About the role
We’re looking for an AI Engineer to build production AI capabilities using both commercial AI APIs and open-source models.
You will develop LLM applications, build retrieval and knowledge systems, train and fine-tune models, and deploy AI services in the cloud. You’ll expose these capabilities through secure, documented APIs that our backend developers can integrate into our products.
This role owns AI services and their supporting backend infrastructure. Frontend development is outside its scope.
Responsibilities
Integrate AI APIs from providers such as OpenAI, Anthropic, and Google, working across different models and their capabilities.
Build LLM workflows using prompt design, structured outputs, tool calling, streaming, and conversation management.
Select models based on measured quality, latency, context requirements, and cost; implement routing, fallbacks, and retries where needed.
Design and maintain retrieval-augmented generation (RAG) systems, including document ingestion, parsing, chunking, embeddings, indexing, retrieval, and reranking.




Implement and evaluate approaches such as vector RAG, hybrid search, GraphRAG, and agentic retrieval based on product needs.
Build AI assistants and workflows that connect models with internal data, tools, and business systems.
Prepare datasets, train models where appropriate, and fine-tune open-source models for specific tasks.
Deploy and operate open-source models on cloud infrastructure, including GPU environments.
Develop secure, tested, and documented APIs for backend developers, with clear request formats, responses, and error handling.
Evaluate model outputs and retrieval quality, and monitor production reliability, latency, and cost.
Maintain reproducible workflows for experimentation, model versioning, deployment, and ongoing improvement.
Implement access controls, data protection, and safeguards against prompt injection and unauthorized data retrieval.
Requirements
Solid Python skills and experien

📌 AI Engineer (India)
🏢 Vebholic
📍 India