Principal Engineer – AI

Epergne Solutions; Bengaluru; On-site; INR 4,200,000 - 6,400,000; Full time

Job summary

Epergne Solutions in Bengaluru, India seeks a Principal Engineer – AI Research to lead the architecture, design, and delivery of production-grade AI platforms and agentic AI systems. This hands-on technical leadership role focuses on scalable, secure, high-performance AI infrastructure for Generative AI, multimodal AI, and autonomous AI solutions across on-premise and cloud environments.

The role requires 10-15 years of software engineering and AI platform experience, with expertise in

Qualifications

• Experience designing and delivering large-scale production AI platforms.
• Strong expertise in AI platforms and agentic AI systems.
• Hands-on principal-level engineering with security and observability focus.

Responsibilities

• Design end-to-end architectures for AI systems and pipelines.
• Lead development of scalable AI platforms and inferencing workflows.
• Improve system latency, throughput, and GPU utilisation while controlling costs.
• Mentor teams and establish engineering standards and CI/CD templates.
• Collaborate with research, product, data, and platform teams to ship production-grade solutions.

Skills

AI system architecture

Distributed systems

Cloud platforms

Python

MLOps/LLMOps

Performance optimisation

Technical leadership

Education

Bachelors, Masters, or PhD in CS/AI/SE

Tools

Kubernetes

CI/CD

Containerisation

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.