AI/ML Architecture & System Design

Role - AI/ML Architecture & System Design

Experience - 6- 9 years

Work Mode- Hybrid

Key Responsibilities:

AI/ML Architecture & System Design

Design end-to-end AI/ML and LLM system architecture.

Define scalable architecture for AI applications.

Select appropriate models, frameworks, and infrastructure.

Agentic AI System Architecture

Design complex multi-agent systems.

Implement advanced agent orchestration workflows.

Build planning, reasoning, and memory-enabled agents.

Model Context Protocol (MCP) Architecture

Design MCP server architecture and tool ecosystems.

Standardize enterprise integration using MCP resources.

Define MCP governance and best practices.

Scalable AI Infrastructure

Architect distributed inference pipelines.

Optimize latency, performance, and cost of AI systems.

Design scalable vector database architecture.

Technical Leadership

Mentor junior engineers and guide development standards.

Conduct code reviews and enforce best practices.

Drive technical decision-making.

Production AI Systems

Lead deployment of production-grade AI systems.

Ensure reliability, monitoring, and observability of AI services.

Performance Optimization

Optimize prompts, embeddings, and retrieval strategies.

Improve model performance and cost efficiency.