AI Engineer

Role & responsibilities

Preferred candidate profile

No of roles 2

Experience- 4+ years

Mode of working – WFH / Remote

AI Engineer - Role Summary

As an AI engineer part of the Internal Tooling automation, you will collaborate closely with Operations teams to develop and maintain tools that ensure seamless daily support for customers. In addition to traditional development responsibilities, you will leverage AI and machine learning (ML) tools to increase automation, streamline processes, and enhance operational efficiency. Your primary focus will be on designing, implementing, and optimizing internal tools, identifying opportunities for automation, and integrating intelligent solutions that boost productivity and effectiveness across support processes.

Key Responsibilities

• Design, develop, and maintain internal tools and automation solutions, incorporating AI/ML capabilities where applicable.
• Leverage AI and ML tools to identify, implement, and optimize automation opportunities.
• Integrate SaaS platforms (e.g., Hubspot, Zendesk) with internal company tools using APIs and web technologies.
• Collaborate with cross-functional teams to understand requirements and deliver AI-enhanced solutions.
• Develop and maintain documentation for tools, integrations, and automation processes.
• Troubleshoot and resolve issues related to integrations, automation, and AI-powered solutions.
• Continuously improve existing tools, processes, and user experiences by utilizing AI and ML advancements.
• Stay up-to-date with the latest trends in web development, AI, ML, and automation technologies.

Knowledge, Skills, and Capabilities

• Proven experience in web technologies (HTML, CSS, JavaScript) and RESTful & GraphQL API development.
• Experience with server-side frameworks like Express.js (Node.js), Django (Python), or Spring Boot (Java).
• Proficiency in scripting languages (e.g., Bash, Python) for automation tasks.
• Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch) and tools for deploying automation solutions.
• Strong understanding of integrating AI/ML models into existing systems and workflows.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills.
• Ability to work independently and manage multiple tasks effectively.

Preferred Qualifications

• Experience with cloud platforms (AWS, Azure, Google Cloud) and AI/ML services offered by these platforms.
• Experience with Hubspot APIs, JIRA APIs, and Zendesk APIs/ZAF a bonus.
• Knowledge of CI/CD pipelines, DevOps practices, and AI/ML model deployment pipelines.
• Familiarity with natural language processing (NLP) tools and techniques for automating text-based workflows.

Perks and benefits