Description

Own end-to-end architecture and delivery of Generative AI solutions, including RAG pipelines, embeddings, and vector database systems.

This role is on-site.

Responsibilities

• Lead hands-on design and implementation of GenAI frameworks using LangChain and LangGraph.
• Drive architecture and critical design decisions for scalable, distributed systems and microservices.
• Guide engineering teams on best practices, code quality, and delivery standards.
• Collaborate on cloud-native solution design across AWS, Azure, or GCP platforms.
• Ensure solutions meet non-functional requirements such as performance, scalability, security, and reliability.

Required Skills

• 13+ years of experience in software engineering with a focus on AI/ML or GenAI systems.
• Strong hands-on experience in building and deploying Generative AI solutions.
• Expertise in RAG architectures, embeddings, and vector databases.
• Experience with frameworks such as LangChain, LangGraph, TensorFlow, or PyTorch.
• Strong background in distributed systems and scalable architecture design.
• Hands-on experience with cloud platforms (AWS, Azure, or GCP).
• Experience with microservices, CI/CD pipelines, and Infrastructure as Code (IaC).
• Strong understanding of security, compliance, and governance in enterprise environments.
• Proven leadership experience in managing and mentoring engineering teams.

Key Skills

Education

Any Graduate