Epergne Solutions
Website:
epergnesolutions.com
Company:
https://www.linkedin.com/company/epergne-solutions
Seniority: Not Applicable
Industries: IT Services and IT Consulting
Job details:
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.
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