AI Engineer

Korza; India; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Korza is seeking a seasoned backend architect to design and scale AI infrastructure, data pipelines, and orchestration workflows for LLMs and agent-based systems. You will ship production-grade code that powers high-throughput AI workflows and data-driven applications across cloud environments.

Collaborate directly with ML engineers, product leads, and frontend developers to translate complex client problems into robust platform components and reusable AI products.

Qualifications

• Core backend mastery with strong problem-solving and analytical skills in modern backend technologies (Python, Go, Java, or Node.js).
• System architecture knowledge: data structures, REST/gRPC, SQL/NoSQL, distributed systems.
• AI/ML exposure: hands-on or direct exposure to LLMs, RAG frameworks, model integrations, or AI data pipelines.
• Production operations: experience deploying and scaling backend systems in production cloud environments.
• Problem-solving mindset: turning ambiguous requirements into robust software.

Responsibilities

• Architect AI infrastructure: design and build backend services, data pipelines, and orchestration workflows for LLMs and agent-based systems.
• Ship production-grade code: write high-performance, clean, testable code for high-throughput AI workflows and data-driven systems.
• Integrate and scale: build resilient APIs and pipelines integrating models, vector stores, and backend microservices across clouds.
• Drive productization: translate enterprise client problems into robust platform components and reusable AI products.
• Cross-functional collaboration: work with ML engineers, product leads, and frontend developers to ship AI capabilities.

Skills

Backend mastery

System architecture

AI/ML exposure

Production operations

Problem-solving mindset

Tools

LangChain

LlamaIndex

Job description

• Architect AI Infrastructure: Design and build backend services, data pipelines, and orchestration workflows for LLMs and agent-based systems.
• Ship Production-Grade Code: Write high-performance, clean, testable code to serve high-throughput AI workflows and data-driven systems.
• Integrate & Scale: Build resilient APIs and pipelines integrating foundational models, vector data stores, and backend microservices across cloud environments.
• Drive Productization: Translate ambiguous enterprise client problems into robust, scalable platform components and reusable AI products.
• Cross-Functional Collaboration: Partner directly with ML engineers, product leads, and frontend developers to rapidly ship cutting-edge AI capabilities.

What You’ll Do

• Architect AI Infrastructure: Design and build backend services, data pipelines, and orchestration workflows for LLMs and agent-based systems.
• Ship Production-Grade Code: Write high-performance, clean, testable code to serve high-throughput AI workflows and data-driven systems.
• Integrate & Scale: Build resilient APIs and pipelines integrating foundational models, vector data stores, and backend microservices across cloud environments.
• Drive Productization: Translate ambiguous enterprise client problems into robust, scalable platform components and reusable AI products.
• Cross-Functional Collaboration: Partner directly with ML engineers, product leads, and frontend developers to rapidly ship cutting-edge AI capabilities.

What We’re Looking For

• Core Backend Mastery: Strong problem-solving and analytical skills with solid fundamentals in modern backend technologies (Python, Go, Java, or Node.js).
• System Architecture: Solid understanding of data structures, REST/gRPC APIs, SQL/NoSQL databases, and distributed systems design.
• AI/ML Technical Exposure: Hands-on experience or direct exposure to LLMs, RAG frameworks (e.g., LangChain, LlamaIndex), model integrations, or AI/ML data pipelines.
• Production Operations: Proven track record of building, deploying, operating, and scaling backend systems in production cloud environments.
• Problem-Solving Mindset: Ability to take ambiguous business and technical requirements and turn them into robust, clean software solutions.