- Hands-on experience with AI Development fundamentals. Building and testing intelligent systems, from rule-based models to neural networks.
- Large Language Models (LLMs): Explore how LLMs work. Learn how to fine-tune them, evaluate their performance, and integrate them into products and services.
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Collaboration & Delivery: Work with Product Owner, Developers, Quality Engineers and UX Designers to deliver the Virtual Companion. Contribute to sprint planning, code reviews and documentation.
AI/ML Literacy: A strong grasp of LLM fundamentals, including tokens, temperature, top-p, and context windows.
Prompt Engineering & Evaluation: Design, optimize, and evaluate prompts to improve AI behavior, reasoning, and response quality.
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Operational Governance: Maintaining operational governance of AI solutions by managing production stability, performance thresholds, compliance requirements, risk controls, and responsible AI practices.
Stakeholder Collaboration: Collaborating with application operations, platform operations, engineering, architecture, and business stakeholders to design, deploy, and continuously improve agent-based solutions.
AI Solution Design: Experience with designing scalable, user-centric AI capabilities that automate workflows and augment decision-making.
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Assist in developing AI solution architectures, HLD/LLD, data-flow designs, sizing, BoM, costing, implementation roadmaps and proposals for RFI/RFP/tenders.
Design solutions across generative AI, LLMs, machine learning, computer vision, NLP, intelligent automation, conversational AI, agents and predictive analytics.
Architect enterprise AI platforms across public, private and hybrid cloud, including data platforms, training, fine-tuning, inference, RAG, vector databases, APIs and MLOps/LLMOps.
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Credit & Risk Intelligence: Lead development of AI/ML models for credit scoring, lease default prediction, and portfolio risk analytics—leveraging both traditional financial data and alternative data sources .
Process Automation: Deploy NLP and generative AI solutions to automate lease document review, contract analysis, and compliance checking; streamline RFP responses and lease negotiation workflows .
Commercial Optimization: Build predictive analytics for lease pricing optimization (NPV/NER modeling), tenant retention scoring, and market intelligence—analyzing comparable properties, pricing trends, and competitive positioning .
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Assist in developing AI solution architectures, HLD/LLD, data-flow designs, sizing, BoM, costing, implementation roadmaps and proposals for RFI/RFP/tenders.
Design solutions across generative AI, LLMs, machine learning, computer vision, NLP, intelligent automation, conversational AI, agents and predictive analytics.
Architect enterprise AI platforms across public, private and hybrid cloud, including data platforms, training, fine-tuning, inference, RAG, vector databases, APIs and MLOps/LLMOps.
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Safety & Bias Auditing: Lead "Red Teaming" sessions to identify potential biases, toxic content, or PII (Personally Identifiable Information) leaks.
Regression Testing: Manage the evaluation of model performance across different versions to ensure seamless upgrades and stability.
Collaboration & Delivery: Work with Product Owner, Developers, AI Engineers and UX Designers to deliver the Virtual Companion. Contribute to sprint planning, code reviews and documentation.
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