Walk-in || Gen AI Engineer

Gen AI Engineer

Role Summary

We are seeking a highly skilled and visionary Technical Project Lead / Architect / GenAI Lead to spearhead next-generation AI initiatives. This role demands deep expertise in Large Language Models (LLMs), cloud-native architecture, and strong technical leadership to deliver scalable, secure, and high-performance GenAI solutions primarily on AWS cloud platforms.

Key Responsibilities

• Lead the design, development, and deployment of GenAI solutions leveraging Large Language Models (LLMs) on AWS cloud platforms.

• Architect scalable, event-driven cloud-native solutions using AWS Lambda, SNS, SQS, Step Functions, and related services.

• Drive prompt engineering strategies including prompt versioning, optimization, and chain-of-thought design.

• Oversee fine-tuning, embeddings, and conversational flow development for intelligent, context-aware AI applications.

• Integrate and manage LLM APIs including Azure OpenAI and other emerging AI models.

• Utilize vector databases such as ElasticSearch or OpenSearch for Retrieval-Augmented Generation (RAG).

• Lead model evaluation activities including output analysis, performance tuning, and quality benchmarking.

• Collaborate with data scientists, engineers, and product managers to align AI initiatives with business goals.

• Mentor engineering teams and enforce best practices in GenAI development and cloud architecture.

• Stay current with advancements in AI, cloud services, and LLM frameworks to continuously improve solutions.

Required Skills & Experience

• 3+ years of experience in AWS cloud computing and architecture.

• 4+ years of hands-on experience with Generative AI and Large Language Models.

• Strong programming expertise in Python with frameworks such as FastAPI or Flask.

• Proven experience integrating LLMs into real-world, production-grade applications.

• Deep expertise with AWS services including Lambda, SNS/SQS, Step Functions, and event-driven patterns.

• Mandatory experience with Azure OpenAI services; knowledge of LLaMA and other models is a plus.

• Hands-on experience with vector databases like ElasticSearch, OpenSearch, or similar.

• Advanced proficiency in prompt engineering, prompt optimization, and chain-of-thought techniques.

• Experience using LLM frameworks such as LangChain and LlamaIndex.

• Strong understanding of Retrieval-Augmented Generation (RAG) architectures.

• Expertise in model evaluation, performance tuning, and output quality assessment.

• Excellent leadership, communication, and project management skills.

Education

Bachelors or Master’s degree in Computer Science, Engineering, Artificial Intelligence, or a related field.