Datagaps - AI Lead/AI Architect

Job location: [{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Anywhere in India/Multiple Locations","addressCountry":"IN"}},{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Others","addressCountry":"IN"}}] Work arrangement: Employment type: FULL_TIME Salary: "" Experience requirements: {"monthsOfExperience":96,"educational":{"credentialCategory":"bachelor degree"}} Education requirements: "" AI Lead / AI Architect JD: Position: AI Lead / AI Architect Experience: 8+ Years Total Experience: 8-13 years Location: India / Hybrid Employment Type: Full-Time Job Summary: We are looking for an experienced AI Lead / AI Architect with a strong background in designing and delivering complex AI-driven data engineering solutions. The ideal candidate must have hands-on experience building enterprise-scale platforms such as Self-Healing ETL Pipelines, Automated Data Lineage Extraction for Legacy Systems, Intelligent Data Quality frameworks, NLP-based automation, and Generative AI solutions, NL to SQL. The candidate should be capable of leading architecture discussions, engaging with business stakeholders, mentoring teams, and driving AI innovation across data platforms. Required Skills: AI & Machine Learning: - Artificial Intelligence (AI) - Machine Learning (ML) - Generative AI - Large Language Models (LLMs) - Retrieval Augmented Generation (RAG) - NLP (Natural Language Processing) - Prompt Engineering - AI Agents & Autonomous Workflows Data Engineering: - ETL/ELT Architecture - Databricks - Snowflake - Data Warehousing - Data Lakehouse Architecture - Apache Spark - Data Governance - Data Quality Frameworks Programming: - Python - SQL - PySpark - REST APIs - Microservices Architecture Cloud Platforms: - Azure / AWS / GCP - Azure OpenAI / OpenAI Services - Cloud-native AI Solutions Mandatory Complex Project Experience: The candidate should have successfully designed or delivered one or more of the following: Self-Healing ETL Pipelines: - AI-driven ETL monitoring and anomaly detection. - Automated root cause analysis. - Self-correcting data pipeline failures. - Predictive failure detection and remediation. Automated Data Lineage Extractor for Legacy Code: - Extraction of lineage from legacy ETL systems (Informatica, DataStage, Ab Initio, PL/SQL, COBOL, SSIS, etc.). - AI/NLP-based parsing of source code and SQL scripts. - Automatic source-to-target mapping generation. - Metadata extraction and lineage visualization. Additional Preferred Enterprise AI Projects: - Natural Language to SQL - Intelligent Data Quality Monitoring - AI-powered Metadata Management - Automated Test Case Generation using AI - Data Catalog & Governance Automation - AI Copilot for Data Engineers - AI-based Impact Analysis Platform - Enterprise Knowledge Assistant using RAG Responsibilities: - Define AI and Data Architecture strategy. - Lead end-to-end design of AI-powered enterprise solutions. - Drive implementation of GenAI, RAG, NLP, and ML initiatives. - Collaborate with business, data, and engineering teams. - Build scalable AI platforms and reusable frameworks. - Establish AI governance, security, and responsible AI practices. - Mentor architects, leads, and development teams. - Conduct architecture reviews and technology evaluations. - Engage with clients and provide technical leadership. Preferred Qualifications: - Bachelor's/Master's in Computer Science, AI, Data Science, or related field. - Certifications in Azure AI, AWS AI/ML, Databricks, Snowflake, or Cloud technologies. - Experience leading enterprise-scale AI transformation programs. - Strong stakeholder management and client-facing experience.