Responsibilities:
AI ApplicationDevelopment
- Develop AI-enabled applications using LLMs, agents, and RAG architectures
- Build and integrate chat-based, voice-enabled, and AI agents
- Apply prompt engineering, tool calling, and multi-agent orchestration
- Prototype and refine AI workflows using modern AI frameworks
- Continuously improve solution quality, accuracy, and performance
Full-StackEngineering
- Develop frontend interfaces for applications and demonstrations
(React / Next.js or similar frameworks) - Build backend APIs and services using Node.js, Python, or FastAPI
- Integrate databases, vector stores, and cloud services
- Connect AI solutions with enterprise systems
POC, Demo& Product Support
- Develop structured proofs of concept and customer demonstrations
- Support client-specific configurations and controlled experiments
- Transition successful POCs into maintainable, reusable product features
- Troubleshoot issues, optimize system performance, and improve reliability
Platform& Engineering Collaboration
- Work closely with cross-functional teams to convert use cases into technical solutions
- Contribute to shared components, platform architecture, and engineering standards
- Document designs, patterns, and implementation approach
Key Technical Skills & Responsibilities
Must-Have
- Strong fundamentals in software engineering (data structures, APIs, web applications)
- Experience with full-stack development (frontend and backend)
- Hands-on exposure to LLMs / Generative AI APIs (OpenAI, Anthropic, etc.)
- Proficiency in JavaScript / TypeScript or Python
- Experience designing and consuming REST APIs
- Familiarity with Git and standard development workflows
- Ability to work independently, manage tasks, and take ownership
- Strong analytical and problem-solving mindset
Good to Have (Not Mandatory)
- Experience with RAG architectures and vector databases (Pinecone, Milvus, FAISS, etc.)