Architect – AI & Data Engineering (EXL)
| Location |
Pune |
| Experience |
10–12 Years |
Role Overview
We are seeking an experienced Architect – AI & Data Engineering to lead
the design, development, and deployment of enterprise-scale AI and data
platforms. The ideal candidate will possess deep expertise in Agentic AI,
GPT-based solutions, modern data engineering architectures, and cloud-native
data platforms. This role will be responsible for architecting intelligent
systems that combine large language models, multi-agent orchestration
frameworks, and scalable data ecosystems to drive business transformation and
operational efficiency.
Key Responsibilities
-
Design and implement enterprise-grade Agentic AI solutions leveraging
GPT-based models.
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Architect and develop multi-agent AI systems using LangGraph and related
orchestration frameworks.
-
Define AI architecture standards, governance frameworks, and best practices
for Generative AI deployments.
-
Lead the integration of LLMs, RAG frameworks, vector databases, and
agent-based architectures.
-
Design and implement end-to-end data engineering solutions utilizing
Microsoft Fabric, Azure Databricks, and Snowflake.
-
Architect scalable ETL/ELT pipelines and modern data platforms.
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Drive data platform modernization initiatives including lakehouse
architectures and real-time data processing.
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Develop and oversee API-based integrations between AI platforms, enterprise
applications, and cloud services.
-
Collaborate with business and technology stakeholders to deliver scalable
solutions.
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Provide technical leadership, architecture governance, mentoring, and
best-practice adoption.
-
Establish monitoring, evaluation, and optimization frameworks for AI
systems.
-
Lead architecture reviews, solution design workshops, and proof-of-concept
initiatives.
Required Experience & Skills
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10–12 years of experience in Data Engineering, Analytics, AI, or Cloud
Architecture roles.
-
Hands-on experience designing and deploying Agentic AI solutions using
GPT-based models and Azure OpenAI.
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Strong expertise in LangGraph and multi-agent orchestration frameworks.
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Experience with RAG architectures, vector databases, embeddings, prompt
engineering, and AI workflow automation.
-
Extensive experience with Microsoft Fabric, Azure Databricks, and Snowflake.
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Strong understanding of Data Lake, Lakehouse, Data Warehouse, and Real-Time
Streaming architectures.
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Advanced programming skills in Python and PySpark.
-
Proven experience designing APIs, microservices, and enterprise integration
solutions.
-
Strong knowledge of Azure cloud services and modern data engineering
ecosystems.
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Experience with CI/CD, DevOps practices, Docker, Kubernetes, and MLOps
frameworks.
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Strong understanding of data governance, security, privacy, and compliance
requirements.
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Experience leading architecture discussions and cross-functional technical
teams.
Preferred Qualifications
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Experience with LangChain, CrewAI, AutoGen, Semantic Kernel, or similar
frameworks.
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Exposure to vector databases such as Pinecone, Weaviate, Chroma, or Azure AI
Search.
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Experience implementing enterprise AI governance and responsible AI
frameworks.
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Familiarity with machine learning workflows and advanced analytics
ecosystems.
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Experience working on large-scale enterprise digital transformation
programs.
Education
Bachelor’s or Master’s degree in Computer Science, Information Technology,
Data Science, Engineering, or a related discipline.