AI ML Architect
2 days ago
*AI ML Architect*
Location: Bangalore
Experience: 8+ Years
Your Role
As a AI ML Architect, you will own the end-to-end architecture of enterprise-scale AI systems. Youll collaborate across domains to design reference architectures, evaluate technologies, and guide implementation of production-grade GenAI solutions.
In this role, you will:
- Define and own the end-to-end architecture for enterprise-scale GenAI/AI solutions
- Design reference architectures, reusable patterns, and best practices for integrating GenAI into business applications
- Collaborate with domain leaders, data scientists, security experts, and developers to align business requirements with scalable AI architectures
- Select and evaluate LLMs, vector databases, and orchestration frameworks based on performance, compliance, and cost trade-offs
- Architect RAG pipelines, agentic workflows, and multi-agent ecosystems for production-grade deployments
- Ensure security, privacy, and governance frameworks are embedded in AI systems from inception
- Drive adoption of cloud-native AI services (Azure OpenAI, AWS Bedrock) and optimize for scalability and performance
- Guide teams in model lifecycle management, including deployment, monitoring, retraining, and drift handling (MLOps)
- Evaluate and recommend tools, frameworks, and protocols (e.g., MCP, LangChain, LangGraph) for robust interoperability
- Stay ahead of GenAI/AI advancements, regulations, and enterprise adoption trends, and translate them into actionable roadmaps
Your Profile
- Bachelors or Masters degree in Computer Science, Data Science, or related field
- 8+ years of experience in AI/ML architecture and enterprise solution delivery
- Proven expertise in designing scalable GenAI systems and integrating LLMs into business applications
- Strong understanding of RAG pipelines, agentic workflows, and multi-agent orchestration
- Hands-on experience with GenAI frameworks (LangChain, LangGraph, MCP) and vector databases
- Familiarity with cloud-native AI platforms (Azure OpenAI, AWS Bedrock) and MLOps practices
- Deep knowledge of security, privacy, and governance in AI systems
- Excellent collaboration and communication skills across technical and business teams
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