Posted on: 12/03/2026
Role : Gen AI Solutions Architect.
Experience : 10- 15 Years
Overview :
As a Solutions Architect, you will lead the design and implementation of enterprise-grade Generative AI solutions.
You will bridge the gap between complex data ecosystems and cutting-edge LLM applications, ensuring scalability, security, and measurable ROI.
Key Responsibilities :
- Architectural Leadership : Design end-to-end Gen AI architectures, including RAG (Retrieval-Augmented Generation) frameworks, Agentic workflows, and Multi-modal systems.
- Data Backbone : Build and oversee robust data pipelines that feed AI models, leveraging your background in Big Data and Cloud Data Warehousing.
- Model Lifecycle : Manage LLM selection, prompt engineering, fine-tuning strategies, and deployment using MLOps/LLMOps best practices.
- Enterprise Integration : Ensure AI solutions integrate seamlessly with existing enterprise APIs, microservices, and security protocols.
- Stakeholder Management : Translate complex technical AI concepts into business value for C-suite stakeholders.
Technical Skills Required :
- Gen AI : LangChain, LlamaIndex, OpenAI/Anthropic SDKs, AgenticAI, Vector DBs (Milvus, Pinecone, Weaviate).
- Data Engineering : Apache Spark, Python, SQL, ETL/ELT, Databricks, or Snowflake.
- Cloud : AWS (Bedrock/SageMaker), Azure (OpenAI Service), or GCP (Vertex AI).
- DevOps : Docker, Kubernetes, and CI/CD for AI.
Only Immediate joiners.
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