Job DescriptionWe are looking for a highly skilled Principal Solution Architect to join our AI solutioning team. In this role, you will lead pre-sales solutioning for enterprise Agentic AI engagements. You will be the technical face to the customer during the sales cycle - assessing their data landscape, designing target state architecture and developing compelling technical proposals that win RFIs and RFPs. In this pre-sales solutioning role, you will partner closely with Sales, Business development, Consulting and Delivery teams to ensure what we propose is both best-in-class and deliverable at a reasonable cost and time.
Key Responsibilities- Design multi-agent systems using frameworks like LangGraph, Crew.ai, Strands SDK, Microsoft Agent Framework or Google ADK with clear agent contracts, guardrails, observability and governance
- Provide pre-sales solution support for RFIs/RFPs, Capability/PoV presentations and customer workshops related to GenAI/Agentic AI use cases
- Provide technical advisory on Agentic AI topics such as orchestration patterns, evaluation, observability, AgentOps, context engineering etc. to customers
- Architect context engineering patterns covering semantic layers, vector stores, metadata catalogs, lineage and knowledge graphs to setup data for AI Agents consumption
- Establish engineering patterns for MCP server development, A2A protocol integration and tool orchestration
- Demonstrate technical authority and thought leadership in GenAI/Agentic AI discussions
- Lead architecture reviews and make technology selection decisions across the stack
- Leverage coding agents to experiment and build AI Agent prototypes to demonstrate tools & design patterns
- Create architecture decision frameworks, technology comparison matrices and visual slide decks to communicate complex architecture and technical strategies to mixed audience (executive + engineering)
- Mentor engineering and sales teams on agentic patterns, context engineering and the evolving AI services landscape
- Provide technology consulting support to delivery, CoE/community by publishing best practices/architectural guidelines, providing training, publishing whitepapers/case studies and building reusable components.
Requirements:• Overall, 15 + years of experience in the Data Engineering and/or AIML Space
• 2+ years of experience in Generative AI/Agentic AI architecture & implementation
• 2+ years of experience in pre-sales solutioning in GenAI/Agentic AI space
• Strong proficiency in one or more Agentic AI frameworks (LangGraph, Crew.ai, Strands SDK, Google ADK, Microsoft Agent Framework)
• Strong proficiency in foundational models and AI/GenAI Services in one of the hyperscalers (AWS, Azure, GCP)
• Deep expertise in architecting & implementing multi-agentic systems with appropriate guardrails, observability and governance
• Deep expertise in advanced prompt engineering, RAG implementation and AI Agents evaluation techniques
• Proven track record of designing, developing and deploying AI Assistants & AI Agents in production environments.
• Solid understanding of Generative AI fundamentals, LLMOps/AgentOps and cloud platforms (AWS,).
• Familiarity with responsible AI practices and AI governance processes
• Basic understanding on building lakehouse and data products in Snowflake and Databricks
• Prior experience in building ontologies and knowledge graphs is an added advantage
• Excellent problem-solving, communication, and leadership skills.
Additional employment informationCompensation 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.
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.
