Senior AI Engineer

Location: Ahmedabad, Gujarat, India (On-Office)

Domain: Applied AI / LLM Systems / SaaS Platforms

We are looking for a Senior AI Engineer who can design and ship production AI systems not just run notebooks.

You will own architecture decisions for real customer-facing AI features including retrieval systems, agents, document intelligence, and automation workflows. The role requires turning ambiguous business problems into reliable AI products that run continuously in production environments.

You will guide experimentation, enforce evaluation discipline, and mentor junior engineers while maintaining engineering rigor.

• Retrieval Augmented Generation (RAG) systems
• Multi-step AI agents and workflows
• Document intelligence pipelines
• Structured output extraction systems
• Automated evaluation frameworks
• Cost-optimized inference pipelines
• Internal AI platform tooling

• Design production AI architectures end-to-end
• Convert business workflows into AI pipelines
• Define prompting strategies and failure handling
• Implement evaluation and benchmarking frameworks
• Optimize latency, reliability, and cost
• Lead debugging of hallucination and quality issues
• Guide junior AI engineers technically
• Work closely with backend and data teams for deployment

• Strong Python engineering skills
• Deep hands-on experience with LLM systems in production
• RAG pipeline design experience
• Prompt engineering patterns and structured outputs
• Model evaluation and benchmarking approaches
• API-based and open-source model integration
• Debugging model behavior systematically
• Git and collaborative development practices

• Agent frameworks (LangGraph / DSPy / similar)
• Building internal AI tooling/platforms
• Observability for AI systems
• Performance and cost optimization at scale
• Cloud deployment experience

Within 3 months you will:

• Own at least one production AI feature
• Reduce failure rate or hallucination rate measurably
• Define repeatable evaluation metrics
• Improve reliability of an AI workflow

This role suits engineers who:

• Think in systems, not prompts
• Care about reliability over demos
• Can explain why an AI system fails
• Want to build long-term AI infrastructure