Solution Architect - AI Data Engineering

Description :

Role : Solution Architect - AI Data Engineering

Location : NJ, GA, IL or VA

Job Description :

The AI - Data Engineering Architect in TCS's Americas region is a senior, client-facing role responsible for designing robust, scalable, and secure data architectures that support advanced AI and analytics solutions. This role ensures that enterprise data ecosystems are AI-ready-supporting use cases like retrieval-augmented generation (RAG), multi-agent systems, and real-time inference. You will work across industries (BFSI, Manufacturing, Life Sciences, Telecom, Retail, etc.) to assess current data infrastructure, define end-to-end data pipelines, and architect storage, processing, and integration layers that enable AI models to consume high-quality, timely, and relevant data.

Key Responsibilities :

• Data Architecture Design : Lead the design of conceptual and logical data architectures for AI pipelines, including ingestion, storage, processing, and access layers.
• Enterprise Data Assessment : Evaluate client data ecosystems for AI readiness and recommend modernization strategies.
• Pipeline & ETL Strategy : Define batch, real-time, and streaming data strategies using tools like Spark, Kafka, and cloud-native services.
• Data Storage & Modeling : Architect data lakes, warehouses, vector stores, and feature stores optimized for AI workloads.
• Integration of Heterogeneous Data : Design solutions to combine structured and unstructured data, ensuring consistency and master data alignment.
• Quality, Governance & Security : Embed data validation, lineage tracking, encryption, and compliance (e.g., GDPR, HIPAA) into architecture.
• Scalability & Performance : Design for high throughput and low latency using distributed computing, caching, and cloud auto-scaling.
• Technology Selection & Blueprinting : Recommend tools / platforms and create detailed architecture blueprints and documentation.
• Collaboration with AI Teams : Align data pipelines with AI model requirements, including RAG, feature engineering, and inference needs.
• Prototyping & Validation : Build proof-of-concept pipelines to validate architecture decisions before full-scale implementation.
• Industry-Specific Solutions : Customize architecture for domain-specific needs (e.g., HL7 / FHIR in Healthcare, time-series DBs in Telecom).
• Client Engagement & Thought Leadership : Lead workshops, present data strategies, and advise on governance and operating models.
• Implementation Oversight : Guide and review implementation by engineering teams, ensuring alignment with architectural vision.
• Emerging Trends : Stay current with lakehouse paradigms, data mesh, edge computing, and federated learning patterns.

Qualifications :

Salary Range : $131,750 - $178,250 a year

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