AI Software Engineer

Doctutorials Edutech Pvt Ltd; Hyderabad; Presencial; INR 500.000 - 800.000; Jornada completa

Descripción de la vacante

Doctutorials Edutech Pvt Ltd is seeking an AI Services Lead to design and build reliable, secure and measurable AI services powering DocTutorials products and internal capabilities. You will design LLM, RAG, semantic-search and agentic-AI solutions, develop production APIs using Python and FastAPI, and evaluate models for quality, latency and cost.

As a technical leader, you will mentor engineers, document architecture and experiments, and collaborate with product teams to define measurable

Responsabilidades

• Design and implement LLM, RAG, semantic-search and agentic-AI solutions.
• Build ingestion, chunking, embedding, indexing, retrieval, reranking and response pipelines.
• Develop production APIs and services using Python and FastAPI.
• Evaluate open-source and commercial models based on quality, latency and cost.
• Define benchmark datasets and metrics for accuracy, groundedness, relevance and safety.
• Implement prompt and retrieval regression testing, observability and failure handling.
• Optimise model serving, caching, concurrency, token usage and infrastructure cost.
• Ensure source traceability, human validation and secure data handling.
• Lead design and code reviews for AI services and integrations.
• Mentor AI engineers and guide application teams integrating AI capabilities.
• Document architecture, experiments, model decisions and operational runbooks.
• Collaborate with Product and domain experts to define measurable outcomes.

Descripción del empleo

Role & responsibilities

Primary objective: Design and build reliable, secure and measurable AI services that power DocTutorials products and internal capabilities.

1. AI Solution Engineering

• Design and implement LLM, RAG, semantic-search and agentic-AI solutions.
• Build ingestion, chunking, embedding, indexing, retrieval, reranking and response pipelines.
• Develop production APIs and services using Python and FastAPI.
• Evaluate open-source and commercial models based on quality, latency, privacy and cost.

2. Evaluation and Production Reliability

• Define benchmark datasets and metrics for accuracy, groundedness, relevance and safety.
• Implement prompt and retrieval regression testing, observability and failure handling.
• Optimise model serving, caching, concurrency, token usage and infrastructure cost.
• Ensure source traceability, human validation and secure data handling.

3. Technical Leadership

• Lead design and code reviews for AI services and integrations.
• Mentor AI engineers and guide application teams integrating AI capabilities.
• Document architecture, experiments, model decisions and operational runbooks.
• Collaborate with Product and domain experts to define measurable outcomes.