Piramal Realty
Website:
piramalrealty.com
Job details:
Purpose Of The Job
Lead the end-to-end design, development, and optimisation of enterprise data platforms while driving the adoption of generative AI solutions across the organisation. This role combines deep expertise in modern data engineering, cloud-based architectures, and advanced AI/LLM technologies to build scalable, secure, and intelligent data-driven systems.
Key Roles And Responsibilities
- Data Engineering & Architecture
- Design and implement robust data pipelines using modern tools (e.g., Spark, Databricks, Kafka, Airflow).
- Build and maintain scalable ETL/ELT frameworks for structured, semi-structured, and unstructured data.
- Own the architecture of data lakes, data warehouses (Snowflake/BigQuery/Redshift), and real-time streaming systems.
- Optimise data models for analytics, ML workloads, and business intelligence use cases.
- Ensure high data quality, governance, lineage, security, and compliance with organisational standards.
- Generative AI & Machine Learning
- Develop, fine-tune, and deploy LLM-based solutions (e.g., GPT, Llama, Claude models) for business automation, insights generation, and decision support.
- Build retrieval-augmented generation (RAG) architectures and vector databases (Pinecone, FAISS, Chroma).
- Create custom AI agents for internal workflows—credit analysis, due diligence, underwriting support, customer interactions, etc.
- Lead experimentation with multimodal AI (text, image, document intelligence).
- Collaborate with business teams to convert functional problems into scalable AI-driven solutions.
- Platform & Infrastructure
- Deploy and manage AI and data workloads on cloud platforms (AWS / Azure / GCP).
- Implement MLOps & LLMOps pipelines for CI/CD, automated testing, and monitoring of AI models.
- Integrate AI systems with enterprise applications and APIs for seamless workflow automation.
- Evaluate, adopt, and integrate new AI tools, frameworks, and model providers.
- Stakeholder & Cross-Functional Collaboration
- Work closely with analytics, business, product, and engineering teams to deliver impactful AI and data initiatives.
- Translate complex technical concepts into clear business insights.
- Mentor junior engineers and contribute to building an internal AI/Data capability.
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