Job description

The Data & AI Architect (AWS) is responsible for designing and delivering enterprise‑grade data platforms and AI‑enabled solutions on Amazon Web Services (AWS). This role provides architectural leadership across data engineering, analytics, machine learning, and generative AI, supporting large‑scale cloud modernization and AI‑led transformation programs. The architect partners with Sales, Industry Teams, Cloud Architects, and Delivery to shape scalable, secure, and cost‑effective AWS data and AI architectures that align to client business objectives and TCS’s AI.Cloud and AWS partnership strategy. Key Responsibilities • AWS Data Platform Architecture • Architect end‑to‑end AWS data platforms including data lakes, lakehouse architectures, streaming platforms, and analytics layers. • Design solutions using AWS services such as Amazon S3, Glue, Athena, Redshift, EMR/Spark, Kinesis, Lambda, and managed databases. • Define data ingestion, transformation, and orchestration patterns (batch, streaming, real‑time) for large‑scale enterprise workloads. • Establish data governance, security, and access‑control frameworks aligned with enterprise and regulatory standards. • AI, ML & GenAI Architecture • Design and guide implementation of AI/ML solutions on AWS, including model development, training, deployment, and lifecycle management. • Architect GenAI and agentic AI solutions leveraging AWS services such as Amazon Bedrock, SageMaker, vector databases, and AI orchestration platforms. • Define MLOps and LLMOps patterns for scalable, reliable, and cost‑efficient AI operations. • Ensure Responsible AI practices including security, privacy, explainability, and governance. • Solution Shaping & Client Engagement • Partner with Sales and Solution Architects to shape data and AI solution strategies for proposals and large AWS pursuits. • Translate business requirements into scalable AWS data and AI architectures with clear value articulation. • Engage with client stakeholders (Data Leaders, Analytics Heads, AI Leads) to act as a trusted technical advisor. • Delivery & Architecture Governance • Provide architectural oversight during delivery to ensure adherence to approved designs and best practices. • Mentor data engineers, ML engineers, and platform teams on AWS data and AI patterns. • Support performance tuning, cost optimization (FinOps), and operational readiness of AWS data and AI platforms. • AWS Alliance & Innovation • Align architectures to AWS Well‑Architected Framework and AWS data & AI best practices. • Collaborate with AWS teams on joint innovation initiatives, accelerators, and PoCs. • Contribute to reusable assets, reference architectures, and industry‑specific data & AI offerings for AWS. Required Experience & Qualifications • 10–15+ years of experience in data architecture, analytics, or AI/ML engineering, with strong focus on AWS. • Proven experience designing and delivering enterprise data lakes, analytics platforms, and AI solutions on AWS. • Strong hands‑on knowledge of AWS data services, AI/ML services, and distributed data processing frameworks. • Experience with cloud data migration, modernization, and large‑scale platform implementation. • Ability to translate complex technical architectures into business ou tcomes. Preferred Attributes • Experience with GenAI, LLMs, vector search, and agentic AI patterns on AWS. • Industry experience in Life Sciences, Healthcare, Manufacturing, Financial Services, or Transportation. • Familiarity with Databricks on AWS and third‑party data ecosystems. • AWS certifications such as Data Analytics, Machine Learning, or Solutions Architect. Salary Range: $132,000-$178,250 a year #LI-AK1 </div

Requirements

Must-haves

AWS Data Platform Architecture
Architect end‑to‑end AWS data platforms including data lakes, lakehouse architectures, streaming platforms, and analytics layers.
Design solutions using AWS services such as Amazon S3, Glue, Athena, Redshift, EMR/Spark, Kinesis, Lambda, and managed databases.
Define data ingestion, transformation, and orchestration patterns (batch, streaming, real‑time) for large‑scale enterprise workloads.
Establish data governance, security, and access‑control frameworks aligned with enterprise and regulatory standards.
AI, ML & GenAI Architecture
Design and guide implementation of AI/ML solutions on AWS, including model development, training, deployment, and lifecycle management.
Architect GenAI and agentic AI solutions leveraging AWS services such as Amazon Bedrock, SageMaker, vector databases, and AI orchestration platforms.
Define MLOps and LLMOps patterns for scalable, reliable, and cost‑efficient AI operations.
Ensure Responsible AI practices including security, privacy, explainability, and governance.
Solution Shaping & Client Engagement
Partner with Sales and Solution Architects to shape data and AI solution strategies for proposals and large AWS pursuits.
Translate business requirements into scalable AWS data and AI architectures with clear value articulation.
Engage with client stakeholders (Data Leaders, Analytics Heads, AI Leads) to act as a trusted technical advisor.
Delivery & Architecture Governance
Provide architectural oversight during delivery to ensure adherence to approved designs and best practices.
Mentor data engineers, ML engineers, and platform teams on AWS data and AI patterns.
Support performance tuning, cost optimization (FinOps), and operational readiness of AWS data and AI platforms.
AWS Alliance & Innovation
Align architectures to AWS Well‑Architected Framework and AWS data & AI best practices.
Collaborate with AWS teams on joint innovation initiatives, accelerators, and PoCs.
Contribute to reusable assets, reference architectures, and industry‑specific data & AI offerings for AWS.
Required Experience & Qualifications

Nice-to-haves

Preferred Attributes

Application prep

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Keywords to mirror

aiawsmachine learningml

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