CA
Full time
🤖 AI / ML
Cloud, Data Science & AI Architect at Capgemini
Listed by DevShelfHub
Bangalore, Karnataka, India
Hybrid
Mid-level · 2–5 yrs
About the Role
Capgemini is hiring a Cloud, Data Science & AI Architect in Bangalore to define and own end-to-end architecture for enterprise cloud, data, analytics, machine learning, and Generative AI platforms. Capgemini is a global business and technology transformation partner with 340,000 team members in more than 50 countries.
This is a permanent role for experienced professionals under Capgemini Invent.
What you'll do
- You will architect and lead scalable cloud and data platforms supporting digital transformation and AI initiatives.
- Define and own end-to-end architecture for enterprise cloud, data, analytics, ML, and GenAI platforms
- Design cloud-native, distributed, and microservices-based solution architectures
- Define scalable data architectures for batch, streaming, event-driven, and real-time processing
- Design enterprise data platforms covering ingestion, transformation, storage, governance, analytics
- Architect data-lake, data-warehouse, and lakehouse solutions
- Lead ML solution architecture including model development, deployment, monitoring, and lifecycle management
- Define MLOps architectures using MLflow, Azure ML, SageMaker, or equivalent
- Design Generative AI solutions with LLMs, RAG, vector databases, prompt engineering, and agent frameworks
- Design streaming and real-time analytics solutions
- Establish architecture standards for cloud engineering, DataOps, MLOps, DevSecOps, and governance
- Conduct architecture assessments, technology evaluations, and proofs of concept
What we're looking for
- Extensive experience designing scalable enterprise solutions on AWS, Azure, or GCP
- Deep expertise in enterprise data platforms: ingestion, processing, storage, governance, analytics
- Experience with data-lake, data-warehouse, and lakehouse architecture patterns
- Hands-on with Spark, Databricks, Snowflake, BigQuery, Synapse, Fabric, or equivalent
Skills & Technologies
Required
Extensive experience designing scalable enterprise solutions on AWS, Azure, or GCP
Deep expertise in enterprise data platforms: ingestion, processing, storage, governance, analytics
Experience with data-lake, data-warehouse, and lakehouse architecture patterns
Hands-on with Spark, Databricks, Snowflake, BigQuery, Synapse, Fabric, or equivalent
Experience with streaming platforms: Kafka, Kinesis, Pulsar, Flink, Spark Streaming
ML and AI lifecycle management including MLOps platforms and practices
Generative AI applications using LLMs and RAG architectures
Agent-based solutions using LangChain, LangGraph, Semantic Kernel, or equivalent
Benefits & Perks
- Health Insurance
- Flexible Leave Policy
- Learning Budget
- EPF / NPS
Why This Role is Good for Experienced Professionals
- This architect role offers end-to-end ownership of cloud, data, analytics, ML, and Generative AI platform architecture at enterprise scale.
- Define end-to-end architecture for enterprise cloud, data, analytics, ML, and GenAI platforms
- Design cloud-native, distributed, and microservices architectures on AWS, Azure, or GCP
- Architect data-lake, data-warehouse, and lakehouse solutions using Databricks, Snowflake, Fabric, BigQuery, Synapse
- Lead MLOps architectures using MLflow, Azure ML, Amazon SageMaker
- Design Generative AI solutions with LLMs, RAG, vector databases, and agent-based frameworks
- Architect streaming solutions using Kafka, Kinesis, Pulsar, Flink, Spark Streaming
- Establish DataOps, MLOps, DevSecOps, and Infrastructure-as-Code practices
- Ensure compliance with security, privacy, regulatory, data sovereignty, and responsible AI requirements
About Capgemini
Capgemini delivers cutting-edge transformation solutions with market leading capabilities in AI, generative AI, cloud, and data across industries including energy, utilities, manufacturing, and rail.
- Industry
- Technology
- Company Size
- 500+
- Website
- capgemini.com
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Job Details
- Type
- Full time
- Level
- Mid-level
- Experience
- 2–5 years
- Location
- Bangalore, Karnataka, India
- Work Mode
- Hybrid
- Category
- AI / ML
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