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Gen AI Architect

Gen AI Architect

LTIMindtreeBengaluru, Karnataka, India
3 days ago
Job description

Job Description : Enterprise AI Architect (for Data & AI practice)

Role Overview :

Drive enterprise-scale AI strategy, architecture, and delivery—enabling agentic, autonomous, and orchestrated AI solutions that align with business outcomes and compliance standards.

Preferred Qualifications :

  • 15-20+ years of total experience in Data & Analytics space using array of ETL and BI tools Designing and architecting data and analytics platform.
  • 4-8+ years of experience in architecting enterprise AI / ML solutions and delivery
  • 1-2+ years of hands-on experience with LLMs, agentic systems, and enterprise AI platforms (ideally in production or pilot environments)

Worked in advanced R&D / innovation teams or any Certifications in Responsible AI, and Advanced ML / NLP would be plus.

Strong stakeholder management and executive communication skills.

Key Responsibilities & Requirements :

  • Architect and deliver transformative AI products across enterprise domains (BFSI, CPTS (non-BFSI Domains)
  • Design scalable, secure AI frameworks —from concept to production—ensuring ethical and compliant adoption. Lead enterprise LLM / SLM strategy.
  • Mobilize cross-functional teams to accelerate AI innovation and drive measurable business impact.
  • Develop and implement agentic systems (multi-agent architectures, marketplaces, orchestration patterns).
  • Champion low / no-code GenAI platforms to democratize AI integration for business and technical users.
  • Align AI strategy with business goals —link technology roadmaps to measurable outcomes.
  • Drive adoption of AI toolkits (e.g. GitHub Co-Pilot, Vibe coding etc. AI bootcamps) —empower employees to integrate AI into daily workflows.
  • Implement MLOps & LLMOps lifecycle management for traditional AI / ML and LLM agentic solutions —optimize performance and governance.
  • Lead data monetization programs —unlock new revenue streams from latent data assets.
  • Automate data engineering SLDC across Data & Analytics —data cleansing, deduplication, and reliability for AI / ML models, automate enterprise data ingestion and analytics.
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