Senior AI Engineer

Role & responsibilities

• Design, develop, and maintain full-stack Python applications with modern frontend frameworks
• Build and optimize RAG (Retrieval-Augmented Generation) systems for AI applications
• Create and implement efficient vector databases and knowledge stores
• Develop APIs that connect frontend interfaces with backend AI services
• Implement and maintain CI/CD pipelines for AI applications
• Monitor application performance and troubleshoot issues in production
• Design and maintain data pipelines, ETL/ELT workflows, and data infrastructure to support AI and analytics

Preferred candidate profile

Minimum of 5 years of experience in AI/ML solution implementation (mandatory

Minimum of 3 years of experience in Pyspark processing high volume data (mandatory)
• AI & ML Skills:
Multi-Agent System Design & Orchestration
Full-stack AI Integration (Frontend to Backend)
Advanced Prompt Engineering
LLM Observability, Evaluation & Monitoring (LLMOps)
• Data Engineering Skills:
Proficient in Pyspark coding and concepts. Example: Lazy evaluation, window functions, spark architecture and performance finetuning (ex: data skew reduction (salting etc), joins (broadcast, merge sort joins ect)
SQL proficiency and query optimization

Perks and benefits