Technical Project Lead / Architect / GenAI Lead – AWS Cloud & GenAI

Experience : 6-8 years working experience on AWS & GenAI.

We are seeking a highly skilled and visionary Technical Lead to spearhead our next-generation AI initiatives. This role demands deep expertise in Large Language Models (LLMs) integration, cloud-native architecture, and hands-on leadership in delivering scalable GenAI solutions on cloud platforms. You will lead multiple GenAI projects, driving innovation from concept through deployment, ensuring robust, scalable, and efficient AI-powered applications.

Key Responsibilities :

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

Architect and implement 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 to enhance model performance.

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

Integrate and manage LLM APIs such as Azure OpenAI and other emerging models to deliver cutting-edge AI capabilities.

Utilize vector databases (ElasticSearch, Open Search, or similar) for embedding-based search and Retrieval-Augmented Generation (RAG).

Lead model evaluation efforts including output analysis, performance tuning, and quality benchmarking to ensure high standards.

Collaborate with cross-functional teams including data scientists, engineers, and product managers to align AI solutions with business goals.

Mentor and guide technical teams on best practices in GenAI development and cloud architecture.

Stay abreast of the latest advancements in AI, cloud technologies, and LLM frameworks to continuously innovate and improve solutions.

Skills & Experience :

Proven hands-on experience integrating Large Language Models (LLMs) into real-world applications.

Strong programming skills in Python and experience with web frameworks such as FastAPI or Flask.

Expertise in cloud architecture, particularly AWS services including Lambda, SNS / SQS, Step Functions, and event-driven design patterns.

Deep knowledge of LLM APIs, with mandatory experience in Azure OpenAI; familiarity with other models like LLaMA is a plus.

Experience working with vector databases such as ElasticSearch, Open Search, or other vector search engines.

Proficiency in prompt engineering techniques including prompt versioning, optimization, and chain-of-thought design.

Familiarity with LLM frameworks such as LangChain and LlamaIndex.

Experience with embedding-based search and Retrieval-Augmented Generation (RAG) methodologies.

Strong skills in model evaluation, including output analysis, performance tuning, and quality benchmarking.

Excellent leadership, communication, and project management skills.