Ai Architect

Job Description – AI Architect (Generative & Agentic AI) Position : AI Architect

Experience : 10–12 Years

Employment Type : Full-time

About the Role

We are seeking an experienced AI Architect with deep expertise in Generative AI (GenAI) , Agentic AI frameworks , and advanced Python development . The ideal candidate will design, architect, and implement scalable AI solutions leveraging LLMs, multi-agent systems, vector databases, and cloud-native AI platforms . You will collaborate with cross-functional teams to drive innovation, design robust AI architectures, and deliver enterprise-grade AI products.

Key Responsibilities

Architecture & Design

Define end-to-end architecture for GenAI & Agentic AI solutions .

Design scalable and secure AI pipelines including data ingestion, model training, fine-tuning, deployment, and monitoring .

Architect multi-agent AI systems leveraging frameworks like LangChain, AutoGen, LlamaIndex, or similar .

Hands-on Development

Build and optimize AI applications in Python using frameworks such as PyTorch, TensorFlow, Hugging Face Transformers .

Implement and integrate LLMs, embeddings, RAG (Retrieval-Augmented Generation), vector databases (Pinecone, FAISS, Weaviate, Milvus) .

Develop autonomous AI agents for workflow automation, reasoning, and decision-making.

Innovation & Strategy

Evaluate and recommend emerging GenAI & Agentic AI frameworks, tools, and platforms .

Define best practices for prompt engineering, model fine-tuning, safety, compliance, and governance .

Collaborate with stakeholders to align AI solutions with business goals and enterprise architecture .

Leadership & Mentoring

Lead technical discussions and provide architectural guidance to engineering teams.

Mentor data scientists, ML engineers, and software developers in AI best practices.

Collaborate with product managers and business leaders on solution roadmaps.

Required Skills & Experience

10–12 years of experience in software engineering / AI solutions, with at least 4+ years in AI / ML and GenAI .

Strong expertise in Python and AI / ML frameworks ( PyTorch, TensorFlow, Hugging Face ).

Proven experience architecting Generative AI solutions (LLMs, diffusion models, multimodal AI).

Hands-on experience with agent frameworks (LangChain, AutoGen, CrewAI, etc.) for building Agentic AI systems .

Expertise in vector databases (Pinecone, FAISS, Milvus, Weaviate) and RAG architectures .

Strong understanding of cloud platforms (AWS, Azure, GCP) and AI services (Bedrock, Vertex AI, OpenAI APIs).

Knowledge of MLOps practices : CI / CD pipelines, monitoring, observability, and governance for AI systems.

Experience with scalable distributed systems , API integration, and microservices architecture.

Familiarity with data privacy, security, and ethical AI practices .

Familiarity working with healthcare domain would be an added advantage

Preferred Skills

Experience with multi-modal GenAI models (text, vision, speech).

Knowledge of enterprise AI platforms (Databricks, Snowflake, Azure AI, AWS SageMaker).

Contributions to open-source AI projects .

Strong background in solution architecture and enterprise AI adoption strategies .

Education

Bachelor’s / Master’s degree in Computer Science, AI / ML, Data Science, or related field .

Certifications in AI / ML, cloud architecture, or Generative AI are a plus.