Principal Python GenAI Engineer

Job Description

We are seeking a highly experienced Principal Engineer GenAI with proven experience in software development and system maintenance.The ideal candidate will have a strong background in N-tiered applications, multi-tier architecture, and scalable system design while leveraging GenAI technologies to develop innovative solutions.

Responsibilities

• Accountable for leading application development supporting business objectives while demonstrating independence in software development lifecycle phases from concept and design to testing.
• Lead new and existing applications along with enhancements to applications and infrastructure.
• Perform hands-on coding while designing and architecting data processing and analytics solutions.
• Serve as a liaison to internal customers, research groups and various business support areas.
• Provides technical guidance to junior programmers and other software engineers.
• Ability to troubleshoot and maintain mid-level to complex applications.

Qualifications

• 8+ years of proven experience in software development and system maintenance.
• Lead the implementation of GenAI systems, ensuring they are robust, secure, and performant is must.
• Leverage advanced knowledge of Python open-source software stack such as Fast API or Flask, Django or Django Rest
• Ability to learn and adapt to continuously changing technology.
• Should have AWS experience preferably.
• Demonstrated experience with N-tiered applications and multi-tier architecture.
• Highly experienced at developing elegant-yet-simple systems using best practices and design patterns.
• Highly experienced with multi-threading, memory management, networking, I/O concepts, and performance aspects of common classes and algorithms.
• Develop and design scalable and efficient GenAI solutions tailored to our requirements
• Design, develop, and deploy GenAI solutions using AWS Bedrock services, including model selection, fine-tuning, and integration with enterprise applications.
• Experience working with RAG technologies and LLM frameworks, LLM model registries (Hugging Face), LLM APIs, embedding models, and vector databases.
• Experience working on all aspects of enterprise-scale implementation for AI/GenAI solutions, including architecture, design, security, infrastructure, MLOP's