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.
The Cognizant community:
We are a high caliber team who appreciate and support one another. Our people uphold an energetic, collaborative and inclusive workplace where everyone can thrive.
- Cognizant is a global community with more than 300,000 associates around the world.
- We don’t just dream of a better way – we make it happen.
- We take care of our people, clients, company, communities and climate by doing what’s right.
- We foster an innovative environment where you can build the career path that’s right for you.
About us:
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, building the bridge between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, realize tangible returns and keep global enterprises ahead in a fast-changing world. See how at www.cognizant.com or @cognizant.
Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.
If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email [email protected] with your request and contact information.
Disclaimer: Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.