AI Technical Lead

Overview

• Identify AI opportunities across products, software development, QA, DevOps, support, sales, finance, HR, and operations.
• Establish responsible AI practices covering security, privacy, compliance, explainability, auditability, and human oversight.
• Present AI adoption progress, effectiveness and risks to executive leadership.
• Lead AI research, experimentation, prototyping, proof-of-concepts, and MVP development.
• Evaluate emerging AI technologies, LLMs, frameworks, tools, platforms, and cloud AI services.
• Build reusable AI components, prompt libraries, knowledge bases, automation templates, and internal accelerators.
• Convert R&D outcomes into production-ready product features, internal tools, or strategic business capabilities.
• Act as the company’s AI champion and drive AI adoption across all departments.
• Conduct awareness sessions, training programs, workshops, and use-case discovery sessions.
• Help teams use AI to improve productivity, documentation, development, testing, support, analysis, and decision-making.
• Create internal AI usage guidelines, prompt engineering guides, best practices, and safe-use policies.
• Track adoption, productivity gains, quality improvements, and process efficiencies.
• Lead the design and implementation of AI-powered features within the company’s products.
• Build and deploy Agentic workflows, copilots, chatbots, intelligent assistants, smart search, document intelligence, analytics, and automation features.
• Work with product, architecture, development, QA, DevOps, and business teams to deliver secure, scalable, and reliable AI solutions.
• Design AI solution architectures using LLMs, RAG pipelines, vector databases, APIs, orchestration frameworks, cloud services, and monitoring tools.
• Support AI-related product demos, client presentations, proposals, and solution positioning.