Senior AI Engineer

Indian AI Research Organisation (IAIRO); India; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Indian AI Research Organisation (IAIRO) is seeking a seasoned backend/AI engineer to design, build, and operate scalable services and APIs powered by LLMs and SLMs. You will architect databases, integrate external AI capabilities, and implement automated testing and robust CI/CD pipelines to ensure production readiness.

The role requires strong CS fundamentals, hands-on experience with major backend frameworks, and a track record of delivering production-grade AI/backend systems in cloud

Qualifications

• Advanced degree (BS/MS) in Computer Science or equivalent.
• Demonstrated ownership of production-grade AI/backend projects.
• Experience with production-grade AI/ML or backend services.

Responsibilities

• Design, build, and operate scalable backend services and APIs.
• Architect and administer scalable databases for AI workloads.
• Integrate external APIs to embed AI into business systems.
• Establish automated testing across unit to performance levels.
• Build and maintain CI/CD pipelines with DevOps/MLOps.
• Diagnose and resolve bugs and document for customers.
• Partner with product managers and AI engineers to deliver production-ready solutions.

Skills

Data structures

Algorithms

Programming

Design patterns

Virtualization

Code quality

Automated testing

Distributed systems

Education

BS in Computer Science

MS in Computer Science

Tools

Node.js

Django

Flask

FastAPI

Docker

Kubernetes

AWS

GCP

Azure

Job description

• Design, build, and operate scalable backend services, APIs, and AI agents driven by large and small language models (LLMs and SLMs), engineered for production reliability from day one.
• Architect and administer databases that power AI functionality at scale, designing efficient, performant data models that hold up under real-world load.
• Integrate external APIs and services to embed AI capabilities into existing business systems and workflows without compromising stability or performance.
• Establish comprehensive automated testing across unit, functional, integration, and performance layers to guarantee production readiness.
• Build and maintain robust CI/CD pipelines using DevOps and MLOps practices to deploy, monitor, and evaluate applications and services in live production environments.
• Diagnose and resolve bugs and field issues quickly, and produce clear documentation as needed to support customers and business partners.
• Partner with product managers and AI engineers to deliver complete, production-quality solutions.

Minimum Qualifications and Experience

• Advanced degree (BS/MS) in Computer Science or equivalent technical discipline. We prioritise tangible impact over tenure; you should demonstrate clear ownership of production-grade AI/ML or backend services through professional work, open-source contributions, or sophisticated personal engineering projects.

Required Expertise

• Strong grounding in computer science fundamentals such as data structures, algorithms, programming, design patterns, virtualization, and so on, paired with sharp problem-solving abilities.
• Commitment to high code-quality standards (clean, well-documented, modular, maintainable, reliable, efficient, secure coding) and automated testing that stands up to production demands.
• Practical experience with backend frameworks such as Node.js, Django, Flask, and FastAPI.
• Proven experience building and scaling large-scale microservices and applications on cloud platforms (e.g., AWS, GCP, Azure) using containerization and orchestration tools (e.g., Docker, Kubernetes).
• Familiarity with SQL and NoSQL databases, including the ability to write complex queries and optimize database performance at scale.
• Collaborative team player with strong interpersonal skills and the ability to work effectively alongside remote teammates.
• Proactive, go-getter mindset and the ability to thrive in a fast-paced startup environment.

Preferred Skills

• Experience with or working knowledge of any of the following is a strong plus:
• Building AI/ML applications such as AI agents, chatbots, and automation workflows.
• Vector databases, embeddings, and retrieval-augmented generation (RAG).
• Model Context Protocol (MCP), Agent-to-Agent (A2A), and Agent Communication Protocol (ACP).
• AI/ML tools such as PyTorch, TensorFlow, LangChain, LlamaIndex, and similar.

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