Technical Lead
- Cognizant
- 6 - 9 years
- Chennai
- 19 hours ago
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Job Description
Job Summary
We are seeking a highly skilled Generative AI Architect specializing in AI agent design and development to lead the creation of intelligent autonomous systems using advanced LLMs and orchestration frameworks. The role involves designing scalable AI architectures building multi-agent workflows and enabling enterprise-level adoption of GenAI-powered solutions.
Responsibilities
- Design and implement LLM-powered AI agents for enterprise use cases such as automation decision support and conversational systems
- Architect multi-agent systems including tool-using agents planning agents and collaborative agent ecosystems
- Define architecture patterns for memory context management and stateful interactions
- Design end to end generative AI solutions that leverage Google BARD and ChatGPT to optimize product management workflows and software asset life cycle activities
- Lead technical discovery with product managers to translate complex business objectives in product management and software asset life cycle management into clear generative AI solution requirements
- Develop robust prompt architectures and interaction patterns that improve response quality relevance and safety across diverse generative AI use cases
- Coordinate with engineering and operations teams to integrate generative AI capabilities into existing product management tools and software asset management platforms
- Implement scalable data pipelines and model integration patterns that respect enterprise governance security and compliance standards in a hybrid work environment
- Review solution designs and code modules to ensure maintainability performance observability and alignment with enterprise technical standards
- Guide the evaluation of new generative AI services and frameworks to continuously improve solution quality cost efficiency and time to market
- Collaborate with domain experts in product management and software asset life cycle management to design reusable accelerators templates and knowledge assets that increase delivery speed
- Provide technical mentoring to team members on generative AI concepts implementation patterns prompt engineering practices and quality assurance methods
- Establish monitoring practices and feedback loops that track usage patterns model effectiveness and user satisfaction enabling data informed enhancement cycles
- Drive documentation of solution designs integration patterns and operational procedures to ensure resilient support and smooth knowledge transfer across teams
- Support stakeholder communication by preparing clear technical updates risk assessments and effort estimates that enable informed decision making
- Ensure that delivered solutions contribute to responsible and sustainable technology adoption improving customer value while considering ethical and societal impact
Qualifications
- Demonstrate substantial hands on experience in designing and implementing solutions that use Google BARD ChatGPT and broader generative AI ecosystems in production environments
- Exhibit strong practical knowledge of product management processes for managed accounts and software asset life cycle management across planning acquisition deployment and retirement stages
- Apply solid programming and scripting capabilities along with API integration experience to connect generative AI components with existing enterprise applications and workflows
- Show proficiency in data modeling query design and basic data engineering concepts that support effective preparation of inputs and post processing of outputs for generative AI
- Display familiarity with hybrid work practices agile delivery methods and collaboration tools that support distributed design build and testing activities
- Utilize effective communication and stakeholder engagement skills to explain generative AI concepts limitations and trade offs to both technical and nontechnical audiences
- Leverage analytical and problem solving skills to troubleshoot complex generative AI behaviors optimize performance and improve reliability across multiple use cases
Certifications Required
Preferred certifications include Google Cloud Professional Machine Learning Engineer and equivalent generative AI or machine learning credentials.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Technical LeadEmployement Type: Full timeContact Details:
Company: CognizantLocation(s): Chennai
Keyskills: process life cycle management technical leadership software analytical query google artificial intelligence scripting product management data modeling orchestration framework design stakeholder engagement api agile asset programming communication skills architecture
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