Description

Lead end-to-end product development for AI-driven platforms, owning system architecture, RAG implementation, and hands-on engineering.

This role is on-site.

Responsibilities

• Design and implement RAG architectures, including data ingestion, embedding pipelines, vector databases, and LLM orchestration.
• Build scalable AI/ML solutions and microservices, translating business requirements into technical product designs.
• Develop APIs and cloud-native applications supporting AI workloads while ensuring scalability, performance, and cost optimization.
• Implement MLOps practices for model deployment, monitoring, evaluation, and continuous improvement.
• Drive rapid prototyping and establish feedback loops to improve AI system accuracy and user satisfaction.

Required Skills

• 8+ years of software engineering experience, with 3+ years focused on AI/ML or data-driven applications.
• Proficiency in Python and experience with ML/AI frameworks such as TensorFlow or PyTorch.
• Strong hands-on experience designing RAG-based systems, vector databases, embeddings, and semantic search.
• Experience with cloud platforms (AWS, Azure, or GCP) and distributed system design.
• Strong understanding of APIs, microservices, and product design thinking.
• Familiarity with data pipelines, vector indexing, and retrieval optimization techniques.

Preferred Skills

• Experience building advanced RAG pipelines with LangChain, LlamaIndex, or similar frameworks.
• Familiarity with prompt engineering, fine-tuning, and LLM evaluation techniques.

Key Skills

Education

Any Gradute