Agentic AI Architect

Job Title: Agentic AI Architect

Role Summary

The Agentic AI Architect is responsible for designing, building, and operationalizing autonomous AI systems (AI agents) that can reason, plan, and execute tasks across enterprise ecosystems. This role combines deep expertise in AI/ML, Generative AI, distributed systems, and enterprise architecture to enable intelligent, self-orchestrating workflows that enhance business productivity and decision-making.

Key Responsibilities

1. Architecture & Design

• Define end-to-end Agentic AI architecture frameworks leveraging LLMs, multi-agent systems, and orchestration layers
• Design autonomous AI agents capable of planning, reasoning, memory management, and tool usage
• Establish reference architectures for enterprise-grade AI applications (cloud-native, scalable, secure)
• Integrate AI agents with enterprise systems (Data Platforms, ERP, CRM, APIs, and event-driven systems)

2. Agentic AI Development

• Build and deploy multi-agent systems using frameworks such as LangChain, Semantic Kernel, AutoGen, CrewAI, or similar
• Implement agent orchestration patterns (planner-executor, reflection loops, self-healing agents)
• Develop agents with capabilities including:
  • Task decomposition and planning
  • Contextual reasoning and chaining
  • Memory (short-term, long-term, vector-based retrieval)
  • Tool calling and API integrations

3. GenAI & LLM Integration

• Architect solutions leveraging leading LLMs (Azure OpenAI, OpenAI, Anthropic, etc.)
• Implement RAG (Retrieval-Augmented Generation) pipelines with vector databases (FAISS, Pinecone, Azure AI Search, etc.)
• Optimize prompt engineering, fine-tuning, and grounding strategies
• Ensure efficient token usage, latency, and cost optimization

4. Enterprise Integration

• Integrate Agentic AI solutions with:
  • Data ecosystems (Azure Databricks, Synapse, Snowflake)
  • Workflow tools (ServiceNow, Power Platform, custom enterprise apps)
  • APIs, microservices, and event-driven architectures
• Enable AI-driven automation across business processes

5. Governance, Security & Responsible AI

• Define AI governance frameworks (auditability, compliance, explainability)
• Implement guardrails for safe and responsible AI usage
• Ensure data privacy, model security, and regulatory compliance
• Design monitoring mechanisms for hallucination detection and agent reliability

6. Performance Optimization & Scalability

• Optimize inference performance, caching strategies, and execution flows
• Design scalable multi-agent systems across distributed/cloud environments
• Monitor throughput, reliability, and system health

7. Leadership & Strategy

• Lead architecture discussions with stakeholders and executive leadership
• Drive AI adoption strategy and roadmap across business units
• Mentor engineering teams on Agentic AI best practices
• Evaluate emerging tools, frameworks, and innovations in AI ecosystems

Required Qualifications

Education

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related field

Experience

• 10+ years in software engineering, data engineering, or enterprise architecture
• 3–5+ years in AI/ML or Generative AI solution development
• Hands-on experience with LLM-based applications and orchestration frameworks

Required Technical Skills

AI/ML & GenAI

• LLMs, prompt engineering, fine-tuning
• RAG, embeddings, vector databases
• Multi-agent architectures and agent frameworks

Programming

• Python (primary), with experience in AI libraries
• Familiarity with Java/Scala/Node.js (optional but useful)

Cloud Platforms

• Azure (preferred), AWS, or GCP
• Azure OpenAI, Azure AI Studio, Databricks

Data & Platforms

• Data engineering ecosystems (Databricks, Snowflake, Synapse)
• REST APIs, microservices, event streaming (Kafka, Event Hub)

DevOps & MLOps

• CI/CD pipelines, Docker, Kubernetes
• Monitoring, logging, experiment tracking

Preferred Skills

• Experience with Autonomous AI systems / AI agents in production
• Knowledge of knowledge graphs and semantic search
• Exposure to reinforcement learning or adaptive systems
• Experience in Insurance/Financial Services domain (nice to have for enterprise roles like AIG)

Key Competencies

• Strategic thinking and enterprise architecture design
• Strong problem-solving and system design skills
• Excellent stakeholder communication and leadership abilities
• Ability to translate business requirements into AI solutions

*Please note this role is not able to offer visa transfer or sponsorship now or in the future*

We're excited to meet people who share our mission and who can make an impact in a variety of ways. Don't hesitate to apply—even if you only meet the minimum requirements. Think about your transferable experiences and unique skills that make you stand out.

Salary and Other Compensation:

Applications will be accepted until July 29, 2026,

The annual salary for this position is between $ 90,000 - $ 150,000 depending on experience and other qualifications of the successful candidate.

This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.

Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:

• Medical/Dental/Vision/Life Insurance
• Paid holidays plus Paid Time Off
• 401(k) plan and contributions
• Long-term/Short-term Disability
• Paid Parental Leave
• Employee Stock Purchase Plan

Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.

À propos de Cognizant 
Cognizant (NASDAQ : CTSH) est un AI Builder et une entreprise de services numériques (ESN) élaborant des solutions complètes d’IA maximisant les investissements pour des résultats concrets. Sa profonde expertise des métiers, des processus et des technologies lui permet d’intégrer dans les systèmes technologiques le contexte unique de chaque organisation de l’ingénierie à la production à l’échelle. Son objectif : améliorer l’efficacité des équipes, créer de la valeur et permettre aux grandes entreprises de rester performantes dans un monde qui évolue rapidement. Pour en savoir plus : cognizant.ai ou @cognizant. 

Renseignments suppplémentaires sur l'emploi
Les informations sur la rémunération sont exactes à la date de publication. Cognizant se réserve le droit de modifier ces informations à tout moment, conformément aux lois applicables.

Les exigences linguistiques varient selon les postes, mais nous demandons à tous les candidats d’avoir une connaissance de base de l’anglais afin de faciliter les communications internes à l’échelle de l’entreprise. Pour les postes basés au Québec, une maîtrise de l’anglais est requise puisque vous fournirez des services et collaborerez avec des parties prenantes situées hors de la province, qui ne parlent pas nécessairement le français. 

Cognizant est un employeur souscrivant au principe de l’égalité d’accès à l’emploi. Votre candidature et votre dossier ne seront pas examinés en fonction de la race, de la couleur, du sexe, de la religion, des croyances, de l'orientation sexuelle, de l'identité de genre, de l'origine nationale, du handicap, de l'information génétique, de la grossesse, du statut d'ancien combattant ou de toute autre caractéristique protégée telle que décrite par les lois fédérales, provinciales ou locales.

Si vous avez un handicap qui nécessite un aménagement raisonnable pour rechercher une offre d'emploi ou poser une candidature, envoyiez un courriel à [email protected] avec votre demande et vos coordonnées.