AI Architect for Automation Delivery (Remote)

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.

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.

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
• Define reference architectures, reusable frameworks, and engineering standards for automation and AI workloads
• Architect solutions using cloud AI services (Azure OpenAI, AWS Bedrock, GCP Vertex), AI capabilities provided by IPA platforms (UiPath, Power Platform), and custom Python‑based pipelines
• Conduct technical feasibility assessments, including data availability, model readiness, integration constraints, and infrastructure requirements
• Ensure solutions meet enterprise standards for security, scalability, observability, compliance, and responsible AI
• 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
• Oversee creation of APIs, microservices, connectors, and integration layers to embed AI into enterprise systems
• Implement CI/CD pipelines, MLOps practices, and automation deployment frameworks
• 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
• Serve as the primary technical advisor to client architects, product owners, and engineering leaders. Drive adoption and operationalization of AI solutions through training, change management, and platform enablement
• Lead for AI programs, driving alignment between business stakeholders, technical teams, and delivery partners. Should bring strong experience leading complex AI initiatives, manage cross‑functional engagement, and translating strategic objectives into actionable program plans
  
  

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:
• Azure AI / Azure OpenAI
• AWS AI/ML stack
• 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.

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)
  
  

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.