Principal Engineer – AI

Epergne Solutions; Delhi; On-site; INR 1,400,000 - 2,100,000; Full time

Job summary

Epergne Solutions seeks a Principal Engineer – AI Research to lead the architecture, design, and delivery of production-grade AI platforms and agentic AI systems. The role focuses on scalable and secure AI infrastructure for Generative AI, multimodal AI, and autonomous AI across on‑premise and cloud environments.

You will design end-to-end architectures for agentic AI systems, build scalable platforms for distributed training and deployment, and drive best practices in MLOps, observability, and

Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Artificial Intelligence, Software Engineering, or related field.
• 10–15 years of experience in software engineering, AI platforms, ML infrastructure, or distributed systems.
• Proven experience designing and delivering large-scale production systems and AI platforms.
• Experience leading technical architecture, engineering standards, and cross-functional delivery initiatives.

Responsibilities

• Design and implement end-to-end architectures for agentic AI systems, Generative AI platforms, RAG pipelines, and AI inference workflows.
• Build scalable AI platforms supporting distributed training, model deployment, and enterprise integration.
• Optimise system performance, latency, throughput, GPU utilisation, and infrastructure costs.
• Lead debugging, production incident resolution, performance tuning, and reliability improvements.
• Develop reusable AI frameworks, SDKs, APIs, connectors, and CI/CD templates.
• Implement observability, monitoring, logging, tracing, and operational dashboards.
• Establish engineering standards, architecture governance, testing frameworks, and controlled release processes.
• Collaborate with research, product, data, and platform teams to translate AI research into production-ready systems.
• Mentor engineering teams and drive best practices in software engineering, MLOps, and AI platform development.

Skills

AI architecture

Distributed systems

Cloud platforms

Generative AI

LLM deployment

RAG systems

agentic AI frameworks

AI orchestration

Python

MLOps

LLMOps

Containerisation

Kubernetes

CI/CD

Monitoring

Infrastructure automation

Distributed training

GPU optimisation

Vector databases

Real-time inference

Debugging

Performance optimisation

Reliability engineering

Leadership

Mentoring

Education

Bachelor/Master/PhD in CS/AI

Job description

We are seeking a Principal Engineer ? AI Research to lead the architecture, design, and delivery of production-grade AI platforms and agentic AI systems. This is a hands-on technical leadership role focused on building scalable, secure, and high-performance AI infrastructure that enables the deployment of advanced Generative AI, multimodal AI, and autonomous AI solutions across on-premise and cloud environments.

Job Role

Principal Engineer ? AI

Job Location

Bengaluru, India

Experience

10-15 Years

Role Summary

We are seeking a Principal Engineer ? AI Research to lead the architecture, design, and delivery of production-grade AI platforms and agentic AI systems. This is a hands-on technical leadership role focused on building scalable, secure, and high-performance AI infrastructure that enables the deployment of advanced Generative AI, multimodal AI, and autonomous AI solutions across on-premise and cloud environments.

Key Responsibilities

• Design and implement end-to-end architectures for agentic AI systems, Generative AI platforms, RAG pipelines, and AI inference workflows.
• Build scalable AI platforms supporting distributed training, model deployment, and enterprise integration.
• Optimise system performance, latency, throughput, GPU utilisation, and infrastructure costs.
• Lead debugging, production incident resolution, performance tuning, and reliability improvements.
• Develop reusable AI frameworks, SDKs, APIs, connectors, and CI/CD templates.
• Implement observability, monitoring, logging, tracing, and operational dashboards.
• Establish engineering standards, architecture governance, testing frameworks, and controlled release processes.
• Collaborate with research, product, data, and platform teams to translate AI research into production-ready systems.
• Mentor engineering teams and drive best practices in software engineering, MLOps, and AI platform development.

Required Skills

• Strong expertise in AI system architecture, distributed systems, cloud platforms, and scalable backend engineering.
• Experience with Generative AI, LLM deployment, RAG systems, agentic AI frameworks, and AI orchestration platforms.
• Proficiency in Python and modern software engineering practices.
• Experience with MLOps/LLMOps, containerisation, Kubernetes, CI/CD, monitoring, and infrastructure automation.
• Knowledge of distributed training, GPU optimisation, vector databases, and real-time inference systems.
• Strong debugging, performance optimisation, and reliability engineering skills.
• Excellent technical leadership, collaboration, and mentoring abilities.

Qualifications & Experience

• Bachelor?s, Master?s, or PhD in Computer Science, Artificial Intelligence, Software Engineering, or a related field.
• 10?15 years of experience in software engineering, AI platforms, machine learning infrastructure, or distributed systems.
• Proven experience designing and delivering large-scale production systems and AI platforms.
• Experience leading technical architecture, engineering standards, and cross-functional delivery initiatives.

Preferred Attributes

• Hands-on principal-level engineering expertise.
• Strong understanding of security, governance, observability, and production operations.
• Experience building reusable engineering platforms and developer tooling.
• Ability to translate advanced AI research into reliable enterprise-grade products.