Tech Stack

PythonLangChainAutoGenCrewAISemantic KernelPineconeWeaviateFAISSAWSAzureGCP

About the role

Role Overview

We are seeking an experienced AI Architect with strong expertise in Agentic AI systems to design and implement intelligent, autonomous AI solutions that can reason, plan, and execute complex tasks. This role involves architecting end-to-end AI solutions, guiding engineering teams, and ensuring reliable deployment of agent-based AI systems across enterprise environments.

Key Responsibilities

Design and architect Agentic AI systems capable of autonomous reasoning, decision-making, and task execution
Build and implement multi-agent frameworks that collaborate to solve complex workflows
Define architecture for LLM-powered applications, including prompt orchestration, tool usage, and memory management
Integrate AI agents with enterprise systems, APIs, and data platforms
Lead the design of AI pipelines, orchestration layers, and evaluation frameworks
Establish best practices for AI governance, safety, observability, and monitoring
Collaborate with product managers, data scientists, and engineering teams to translate business requirements into AI-driven solutions
Guide teams in deploying scalable AI solutions on cloud platforms such as Azure, AWS, or GCP
Evaluate and adopt emerging technologies in autonomous AI, reasoning systems, and agent frameworks
Provide technical leadership and mentorship to AI/ML engineers

Required Qualifications

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field
8+ years of experience in software engineering, machine learning, or AI architecture
3+ years of experience working with LLM-based systems and generative AI solutions
Strong experience designing Agentic AI or multi-agent architectures
Proficiency with Python and AI/ML frameworks
Hands-on experience with LLM orchestration frameworks such as LangChain, AutoGen, CrewAI, or Semantic Kernel
Experience working with vector databases (Pinecone, Weaviate, FAISS, etc.)
Knowledge of RAG architectures, prompt engineering, tool integration, and memory management in AI agents
Experience deploying AI workloads in cloud environments (Azure, AWS, or GCP)
Strong understanding of API design, microservices architecture, and distributed systems

About Daman

Daman is a company that specializes in AI solutions, particularly in the domain of Agentic AI systems and enterprise AI architectures.