Senior Artificial Intelligence Engineer

Job Title: Sr.AI Engineer (AI + Software Engineering)


Experience: 5+ Years
Location: Hybrid
Qualification: Bachelors Degree in Computer Engineering or equivalent

About Cloudaeon

Cloudaeon is a data and AI-driven technology consulting firm specializing in modern data platforms, advanced analytics, and enterprise digital transformation. We help organizations unlock business value through scalable cloud solutions, strong engineering practices, and deep domain expertise.

Our focus is on building intelligent, analytics-ready, and AI-enabled data ecosystems powered by Azure, Databricks, and modern transformation frameworks like DBT.

Role Summary

We are looking for a highly skilled Senior AI Engineer with hands-on experience in Generative AI, LLM-based applications and full-stack software development to design and deliver scalable, enterprise-grade AI solutions.

The ideal candidate should possess strong expertise in AI engineering, backend development, frontend technologies such as React.js, API integration and modern software engineering practices, along with experience in CI/CD and cloud-native application development.

This role requires a proactive and self-driven professional who can independently engage with business and technical stakeholders, drive AI initiatives end-to-end and build production-ready AI-powered applications. Databricks experience would be an added advantage.

Key Responsibilities

• Design, develop and deploy AI/ML and Generative AI solutions, including LLM-powered applications, RAG pipelines and AI agents.
• Build scalable backend services, APIs and microservices to integrate AI capabilities with enterprise applications.
• Develop responsive and interactive frontend applications using React.js, JavaScript/TypeScript and related web technologies.
• Integrate LLMs, vector databases, enterprise data sources and third-party services into AI-powered applications.
• Implement AI orchestration, prompt engineering, embeddings, semantic search and retrieval optimisation.
• Develop and maintain CI/CD pipelines, automated testing and deployment processes to ensure reliable software delivery.
• Collaborate with stakeholders to understand business requirements and translate them into scalable technical solutions.
• Ensure application performance, security, scalability, monitoring and maintainability across the technology stack.

• Drive technical discussions, recommend appropriate architectures and independently manage deliverables from design through deployment.

Required Skills

• 5+ years of experience in software engineering, application development and/or AI engineering, with relevant hands-on experience in Generative AI.
• Strong programming skills in Python and/or Java, with experience building production-grade applications.
• Hands-on experience developing LLM-based applications, RAG architectures, prompt engineering and AI-powered workflows.
• Strong backend development experience, including REST APIs, microservices and system integrations.
• Experience with frontend development using React.js, JavaScript/TypeScript, HTML and CSS.
• Familiarity with AI frameworks such as LangChain, LangGraph, LlamaIndex or equivalent.
• Understanding of vector databases, embeddings, semantic search and integration with enterprise data sources.
• Experience with Git, CI/CD pipelines, automated testing and application deployment practices.
• Understanding of cloud-native architectures, application security and software engineering best practices.
• Excellent communication, articulation, stakeholder management and interpersonal skills.
• Highly proactive, self-driven and capable of independently driving initiatives end-to-end.

Good to Have

• Experience with Databricks, including Mosaic AI, Vector Search or Model Serving.
• Exposure to Microsoft AI Foundry, Azure OpenAI and other Microsoft Azure AI services.
• Experience with Agentic AI frameworks, tool calling and autonomous AI workflows.
• Familiarity with Docker, Kubernetes, MLOps and AI application monitoring.
• Experience with Azure, AWS or other cloud platforms.
• Understanding of lakehouse architecture, data engineering concepts and enterprise data platforms.
• Experience with automated frontend testing and application performance optimisation.
• Azure AI Engineer, Databricks or relevant cloud certifications.