Description

You will design and build GenAI solutions for enterprise applications, focusing on agentic systems, RAG architectures, and LLM optimization.

Responsibilities

• Design and develop generative AI solutions using Python, LLMs, and Agentic AI frameworks.
• Build and optimize agentic systems, including planners, executors, memory components, and multi-agent coordination workflows.
• Implement vector database integrations, semantic search, and API/microservice connections.
• Fine-tune, evaluate, and enhance LLM performance through prompt engineering and hallucination mitigation.
• Define end-to-end AI solution architecture across cloud platforms, ensuring scalability and security.

Required Skills

• 5–8 years of experience in AI/ML engineering, software development, or GenAI solution development.
• Strong hands-on expertise with Python and LLM/GenAI frameworks, specifically LangChain.
• Proven experience implementing Agentic AI systems, including planning, tool use, memory, and multi-agent coordination.
• Demonstrated experience with vector database-based RAG architectures.
• Bachelor’s or master’s degree in computer science, Artificial Intelligence, Data Science, or a related technical field.
• Ability to define end-to-end AI solution architecture across cloud platforms.
• Experience collaborating with cross-functional teams to translate business needs into technical solutions.

Preferred Skills

• Experience mentoring junior engineers.
• Knowledge of Responsible AI practices.

Key Skills

Education

Any Graduate