Applied Researcher II (5). Most positions are in Engineering and Research.
Capital One's active AI hiring is concentrated in: serving infrastructure (28%), agents (27%), post-training (23%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Capital One is hiring AI talent in: United States (299 roles), United Kingdom (3 roles), Canada (2 roles), Philippines (1 role).
Job postings at Capital One most frequently reference: model serving, vector db, fine tuning, llm observability, inference infra.
In the past 30 days, Capital One has posted 96 new AI-related roles. That is a -26% change versus the prior 30 days (130 → 96).
| Title | Stage | AI score |
|---|---|---|
| Lead AI Engineer (AI Foundations) Lead AI Engineer focused on AI Foundations, responsible for designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, governance, and observability. The role involves optimizing large-scale production AI systems for performance (scalability, cost, latency, throughput) using various AI technologies and contributing to the technical vision and roadmap of foundational AI systems. | ServeAgent | 8 |
| Senior Lead AI Engineer,(MLX, Agentic AI, Gen AI platform Services) Senior Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems at Capital One. Responsibilities include designing, developing, testing, deploying, and supporting AI software components like foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves leveraging AI technologies and optimizing LLM performance for scalability, cost, and latency. |
| ServeAgent |
| 8 |
| Senior Lead AI Engineer (MLX, Agentic AI, Gen AI platform Services) Senior Lead AI Engineer role focused on building and scaling Gen AI platform services, including foundation model training, LLM inference, similarity search, guardrails, and model evaluation. The role involves optimizing performance (scalability, cost, latency, throughput) of large-scale production AI systems and contributing to the technical vision for foundational AI systems. Requires strong engineering and AI expertise, with experience in cloud platforms and programming languages like Python. | ServeAgent | 8 |
| Lead AI Engineer (MLX, Agentic AI, Gen AI platform Services) Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems, including LLM inference, similarity search, guardrails, and model evaluation, with an emphasis on optimizing performance and scalability for enterprise use. | ServeAgent | 8 |
| Senior Lead AI Engineer (FM Hosting, LLM Inference) Senior Lead AI Engineer focused on LLM inference and hosting infrastructure, optimizing performance, scalability, cost, and latency for large-scale production AI systems. The role involves designing, developing, and deploying AI software components, including foundation model training, inference, similarity search, guardrails, evaluation, governance, and observability, leveraging various AI technologies and cloud platforms. | ServeAgent | 8 |
| Sr. Lead AI Engineer (AI Foundations) This role focuses on engineering AI foundations, including foundation model training, LLM inference, similarity search, guardrails, model evaluation, and optimization techniques for scalability, cost, latency, and throughput. It involves leveraging AI technologies and contributing to the technical vision and roadmap of foundational AI systems. | ServeAgent | 8 |
| Lead AI Engineer (AI Foundations) Lead AI Engineer focused on building and optimizing foundational AI systems, including LLM inference, similarity search, guardrails, and model evaluation, to enhance customer and associate experiences within a large enterprise. | ServeAgent | 8 |
| Director, Data Scientist - Generative AI Systems Capital One is seeking a Director, Data Scientist to lead the Generative AI Systems team. This role involves building and operationalizing AI-powered products, specifically focusing on LLMs for customer-facing applications in dialogue, summarization, comprehension, speech, and image processing. The position requires leading a team of specialists, experimenting with generative AI, and contributing to research. The role emphasizes partnering with cross-functional teams, leveraging technologies like PyTorch, AWS, Hugging Face, LangChain, and VectorDBs, and managing the full ML lifecycle from design to production for over 80 million customers. | AgentPost-train | 8 |
| Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Lead AI Engineer role focused on building and deploying AI-powered products, including foundation model training, LLM inference, similarity search, guardrails, and model evaluation. The role involves leveraging AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails, and optimizing LLM performance for scalability, cost, and latency. The position requires a strong engineering foundation and experience in AI/ML algorithm development and deployment on cloud platforms. | AgentServe | 8 |
| Distinguished AI Engineer This role focuses on engineering and deploying AI-powered products and foundational AI systems, including large language model inference, optimization, and related components like similarity search and guardrails. The primary focus is on the serving and optimization of AI models in production, with a secondary involvement in agentic systems. | ServeAgent | 8 |
| Senior Distinguished AI Engineer Senior Distinguished AI Engineer role focused on designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves inventing and introducing state-of-the-art LLM optimization techniques to improve performance (scalability, cost, latency, throughput) of large-scale production AI systems, and contributing to the technical vision and roadmap of foundational AI systems. Requires strong engineering and mathematics foundation, expertise in hardware, software, and AI, and experience with cloud platforms and programming languages like Python, Go, Scala, or Java. | ServeAgent | 8 |
| Lead AI Engineer (MLX) Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems. Responsibilities include designing, developing, testing, deploying, and supporting AI software components such as foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves optimizing LLM performance for scalability, cost, latency, and throughput using various AI technologies and cloud platforms. | ServeAgent | 8 |
| Lead AI Engineer Lead AI Engineer role focused on designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves leveraging AI technologies, inventing LLM optimization techniques to improve performance (scalability, cost, latency, throughput) of large-scale production AI systems, and contributing to the technical vision and roadmap of foundational AI systems. Requires strong engineering and mathematics foundation, expertise in hardware, software, and AI, and experience with cloud platforms and AI/ML algorithms. | ServeAgent | 8 |
| Senior Lead AI Engineer Senior Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems within an enterprise setting. Responsibilities include designing, developing, testing, deploying, and supporting AI software components such as foundation model training, LLM inference, similarity search, guardrails, model evaluation, and observability. The role emphasizes optimizing LLM performance for scalability, cost, latency, and throughput, and contributing to the technical vision and roadmap of foundational AI systems. | ServeAgent | 8 |
| Lead AI Engineer (Gen AI Platform, Agentic AI & LLM Infrastructure & Orchestration) Lead AI Engineer role focused on building and scaling Gen AI platforms, agentic AI systems, and LLM infrastructure. The role involves designing, developing, and deploying AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, and observability. It emphasizes optimizing LLM performance for scalability, cost, latency, and throughput, and leveraging a broad stack of AI technologies. | AgentServe | 8 |
| Senior Lead AI Engineer Senior Lead AI Engineer role focused on designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves inventing and introducing state-of-the-art LLM optimization techniques to improve the performance of large-scale production AI systems, leveraging technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails. This position is key to bringing AI capabilities to life at Capital One, empowering teams across the company and delivering value to millions of customers. | ServeAgent | 8 |
| Lead AI Engineer Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems within a fintech company. Responsibilities include designing, developing, testing, deploying, and supporting AI software components such as foundation model training, LLM inference, similarity search, guardrails, model evaluation, and observability. The role emphasizes optimizing LLM performance (scalability, cost, latency, throughput) and contributing to the technical vision and roadmap for AI systems. Requires experience with AI/ML algorithms, programming languages like Python, and cloud platforms, with a focus on deploying scalable and responsible AI solutions. | ServeAgent | 8 |
| Distinguished AI Engineer (Agentic AI Platform) The role is for a Distinguished AI Engineer focused on building an enterprise Generative AI Platform. The engineer will design the agentic workflow framework, shared services (memory, guardrails, vector search, SDKs), and blueprints to enable product teams to compose AI capabilities. Key responsibilities include evaluating agentic frameworks, developing an end-to-end GenAI SDK/CLI, implementing central guardrail services, optimizing orchestration for performance, and mentoring other engineers. The role emphasizes creating scalable, safe, and explainable AI solutions for millions of users. | AgentServe | 8 |
| Senior Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Senior Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. It also focuses on optimizing LLM performance (scalability, cost, latency, throughput) for production AI systems and contributing to the technical vision and roadmap of foundational AI systems. | AgentServe | 8 |
| Senior Lead AI Engineer (Gen AI Platform Services) This role focuses on engineering and optimizing AI software components, particularly large language model inference and related platform services, to improve performance, scalability, cost, and latency in a production environment. It involves designing, developing, testing, deploying, and supporting these components, leveraging various AI technologies and cloud platforms. | ServeAgent | 8 |
| Senior Lead AI Engineer (GenAI Platform Services) Senior Lead AI Engineer responsible for designing, developing, testing, deploying, and supporting AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves optimizing LLM performance for scalability, cost, and latency, and contributing to the technical vision and roadmap of foundational AI systems. | ServeAgent | 8 |
| Senior Lead AI Engineer (FM Hosting) This role focuses on designing, developing, testing, deploying, and supporting AI software components, including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The engineer will invent and introduce state-of-the-art LLM optimization techniques to improve the performance of large-scale production AI systems and contribute to the technical vision and roadmap of foundational AI systems. The role involves leveraging various AI technologies and optimizing for scalability, cost, latency, and throughput. | ServeAgent | 8 |
| Distinguished Engineer Distinguished Engineer role focused on building and scaling agentic AI systems for marketing and sales within an enterprise context. Responsibilities include prototyping, defining technical strategy, influencing architecture, and mentoring teams, with a focus on real-time, hyper-personalized customer engagement and assistive technologies for sales teams. | Agent | 8 |
| Lead AI Engineer (FM Hosting, LLM Inference) Lead AI Engineer focused on LLM inference and optimization for AI-powered products within a large enterprise. The role involves designing, developing, and deploying AI software components, with a strong emphasis on improving the performance, scalability, cost, and latency of production AI systems. | ServeAgent | 8 |
| Senior Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Senior Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, governance, and observability. It also requires inventing and introducing LLM optimization techniques to improve performance (scalability, cost, latency, throughput) of large-scale production AI systems. The role leverages AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch. | ServeAgent | 8 |
| Sr. Lead AI Engineer This role focuses on designing, developing, testing, deploying, and supporting AI software components, including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The engineer will also invent and introduce LLM optimization techniques to improve the performance (scalability, cost, latency, throughput) of large-scale production AI systems, leveraging technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails. The role is within the Intelligent Foundations and Experiences (IFX) team, aiming to advance AI science and engineering and deploy proprietary solutions. | ServeAgent | 8 |
| Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Lead AI Engineer role focused on building and deploying AI-powered products, including foundation model training, LLM inference, similarity search, guardrails, and model evaluation. The role involves leveraging AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails, and optimizing LLM performance for scalability, cost, and latency. The position requires a strong engineering foundation and experience in AI/ML algorithm development and deployment on cloud platforms. | AgentServe | 8 |
| Senior Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Senior Lead AI Engineer role focused on AI Foundations, LLM Core, and Agentic AI. Responsibilities include designing, developing, testing, deploying, and supporting AI software components like foundation model training, LLM inference, similarity search, guardrails, model evaluation, and governance. The role involves optimizing LLM performance for scalability, cost, and latency, and contributing to the technical vision for foundational AI systems. It requires experience with cloud platforms and AI/ML algorithms, particularly LLM inference, similarity search, vector databases, and guardrails. | ServeAgent | 8 |
| Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. Key responsibilities include optimizing LLM performance for scalability, cost, latency, and throughput using various AI technologies and techniques. | ServeAgent | 8 |
| Senior Lead AI Engineer (LLM Customization and Finetuning) Senior Lead AI Engineer focused on LLM customization and finetuning within Capital One's Intelligent Foundations and Experiences (IFX) team. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. It requires leveraging AI technologies like Huggingface, VectorDBs, and PyTorch, and optimizing LLM performance for scalability, cost, latency, and throughput in production AI systems. The candidate should have a strong engineering and mathematics foundation, experience with cloud platforms, and the ability to lead and mentor teams. | Post-trainServe | 8 |
| Senior Lead AI Engineer (FM Hosting, LLM Inference) Senior Lead AI Engineer focused on optimizing LLM inference performance, scalability, cost, and latency for production AI systems within Capital One's Intelligent Foundations and Experiences (IFX) team. The role involves designing, developing, and deploying AI software components, including foundation model training, inference, similarity search, guardrails, evaluation, and observability, leveraging cloud platforms and open-source AI technologies. | ServeAgent | 8 |
| Lead AI Engineer (FM Hosting, LLM Inference) Lead AI Engineer focused on optimizing LLM inference for scalability, cost, and latency within an enterprise AI setting. The role involves designing, developing, and deploying AI software components, including foundation model training, inference services, similarity search, guardrails, and model evaluation, leveraging cloud platforms and various AI technologies. | ServeAgent | 8 |
| Senior Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Senior Lead AI Engineer role focused on AI Foundations, LLM Core, and Agentic AI. Responsibilities include designing, developing, testing, deploying, and supporting AI software components such as foundation model training, LLM inference, similarity search, guardrails, model evaluation, and agentic systems. The role involves optimizing LLM performance for scalability, cost, and latency, and contributing to the technical vision and roadmap for foundational AI systems. Requires strong engineering and mathematics foundation, expertise in Python/Go/Scala/Java, and experience with cloud platforms and AI technologies like Huggingface, VectorDBs, and PyTorch. | AgentServe | 8 |
| Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Lead AI Engineer role focused on building and deploying AI-powered products, including foundation model training, LLM inference, similarity search, guardrails, and model evaluation. The role involves leveraging AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails, and optimizing LLM performance for scalability, cost, and latency. The position requires a strong engineering foundation and experience in AI/ML algorithm development and deployment on cloud platforms. | AgentServe | 8 |
| Director, AI Engineering Director of AI Engineering responsible for the strategic vision, development, and management of autonomous AI systems and platforms, with a focus on agentic workflows and ensuring compliance with regulations and ethical AI best practices within a fintech domain. | Agent | 8 |
| Senior Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Senior Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. It also focuses on optimizing LLM performance (scalability, cost, latency, throughput) for production AI systems and contributing to the technical vision and roadmap of foundational AI systems. | AgentServe | 8 |
| Senior Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Senior Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. It also focuses on optimizing LLM performance (scalability, cost, latency, throughput) for production AI systems and contributing to the technical vision and roadmap of foundational AI systems. | AgentServe | 8 |
| Lead AI Engineer Lead AI Engineer role focused on designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves leveraging AI technologies and optimizing LLM performance for scalability, cost, latency, and throughput within an enterprise AI context. The position emphasizes building AI-powered products and foundational AI systems for millions of customers. | ServeAgent | 8 |
| Senior Manager, Data Scientist - US Card (Generative AI Systems) Senior Manager, Data Scientist for the Generative AI Systems (Genesis) team within Capital One's US Card division. This role focuses on building and delivering state-of-the-art generative AI-based solutions for various applications including dialogue, text summarization, reading comprehension, speech recognition, image/document processing, and time-series modeling. The goal is to enhance both internal business efficiency and customer-facing experiences. The role involves partnering with cross-functional teams, leveraging a broad tech stack, and building ML models through all phases of development. | ShipPost-train | 8 |
| Senior Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Senior Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. It also includes optimizing LLM performance for scalability, cost, latency, and throughput using various AI technologies and cloud platforms. The role emphasizes building responsible and reliable AI systems for banking applications. | ServeAgent | 8 |
| Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. It also includes optimizing LLM performance for scalability, cost, latency, and throughput using various AI technologies and techniques. | ServeAgent | 8 |
| Senior Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Senior Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, and observability. It also emphasizes inventing and introducing LLM optimization techniques to improve the performance of large-scale production AI systems. | ServeAgent | 8 |
| Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Lead AI Engineer role focused on building and deploying AI-powered products, including foundation model training, LLM inference, similarity search, guardrails, and evaluation. The role involves optimizing performance, scalability, cost, and latency of large-scale production AI systems using various AI technologies and cloud platforms. | ServeAgent | 8 |
| Manager, Data Science - AI Foundations Manager, Data Science - AI Foundations role at Capital One focuses on building and shipping AI/ML solutions for customer-facing applications, including personalization and digital assistants. The role involves leveraging LLMs, fine-tuning them, and building ML/NLP models through all development phases, from design to production operationalization. It emphasizes partnering with cross-functional teams and utilizing technologies like PyTorch, AWS, Hugging Face, LangChain, and VectorDBs. | Post-trainServe | 8 |
| Principal Data Scientist, AI Foundations This role focuses on building and shipping AI/ML solutions for Capital One's mobile app, leveraging LLMs and generative AI. The Principal Data Scientist will partner with cross-functional teams to deliver AI-powered products, adapt and fine-tune LLMs for customer-facing applications, and build ML/NLP models through all phases of development, including training, evaluation, and validation, with a strong emphasis on operationalizing them in production systems serving millions of customers. Experience in training language models, computer vision models, and expertise in areas like training optimization, self-supervised learning, explainability, and RLHF are required, along with a track record of delivering models at scale. | Post-trainServe | 8 |
| Senior Manager, Data Science - AI Foundations Senior Manager, Data Science - AI Foundations role at Capital One, focusing on building and shipping AI/ML solutions for their mobile app. The role involves partnering with cross-functional teams, leveraging technologies like PyTorch, AWS, Hugging Face, LangChain, and VectorDBs, and specializing in NLP and LLMs for customer-facing applications. Responsibilities include model development from design to production, operationalization, and translating complex work into business goals. The ideal candidate is customer-first, innovative, creative, a leader, technical with hands-on LLM experience, and influential. Experience in training language models, computer vision models, and expertise in areas like training optimization, self-supervised learning, explainability, and RLHF is required, along with a track record of delivering models at scale in both training and inference. | Post-trainServe | 8 |
| Manager, Data Scientist - Business Cards & Payments Credit Infrastructure Team Capital One is seeking a Manager, Data Scientist for their Business Cards & Payments Credit Infrastructure Team. This role involves building machine learning models for credit card acquisitions valuations, supporting credit programs through robust models and tools. The candidate will partner with cross-functional teams, leverage technologies like Python, AWS, and Spark, and translate complex work into business goals. The ideal candidate is customer-focused, creative, a leader, technically proficient with open-source tools and cloud platforms, and statistically minded with experience in various modeling techniques. | Post-train | 7 |
| Principal, Data Scientist - Card Intelligence This role focuses on building and deploying machine learning models for the credit card lifecycle, including marketing, underwriting, and fraud prevention. The candidate will work with a cross-functional team, leverage technologies like Python and AWS, and be responsible for all phases of model development from design to implementation. The role requires a strong statistical background and experience with various machine learning techniques. | Post-train | 7 |
| Senior Associate, Data Scientist - Card Intelligence Data Scientist role focused on building and deploying machine learning models for the credit card lifecycle, including marketing, acquisitions, underwriting, and fraud prevention. The role involves leveraging customer data, applying various ML techniques, and working with technologies like Python, AWS, and Spark. | Post-train | 7 |
| Senior Lead Software Engineer, Full Stack (Enterprise Platform Technology) This role focuses on building and operating AI-native software engineering harnesses, including agentic workflow orchestration systems, to enable governed AI model and coding agent delivery. It involves defining contracts, developing observability for AI-assisted workflows, integrating evaluation results into CI/CD, and building reusable APIs and services for AI-native engineering practices within an enterprise platform. | AgentEval Gate | 7 |