TSIT Digital
AI Full Stack Engineer - Python/React.js
- Compensation
- Not disclosed
- Location
- Bangalore
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Full time
- Experience
- Not specified
- Category
- Fullstack
- Posted
Skills
Full description
Company: Data Essential
Employment Type: Full-Time
Work Mode: Remote-Friendly
About the Role:
Datassential is seeking an experienced AI Software Engineer to build and deliver AI-powered product features that directly impact customers. This is a hands-on engineering role focused on turning LLMs, AI agents, embeddings, and retrieval systems into scalable, production-ready applications. The ideal candidate will work across the full stack, developing backend services in Python/FastAPI and frontend components in React, while integrating advanced AI capabilities into customer-facing products.
Key Responsibilities:
- Design, develop, and deploy AI-powered product features end-to-end.
- Build and integrate LLM-based workflows including Prompt Engineering, RAG, Function Calling, and Agent Orchestration.
- Develop scalable backend services using Python and FastAPI.
- Create intuitive and responsive user interfaces using React.
- Integrate LLM APIs, vector databases, and enterprise data sources.
- Monitor and optimize AI solutions for quality, latency, scalability, and cost.
- Collaborate with Product, Design, and Data Science teams to deliver impactful AI experiences.
- Implement testing, observability, and performance monitoring best practices.
- Contribute to modern AI integration frameworks such as MCP and Agent-to-Agent (A2A) architectures.
Required Skills:
- Strong experience with Python and FastAPI.
- Hands-on experience with React.js.
- Experience building production applications using LLMs, Generative AI, or AI/ML solutions.
- Strong understanding of RAG (Retrieval-Augmented Generation), Embeddings, and AI Agents.
- Experience with OpenAI, Anthropic, or similar LLM platforms.
- Knowledge of vector databases such as Pinecone, Weaviate, or pgvector.
- Experience with PostgreSQL and relational databases.
- Familiarity with cloud platforms (AWS, Azure, or GCP).
- Experience with Docker, Kubernetes, and CI/CD pipelines.
- Strong software engineering, testing, and debugging skills.