KANINI - AI Architect/Lead

Role OverviewThe AI Architect / AI Lead will be responsible for defining the AI strategy, designing scalable AI/ML architectures, and leading end-to-end implementation of AI solutions across the organization. This role involves deep technical expertise, strategic leadership, and collaboration with cross-functional teams to drive the adoption of AI responsibly and effectively.Key Responsibilities1. AI Strategy & Leadership- Develop and maintain the enterprise AI roadmap aligned with business objectives.- Evaluate new AI technologies, frameworks, and vendors to support innovation.- Define governance frameworks for responsible AI, privacy, security, and ethics.- Lead AI/ML initiatives across multiple business units.2. Architecture & Technical Design- Design scalable, secure, cloud-native AI/ML architectures (Azure AI, AWS, GCP).- Define MLOps frameworks for continuous training, deployment, monitoring, and lifecycle management.- Architect data pipelines, vector databases, LLM orchestration, and retrieval-augmented generation (RAG) systems.- Select appropriate models (LLMs, CV, NLP, Generative AI, predictive analytics) based on business needs.3. Solution Development- Provide technical leadership for building and deploying AI applications.- Work with data scientists, ML engineers, and software teams to deliver production-grade models.- Optimize AI workloads for cost, performance, and scalability.- Oversee integration of AI into products, platforms, and enterprise systems.4. Stakeholder Collaboration- Translate business challenges into AI use cases with measurable outcomes.- Work with product owners, data teams, and business leaders to prioritize initiatives.- Present AI strategy and technical recommendations to executives and leadership teams.5. Risk, Compliance & Responsible AI- Ensure compliance with data protection laws (GDPR, HIPAA, DPDP, etc.).- Create explainability and transparency frameworks for AI decisions.- Implement controls to prevent bias, model drift, and data misuse.Required Skills & ExperienceTechnical Skills- 9-15+ years of overall experience, with 4+ years in AI/ML architecture or leadership roles.- Strong understanding of: o Machine learning, deep learning, NLP, LLMs, RAG, transformers.o Cloud platforms: Azure AI, AWS Sagemaker, or Google Vertex AI.o MLOps tools: MLflow, Databricks, Kubeflow, Airflow, Docker, Kubernetes.o Data engineering: Spark, Databricks, Data Factory, pipelines, ETL/ELT.o Programming: Python, SQL; familiarity with TensorFlow/PyTorch.- Experience designing enterprise-grade AI systems and microservices architectures.Soft Skills- Strong communication and stakeholder-management skills.- Ability to balance technical depth with strategic thinking.- Leadership experience with cross-functional teams.Preferred Qualifications- Master's or bachelor's degree in Computer Science, AI, Data Science, or related fields.- Certifications in cloud (Azure AI Engineer, AWS ML Specialty, etc.).- Experience implementing generative AI and LLM solutions in production.- Background in industry-specific domains (finance, telecom, retail, healthcare, etc.).What You Will Lead- Enterprise AI strategy & architecture- AI platform modernization & MLOps- GenAI and LLM adoption- Cross-functional AI squads- Innovation and PoCs- Responsible AI & governance (ref:hirist.tech)