Senior AI Engineering Lead

EdgeVerve; Bengaluru; On-site; INR 4,200,000 - 6,200,000; Full time

Job summary

EdgeVerve seeks an experienced AI Platform Architect to design, build, and scale enterprise-grade AI platforms and services. The role emphasizes GenAI architectures, agentic AI systems, RAG, and model serving across enterprise environments.

You will drive reliability, security, and governance while mentoring teams and collaborating with product and architecture stakeholders to deliver innovative AI solutions.

Qualifications

• 12+ years of software engineering experience.
• Hands-on with LLMs, RAG, Agentic AI architectures, and AI deployment platforms.
• Strong experience with cloud-native technologies and Kubernetes.
• Led technical teams and strategic architecture initiatives.

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 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.

Skills

Advanced Python

Agentic AI Design Patterns

RAG

Model Serving & Inference Optimization

Responsible AI & AI Governance

LLMOps / MLOps

Education

Bachelor's/Master's in CS/Engineering/AI or related

Tools

LangChain

LangGraph

Semantic Kernel

FastAPI

Flask

Knowledge Graphs

Job description

Experience :12+ Years (with 5+ years in AI/ML Platform Engineering and GenAI Solutions)

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. This role will be responsible for defining AI engineering standards, driving platform reliability and security, mentoring engineering teams, and collaborating with product and architecture stakeholders to deliver innovative AI solutions.

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
• Agentic AI Design Patterns
• Retrieval-Augmented Generation (RAG)
• Model Serving & Inference Optimization
• Responsible AI and AI Governance
• LLMOps / MLOps

Preferred Skills

• LangChain, LangGraph, Semantic Kernel
• API Development (FastAPI, Flask)
• 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.
• 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.