Role Overview :

We are seeking an experienced AI Platform Architect to design, build, and scale enterprise-grade AI platforms and services. The ideal candidate will possess deep expertise in GenAI architectures, Agentic AI systems, Distributed Computing, RAG frameworks, Model Serving, and Cloud-native technologies.

Key Responsibilities :

- Design and own core AI platform capabilities supporting enterprise-scale AI and GenAI initiatives.

- Architect scalable AI services, retrieval frameworks, knowledge systems, and Agentic AI ecosystems.

- Design and optimize Retrieval-Augmented Generation (RAG) architectures for performance, accuracy, and cost efficiency.

- Lead development of multi-agent and autonomous AI systems using modern Agentic AI design patterns.

- Build and maintain highly scalable model serving platforms for LLMs and AI workloads.

- Drive platform reliability, observability, security, governance, and operational excellence.

- Define engineering standards, architecture principles, coding guidelines, and best practices.

- Design cloud-native AI infrastructure leveraging Kubernetes and modern container orchestration technologies.

- Collaborate with Product Managers, Enterprise Architects, Data Scientists, and Engineering teams to translate business requirements into scalable AI solutions.

- Mentor technical teams and establish a culture of innovation, quality, and continuous improvement.

- Lead AI platform governance, compliance, Responsible AI practices, and risk management initiatives.

- Evaluate emerging AI technologies, frameworks, and tools to ensure platform competitiveness and innovation.

Required Technical Skills :

- Advanced Python Programming

- Distributed Systems Architecture

- GenAI Architecture Design

- Agentic AI Design Patterns

- Retrieval-Augmented Generation (RAG)

- Model Serving & Inference Optimization

- Kubernetes & Container Orchestration

- Cloud Platforms (Azure, AWS, GCP)

- Responsible AI and AI Governance

- LLMOps / MLOps

Preferred Skills :

- LangChain, LangGraph, Semantic Kernel

- Vector Databases (Pinecone, Weaviate, ChromaDB, Azure AI Search)

- API Development (FastAPI, Flask)

- Event-Driven Architectures

- Knowledge Graphs

- AI Security and Compliance

- Monitoring & Observability Platforms

- CI/CD and Infrastructure as Code

Qualifications :

- Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or related field.

- 12+ years of software engineering experience.

- Proven experience building large-scale distributed platforms.

- Hands-on expertise with LLMs, RAG, Agentic AI architectures, and AI deployment platforms.

- Strong experience with cloud-native technologies and Kubernetes.

- Demonstrated success leading technical teams and strategic architecture initiatives.