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Franklin Templeton

Global asset management and investment services

Principal AI Data Strategy Consultant - Relational Database, API Layers

Data EngineeringConfirmed live in the last 24 hours
Full-timeHyderabad, Telangana, IndiaNo salary listed

About the Job

Requirements

  • At least 10 years of experience in data engineering, data platform architecture, or AI infrastructure roles.
  • Proven experience building and operating production-grade data systems, including vector databases such as Pinecone, Weaviate, FAISS, or Milvus; object or blob storage such as S3 or Azure Blob; and relational databases such as PostgreSQL or SQL Server.
  • Strong expertise in API design and implementation using GraphQL and/or REST.
  • Hands-on experience with data pipelines, distributed systems, and cloud platforms such as AWS, Azure, or GCP.
  • Demonstrated experience leading and managing engineering teams.
  • Strong understanding of performance optimization, scalability, and reliability engineering.

Responsibilities

  • Own the end-to-end architecture, implementation, and operation of data platforms supporting AI use cases, including vector databases for embeddings and semantic retrieval; blob or object storage for unstructured data such as documents, transcripts, and multimedia; relational databases using SQL for structured and transactional data; and API layers using GraphQL or REST for data access and orchestration.
  • Ensure all data systems are production-ready, with high availability, scalability, and performance.
  • Define standards for data storage, indexing, retrieval latency, and cost optimization across AI workloads.
  • Lead the design and management of vector database ecosystems supporting retrieval-augmented generation and large language model-driven applications.
  • Define strategies for embedding pipelines, chunking, indexing, and hybrid search using vectors, keywords, and metadata.
  • Optimize retrieval quality, latency, and relevance for AI-driven sales insights.
  • Architect and oversee data pipelines that ingest, transform, and synchronize data across blob storage, warehouses, and vector stores.
  • Establish patterns for multimodal data handling, including text, PDFs, structured data, and customer relationship management records.
  • Ensure interoperability between enterprise data platforms such as Snowflake and Databricks and AI-specific storage systems.
  • Define and implement GraphQL and REST API strategies to expose data services for AI applications such as Sales Assist.
  • Build and govern secure, scalable API layers supporting real-time inference and retrieval workflows.
  • Standardize schema design, versioning, and access control for internal and external consumers.
  • Lead and manage a team of data engineers, platform engineers, and data architects responsible for building and maintaining these systems.
  • Set technical direction, best practices, and coding standards for AI data infrastructure.
  • Drive execution through agile delivery, ensuring timelines, quality, and reliability standards are met.
  • Mentor team members and build a high-performing AI data engineering capability within the organization.
  • Implement data governance, security, and compliance controls across all data platforms.
  • Ensure systems meet regulatory requirements such as SEC, GDPR, and CCPA, as well as internal risk standards.
  • Establish monitoring, observability, and incident response practices for data pipelines and storage systems.
  • Deliver a robust, scalable, and low-latency data platform that powers AI applications in production.
  • Enable high-quality retrieval and data access for Sales Assist and future AI initiatives.
  • Build and lead a strong engineering team capable of sustaining and evolving AI data infrastructure.

Desired Qualifications

  • Experience with large language model applications, retrieval-augmented generation architectures, and semantic search systems.
  • Background in financial services or asset management, particularly sales or client data domains.
  • Familiarity with MLOps, feature stores, and AI platform tooling.
  • Experience with data observability tools and modern orchestration frameworks such as Airflow or Dagster.

About the Company

Franklin Templeton

Global asset management and investment services

Franklin Templeton is an asset management firm that provides a variety of investment products and services to different types of clients, including individual investors and institutions. The company specializes in mutual funds, systematic investment plans (SIPs), and lump-sum investment options, focusing on active investment management. This means they use their research and expertise to make informed investment decisions for their clients. Franklin Templeton stands out from its competitors with a strong distribution network across India, having offices in over 34 cities and collection centers in more than 100 locations, along with a comprehensive digital platform that offers tools for investors. The company's goal is to effectively manage assets for their clients while providing a range of financial services that cater to both retail and institutional investors.

Company size
51-200
Company stage
IPO
Headquarters
San Mateo, CA
Founded
1947

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