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 life cycle 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 architecture 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
- 5+ 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
