Gen AI Architect

Role: Gen AI Solutions Architect
Experience: 8-13 Years | Location: Straive Global Locations

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