Full Stack AI Engineer

Job Description

We’re looking for a Full Stack AI Software Development Engineer to join the SearchUnify team at Grazitti Interactive. In this role, you’ll develop end-to-end features across frontend, backend, APIs, databases, and AI integrations. The role involves building AI agents that can reason, plan, and execute tasks, while contributing to scalable, enterprise-grade systems.

If you have experience building AI products and enjoy working across full-stack engineering and AI integrations, this opportunity is for you.

Key Skills

• 3–5 years of professional software development experience across frontend, backend, and APIs.
• Experience building AI products, especially Agentic AI, and supporting workflow-related solutions.
• Hands-on experience with Agentic AI across domains such as BFSI, healthcare, telecom, or retail is a plus.
• Strong programming skills in JavaScript, TypeScript, Python, and Node.js; multi-language experience is a plus.
• Experience with modern JavaScript frameworks and libraries.
• Experience designing and consuming REST and GraphQL APIs and integrating them with AI-driven systems.
• Strong knowledge of relational and non-relational databases, including Elasticsearch, Apache Solr, MySQL, PostgreSQL, MongoDB, Redis, and Citus Data.
• Familiarity with AI/ML integration, MCPs, NLP models, and working with APIs for AI-driven products.
• Knowledge of AWS and GCP is an advantage.
  
  

Roles and Responsibilities

• Design, develop, and maintain scalable, high-performance Agentic AI features on the SearchUnify platform.
• Build end-to-end AI solutions for demos and POCs, covering frontend, backend, and orchestration layers.
• Integrate AI models and frameworks, including NLP, LLMs, and reasoning engines, into backend services and user-facing components.
• Collaborate with product managers, ML engineers, and designers to convert requirements into functional, tested code.
• Participate in Agile Scrum activities, including daily stand-ups, sprint planning, backlog grooming, and retrospectives.
• Perform unit, integration, and API-level testing, troubleshoot production issues, and maintain code quality.
• Stay updated with AI trends, NLP advancements, and emerging engineering tools.
• Follow internal QMS procedures and Information Security Controls as per the organization’s ISMS.
• Report incidents to the reporting manager or supervisor.