Artificial Intelligence Engineer

Bits In Glass; Hyderabad; On-site; INR 2,000,000 - 3,000,000; Full time

Job summary

Bits In Glass is hiring a Gen AI Engineer in Hyderabad, India. This role involves building end-to-end AI applications, integrating data from multiple systems, and developing robust retrieval pipelines.

We seek candidates with at least 8 years of experience, including strong skills in AI/ML and Generative AI. The successful applicant will design and implement applications that meet enterprise standards in security and performance.

Qualifications

• At least 8 years of overall experience, including 6 years in AI/ML and 2 years in GenAI.
• Strong hands-on experience in building end-to-end AI applications.
• Experienced in structured and unstructured data integration.

Responsibilities

• Design and build GenAI/RAG-based applications using enterprise data.
• Integrate with structured and unstructured data sources.
• Develop pipelines for data extraction from documents and images.
• Build workflows for querying and enriching relational databases.
• Implement evaluation practices to ensure solution quality.

Skills

AI/ML engineering

Generative AI

Document parsing

Python

SQL/NoSQL databases

LLM orchestration frameworks

Vector databases

Evaluation frameworks

APIs/services development

Tools

Azure AI stack

Job description

Looking for someone with at least 8 years of overall experience, including 6 years in AI/ML and at least 2 years in GenAI.

Role Summary

Seeking a Gen AI Engineer with strong hands‑on experience in building end-to-end AI applications. The role requires integrating data from multiple systems, extracting and parsing information from documents and images, interacting with structured databases, storing parsed content in a vector database, and implementing robust retrieval pipelines. The engineer must also ensure solution quality through evaluation frameworks, ground‑truth validation, and defined performance metrics.

Key Responsibilities

• Design and build GenAI/RAG-based applications using data from multiple enterprise systems.


• Integrate with structured and unstructured data sources, including databases, APIs, files, and document repositories.


• Develop pipelines to parse and extract data from documents and images using OCR, document intelligence, and related tools.


• Process and structure extracted content for downstream AI use cases.


• Store parsed and chunked content in a vector database and manage embeddings effectively.


• Implement and optimize retrieval pipelines, including chunking, indexing, metadata tagging, filtering, and reranking.


• Build workflows to interact with relational and enterprise databases for querying and enrichment.


• Ensure the application follows strong evaluation practices, including accuracy, groundedness, relevance, hallucination checks, and response quality against ground truth.


• Work closely with architects, platform teams, and business stakeholders to deliver scalable and secure solutions.


• Follow enterprise standards for security, governance, observability, and performance.

Required Skills and Experience

• Strong experience in AI/ML engineering, with hands‑on exposure to Generative AI use cases.


• Experience in building RAG applications in enterprise environments.


• Strong knowledge of document parsing, OCR, and image‑based data extraction.


• Experience with LLM orchestration frameworks and prompt design.


• Experience with vector databases and semantic search.


• Strong programming skills in Python.


• Experience working with SQL/NoSQL databases and enterprise data integration patterns.


• Understanding of evaluation frameworks for GenAI systems using benchmark datasets and ground‑truth‑based validation.


• Experience in building scalable APIs/services and production‑grade AI workflows.

Preferred Skills

• Experience with Azure-based AI stack.


• Experience with high‑volume document processing.


• Familiarity with enterprise architecture, security, and compliance controls.


• Exposure to monitoring, model evaluation, and AI observability tools.

Preferred Profile

• Able to independently build and deploy GenAI applications from ingestion to retrieval and evaluation.


• Strong problem‑solving skills with a practical implementation mindset.