AI Engineer

CodeRound AI; Delhi; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

CodeRound AI is seeking an AI Engineer to build and own production-grade AI systems, including RAG pipelines, AI agents, and evaluation frameworks. You will work with frontier models, vector databases, and LangGraph to improve retrieval quality, agent reliability, and overall AI performance.

The ideal candidate has 2-3+ years of hands-on production AI/ML experience, strong system design skills, and deep expertise in RAG and AI evaluation.

Qualifications

• 2-3+ years of hands-on production AI/ML experience.
• Strong system design skills.
• Deep expertise in RAG and AI evaluation.

Responsibilities

• Own the intelligence layer
• Build RAG and retrieval systems that pull in data from multiple sources to make every AI output relevant and grounded in real context
• Build AI agents and workflows - research agents, enrichment agents, follow-up sequencing agents that operate reliably at scale without human intervention
• Build the evaluation framework that measures output quality before anything reaches real prospects
• Define what "good" means and build the infrastructure to measure it consistently
• Make the AI meaningfully better, measurably, every week
• Make measurable improvements to retrieval quality or agent reliability
• Diagnose the biggest AI quality gaps and create a prioritized plan to close them
• Stay current with new model releases, new frameworks, and new research
• Evaluate and make decisions on the right retrieval strategy, the right eval metric, the right model for a given task
• Work on backend or frontend that work with the AI backend when required

Skills

AI/ML systems

RAG pipelines

System design

Production-grade

Tools

LangGraph

Vector Databases

OpenAI

Anthropic

Job description

Client: An AI-native B2B sales platform that helps companies find high-intent buyers by analyzing hundreds of buying signals across multiple sources, identifying the reason an account is ready to buy, and turning that intelligence into personalized outreach, account research and deal-closure workflows.

Requirements:

AI Engineer AI/ML RAG Retrieval Systems Retrieval Quality Chunking Strategy Embedding Models Re-ranking AI Agents Agentic AI Multi-Agent Systems Agent Orchestration LangGraph Tool Calling Chatbots Evaluation Frameworks AI Evaluation LLM Anthropic OpenAI Vector Databases Vector DBs AI Tooling Agent Libraries Fine-tuning RLHF Distillation System Design AI Backend Backend Enterprise SaaS B2B SaaS Sales Tech Production AI AI/ML Systems AI Quality Model Migration CS

We're looking for an AI Engineer to build and own production-grade AI systems, including RAG pipelines, AI agents, production chatbots, and evaluation frameworks. You'll work with frontier models, vector databases, and LangGraph to improve retrieval quality, agent reliability, and overall AI performance. The ideal candidate has 2-3+ years of hands-on production AI/ML experience, strong system design skills, and deep expertise in RAG and AI evaluation. This is a high-ownership role where you'll be expected to ship, measure, iterate, and make meaningful improvements to AI quality every week.

Responsibilities:

• Own the intelligence layer
• Build RAG and retrieval systems that pull in data from multiple sources to make every AI output relevant and grounded in real context
• Build AI agents and workflows - research agents, enrichment agents, follow-up sequencing agents that operate reliably at scale without human intervention
• Build the evaluation framework that measures output quality before anything reaches real prospects
• Define what "good" means and build the infrastructure to measure it consistently
• Make the AI meaningfully better, measurably, every week
• Make measurable improvements to retrieval quality or agent reliability
• Diagnose the biggest AI quality gaps and create a prioritized plan to close them
• Stay current with new model releases, new frameworks, and new research
• Evaluate and make decisions on the right retrieval strategy, the right eval metric, the right model for a given task
• Work on backend or frontend that work with the AI backend when required

Nice to have:

AI Engineer AI/ML RAG Retrieval Systems Retrieval Quality Chunking Strategy Embedding Models Re-ranking AI Agents Agentic AI Multi-Agent Systems Agent Orchestration LangGraph Tool Calling Chatbots Evaluation Frameworks AI Evaluation LLM Anthropic OpenAI Vector Databases Vector DBs AI Tooling Agent Libraries Fine-tuning RLHF Distillation System Design AI Backend Backend Enterprise SaaS B2B SaaS Sales Tech Production AI AI/ML Systems AI Quality Model Migration CS