Description

You will architect, scale, and lead the development of Agentic AI systems capable of multi-step reasoning and autonomous action.

This role is hybrid.

Responsibilities

• Analyze legacy systems to design and architect scalable Agentic AI solutions for application modernization.
• Define and standardize reference architectures for container hosting, vector memory systems, and data pipelines.
• Lead the product and technical vision for reusable AI modules, including RAG and hybrid ML/LLM systems.
• Evaluate and select the LLM technology stack based on cost, latency, and scalability.
• Integrate LLM-powered workflows into enterprise systems, ensuring interoperability and high-performance outputs.

Required Skills

• 10+ years of experience in AI/ML engineering, designing production-grade systems.
• 1+ year of experience with Agentic AI systems and Large Language Models.
• Expertise in at least one major cloud platform (AWS, Azure, or GCP).
• Deep proficiency in agentic workflow frameworks and memory architectures, including vector storage.
• Experience working with reasoning, instruction-tuned, safety, and embedding models.
• Extensive experience with LLM evaluation, testing, and benchmarking frameworks.
• Strong hands-on development experience using AI-assisted coding tools.
• Familiarity with RAG and LLM implementations.

Key Skills

Education

Any Graduate