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Location: Hyderabad
Experience: 15+ Years
Employment Type: Full-time
We are seeking a highly technical and visionary Data & AI/ML Architect with 15+ years of proven experience in leading enterprise-scale data modernization and AI transformation programs. The ideal candidate will have deep expertise in modern data architectures, advanced analytics, Generative AI (GenAI), and Agentic AI frameworks, with the ability to define strategy, design architectures, and oversee delivery across complex, multi-cloud enterprise ecosystems.
Define and implement enterprise-wide data architecture frameworks, standards, and governance models using frameworks such as DAMA.
Lead modernization initiatives involving cloud-native data platforms, data lakes, data warehouses, and data mesh architectures.
Ensure architectures are AI-ready for real-time analytics, semantic search, and GenAI-powered insights.
Architect AI/ML solutions leveraging machine learning, deep learning, NLP, GenAI, and Agentic AI for enterprise use cases.
Design RAG (Retrieval-Augmented Generation) and vector database solutions to enable contextual, domain-specific GenAI applications.
Implement Agentic AI frameworks to orchestrate autonomous AI agents capable of decision-making, task planning, and multi-step reasoning.
Integrate AI capabilities into enterprise workflows for predictive, prescriptive, and autonomous process automation.
Lead solution design from discovery to deployment, ensuring alignment with business objectives, performance KPIs, and compliance requirements.
Oversee large-scale data migration, integration, and transformation initiatives from legacy systems to modern cloud data platforms.
Drive MLOps and AIOps adoption for continuous delivery and automation of AI/ML and GenAI models.
Evaluate and recommend modern data, analytics, and AI platforms (e.g., Azure Synapse, Databricks, Snowflake, AWS Redshift, GCP BigQuery, OpenAI, Anthropic, LangChain).
Champion GenAI adoption through safe, secure, and compliant implementations, including prompt engineering, fine-tuning, and multi-agent orchestration.
Advocate for AI governance frameworks ensuring transparency, explainability, and ethical AI practices.
Partner with CDOs, CIOs, and business leaders to align architecture with business goals.
Mentor engineering teams, data scientists, and AI specialists in GenAI and Agentic AI development best practices.
15+ years in data engineering, analytics, and AI/ML solution architecture.
Proven track record of enterprise-scale data modernization programs in multi-cloud environments (Azure, AWS, GCP).
Deep expertise in:
Modern Data Platforms: Data lakes, data warehouses, data mesh, data fabric.
ETL/ELT & Data Integration: Azure Data Factory, Informatica, Talend, dbt.
Databases & Storage: Snowflake, Databricks, Synapse, BigQuery, Redshift, SQL/NoSQL.
AI/ML Frameworks: TensorFlow, PyTorch, Scikit-learn, Hugging Face, LangChain, LlamaIndex.
GenAI & Agentic AI: LLM architectures, prompt engineering, fine-tuning, RAG pipelines, autonomous multi-agent orchestration.
Cloud AI Services: Azure OpenAI, AWS Bedrock, GCP Vertex AI.
Strong understanding of data governance, compliance, and security (GDPR, HIPAA, SOC2, ISO27001).
Experience with streaming data architectures (Kafka, Kinesis, Event Hubs).
Experience with multi-modal AI (text, image, audio, video processing).
Exposure to edge AI and IoT data processing pipelines.
Contributions to open-source GenAI, Agentic AI, or data engineering projects.
Strategic thinker with a hands-on technical approach.
Ability to translate business vision into scalable AI-driven data architectures.
Proven leadership in cross-functional, global teams.
Strong executive presentation and stakeholder management skills.
Thanks,
Anusha
Talent Acquisition Team
Job ID: 149621501
Skills:
control management , Microsoft Azure, AI Foundry, Copilot Studio, Microsoft Tech Suite, Innovation
Skills:
Data Architecture, Typescript, Encryption, Javascript, Python, AWS, Gcp, Data Privacy, Azure, Meta, metadata standards, Responsible AI frameworks, RAG and knowledge systems, Security, bias mitigation, AI reference architectures, Google, cloud-native systems, explainability, workflow orchestration, fairness, taxonomies, Anthropic, secure connectivity, AI architecture, Compliance, semantic caching, CI CD pipelines, end-to-end observability, OpenAI, RAG multi-agent systems
Skills:
SIP-based handoff, SIP telephony routing, Genesys Cloud CX, BYOC Cloud, RAG, Sierra.ai, LLM orchestration, enterprise API integration
Skills:
Kafka, Tensorflow, Pytorch, Python, Kubernetes, embedding pipelines, feature stores, Generative AI, data pipelines, scikit-learn, RAG systems, LLMOps, MLflow, vector databases, event streaming systems, SageMaker, Agentic AI, Kubeflow, model lifecycle management, ML frameworks, fine-tuning techniques
Skills:
snowflake , BigQuery, Sql, Deep Learning, Tensorflow, Azure ML, Pytorch, Docker, XGBoost, Spark, Databricks, Python, Kubernetes, scikit-learn, Custom Transformer Architecture, LightGBM, MLflow, SageMaker, DVC, Vertex AI, HuggingFace Transformers
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