Senior AI Engineer
CodeRound AI · Remote · remote · Posted 43d ago
Undisclosed4–9 yrsfulltimeSourced from
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About this role
Job Summary
Responsibilities
Requirements
Key Skills
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
An AI-powered logistics and delivery management platform that helps businesses optimize, manage, and scale their last-mile delivery operations. Design and build production-grade AI applications and agentic workflows using LLMs. Develop and orchestrate complex multi-step and multi-agent workflows using LangGraph. Build AI agents capable of reasoning, tool calling, memory management, and executing real-world tasks. Design robust architectures for LLM applications, including prompt engineering, context management, and retrieval pipelines. Build and optimize RAG systems using vector databases and modern retrieval techniques. Integrate AI systems with internal platforms, APIs, databases, and third-party tools. Improve the reliability, latency, accuracy, and cost efficiency of AI applications. Build evaluation frameworks and monitoring systems for LLM and agent performance. Work closely with product and engineering teams to identify and implement high-impact AI use cases. Take ownership of AI systems from experimentation and architecture through deployment and production monitoring. We are looking for a highly skilled Senior AI Engineer to design, build, and deploy production-grade AI systems and agentic workflows. You will play a key role in developing intelligent automation and AI-powered capabilities that solve complex real-world problems at scale. This role requires strong hands-on experience with LLMs, agentic systems, and LangGraph, along with the ability to build reliable, scalable, and production-ready AI applications.
Responsibilities
- Design and build production-grade AI applications and agentic workflows using LLMs.
- Develop and orchestrate complex multi-step and multi-agent workflows using LangGraph.
- Build AI agents capable of reasoning, tool calling, memory management, and executing real-world tasks.
- Design robust architectures for LLM applications, including prompt engineering, context management, and retrieval pipelines.
- Build and optimize RAG systems using vector databases and modern retrieval techniques.
- Integrate AI systems with internal platforms, APIs, databases, and third-party tools.
- Improve the reliability, latency, accuracy, and cost efficiency of AI applications.
- Build evaluation frameworks and monitoring systems for LLM and agent performance.
- Work closely with product and engineering teams to identify and implement high-impact AI use cases.
- Take ownership of AI systems from experimentation and architecture through deployment and production monitoring.
Requirements
- Strong hands-on experience with LLMs, agentic systems, and LangGraph, along with the ability to build reliable, scalable, and production-ready AI applications.
Key Skills
- LangGraph
- LLMs
- agentic systems
- prompt engineering
- vector databases
- retrieval pipelines
- RAG systems
- tool calling
- memory management
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Sourced from naukri
Skills
AutomationCostdelivery operationsMonitoringMemory managementLogisticsdeploymentmanagementDelivery ManagementArchitecture
About Coderound Ai
CodeRound AI
Mumbai
US
About
CodeRound AI develops an AI-powered recruitment and assessment platform designed to streamline hiring processes for technology roles. Its solutions enable companies to evaluate candidates through automated coding tests, skill assessments, and data-driven insights. By combining artificial intelligence with recruitment workflows, CodeRound AI helps organizations improve efficiency, reduce bias, and make smarter talent acquisition decisions.
Industries
Artificial Intelligence (AI)Information TechnologyRecruitingSaaSSoftware
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