The Cognizant Automation practice delivers enterprise‑grade AI, Machine Learning, GenAI, Agentic AI, Smart Data Intake, and Intelligent Automation solutions across mission‑critical business and IT processes. We are seeking a highly technical AI Architect for Automation Delivery to drive the design, engineering, and implementation of scalable AI automation programs for a North America–based client, with a strong focus on Banking and Financial Services (BFS) environments.
This role is deeply execution‑oriented and requires strong architectural judgment, hands‑on delivery leadership, and the ability to translate business needs into robust, production‑ready AI systems. The Engagement Lead will own the technical roadmap, solution architecture, delivery governance, and operationalization of AI and automation solutions at scale, ensuring alignment with BFS regulatory, risk, and operational requirements.
Key Responsibilities:
AI‑Led Automation Architecture
• Lead the end‑to‑end architecture of AI/ML/GenAI/Agentic AI solutions—including model selection, data pipelines, orchestration layers, integration patterns, and deployment architecture—tailored for BFS use cases such as KYC/AML, fraud detection, credit decisioning, servicing, and regulatory reporting
• Define reference architectures, reusable frameworks, and engineering standards for automation and AI workloads across financial operations
• Architect solutions using cloud AI services (Azure OpenAI, AWS Bedrock, GCP Vertex), IPA platforms (UiPath, Power Platform), and custom Python‑based pipelines, ensuring compatibility with core banking systems, payment platforms, and risk engines
• Conduct technical feasibility assessments, including data availability, model readiness, integration constraints, and infrastructure requirements within regulated BFS environments
• Ensure solutions meet enterprise standards for security, scalability, observability, compliance, responsible AI, and BFS‑specific model risk management expectations
• Own the technical delivery lifecycle: requirements, solution design, development oversight, testing, deployment, and hypercare
• Guide engineering teams on model training, prompt engineering, RAG pipelines, vector databases, orchestration frameworks, and automation workflows supporting high‑volume financial processes
• Oversee creation of APIs, microservices, connectors, and integration layers to embed AI into enterprise systems such as core banking, CRM, and data platforms
• Implement CI/CD pipelines, MLOps practices, and automation deployment frameworks aligned with BFS governance and auditability needs
• Drive performance tuning, model evaluation, monitoring, and continuous improvement of deployed AI systems
• Establish AI governance and AI strategy including model lifecycle management, versioning, auditability, and risk controls consistent with BFS regulatory expectations
• Serve as the primary technical advisor to client architects, product owners, and engineering leaders, supporting adoption and operationalization of AI solutions across financial operations
• Lead AI programs, driving alignment between business stakeholders, technical teams, and delivery partners, with experience navigating BFS risk, compliance, and operational constraints
Required Skills & Qualifications
AI/ML/GenAI Technical Expertise • Strong practitioner experience designing and implementing AI/ML pipelines, GenAI solutions, RAG architectures, and agent‑based systems • Hands‑on experience with cloud AI platforms: o Azure AI / Azure OpenAI o AWS AI/ML stack o GCP Vertex AI • Experience with vector databases (Pinecone, FAISS, Chroma, Redis), embeddings, prompt engineering, and LLM orchestration frameworks • Proficiency in Python, API development, microservices, and automation frameworks
Candidate Background The ideal candidate brings a strong development and technical background, with hands‑on experience in modern engineering stacks such as Python, Java, .NET, and related frameworks. A deep understanding of scalable architecture and clean coding practices is essential, along with experience delivering AI or automation solutions within regulated financial institutions.
Automation & Integration Experience • Strong understanding of workflow orchestration, event‑driven architectures, and enterprise integration patterns • Experience integrating AI with core systems (policy admin, claims, CRM, data lakes, APIs), including BFS platforms such as core banking, payments, lending, and risk systems
Architecture & Delivery Leadership • Proven ability to lead large‑scale AI automation delivery programs with complex technical dependencies • Strong background in MLOps, DevOps, CI/CD, model monitoring, and production deployment • Experience conducting architecture reviews, threat modeling, and performance optimization • Ability to create technical roadmaps, solution blueprints, and engineering playbooks
Cognizant will only consider applicants for this position who are legally authorized to work in the United States without requiring company sponsorship now or at any time in the future.
关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
薪酬信息截至本职位发布之日为准确。Cognizant 保留在适用法律允许的范围内随时修改该信息的权利。
申请人可能需要通过现场面试或视频会议的方式参加面试。此外，候选人在每次面试时可能需要出示其当前所在州或政府签发的有效身份证件。
Cognizant 是一家提供平等就业机会的雇主。在招聘过程中，您的申请和候选资格不会因种族、肤色、性别、宗教、信仰、性取向、性别认同、国籍、残疾、遗传信息、怀孕、退伍军人身份或任何其他受联邦、州或地方法律保护的特征而受到影响。
