AI Lead / Data & AI Enablement Lead

Zohorecruit; Hyderabad, Dadri; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

Multiplier AI in Hyderabad/Noida, India is seeking an experienced AI Lead to identify high-value AI opportunities and enable data and engineering teams to adopt AI capabilities.

The role covers generative AI, retrieval-augmented generation, AI agents, traditional ML, predictive modelling, and intelligent automation, delivering secure, scalable, production-ready solutions across business units.

Qualifications

• Significant experience delivering artificial intelligence, machine learning, or advanced analytics solutions in production environments.

Responsibilities

• Partner with business, data, and technology teams to identify and prioritise artificial intelligence use cases.
• Evaluate whether rules, analytics, traditional machine learning, retrieval-augmented generation, generative artificial intelligence, or automation is the most suitable solution.
• Define artificial intelligence architectures, technology selections, delivery approaches, and implementation roadmaps.
• Lead the design and delivery of retrieval-augmented generation solutions, including document processing, chunking, embeddings, vector search, retrieval, re-ranking, and grounded response generation.
• Guide predictive modelling initiatives involving classification, regression, forecasting, anomaly detection, recommendations, and optimisation.
• Assess managed models, open-source models, fine-tuning approaches, and custom modelling solutions.
• Develop secure integrations between artificial intelligence services, enterprise data platforms, applications, and business workflows.
• Establish evaluation frameworks to measure model quality, retrieval relevance, hallucination, accuracy, latency, cost, and business value.

Skills

Python

SQL

Large language models

Embeddings

Vector databases

Retrieval-augmented generation

Prompt engineering

Model evaluation

Machine learning

Production ML

Tools

Snowflake

Databricks

Job description

Hyderabad, Noida, India

• Industry Pharma/Biotech/Clinical Research
• Work Experience 5+ years
• Country India

About Us

Multiplier AIis a leading AI-driven Healthcare and Life Sciences technology company delivering innovative solutions across Pharma, Healthcare, and Enterprise AI. We empower global organizations with AI-powered platforms, data intelligence, automation, and digital transformation solutions. As we continue to expand, we are looking for energetic professionals who can contribute to our business growth while ensuring operational excellence.

Job Description

We are looking for an experienced AI Lead / Data and Artificial Intelligence Enablement Lead to identify high-value artificial intelligence opportunities, recommend suitable solution approaches, and enable data and engineering teams to adopt artificial intelligence capabilities.

The role involves working across generative artificial intelligence, retrieval-augmented generation, artificial intelligence agents, traditional machine learning, predictive modelling, and intelligent automation. The candidate will be responsible for converting business opportunities into secure, scalable, measurable, and production-ready solutions.

Major Responsibilities

Partner with business, data, and technology teams to identify and prioritise artificial intelligence use cases.

Evaluate whether rules, analytics, traditional machine learning, retrieval-augmented generation, generative artificial intelligence, or automation is the most suitable solution.

Define artificial intelligence architectures, technology selections, delivery approaches, and implementation roadmaps.

Lead the design and delivery of retrieval-augmented generation solutions, including document processing, chunking, embeddings, vector search, retrieval, re-ranking, and grounded response generation.

Guide predictive modelling initiatives involving classification, regression, forecasting, anomaly detection, recommendations, and optimisation.

Assess managed models, open-source models, fine-tuning approaches, and custom modelling solutions.

Develop secure integrations between artificial intelligence services, enterprise data platforms, applications, and business workflows.

Establish evaluation frameworks to measure model quality, retrieval relevance, hallucination, accuracy, latency, cost, and business value.

Requirements

Significant experience delivering artificial intelligence, machine learning, or advanced analytics solutions in production environments.

Strong understanding of the complete artificial intelligence lifecycle, from problem definition and data preparation to evaluation, deployment, and monitoring.

Practical experience implementing retrieval-augmented generation solutions.

Strong knowledge of large language models, embeddings, vector databases, retrieval, re-ranking, prompt engineering, and model evaluation.

Strong programming skills in Python and SQL.

Experience with common data science and machine learning libraries.

Knowledge of modern cloud data platforms such as Snowflake and Databricks.

Experience developing structured, semi-structured, and unstructured data pipelines.

Experience integrating artificial intelligence solutions through application programming interfaces, applications, and enterprise workflows.

Knowledge of machine learning operations, large language model operations, continuous integration and continuous delivery, experiment tracking, model registries, and production monitoring.

Professional growth and career development in artificial intelligence and machine learning.

Opportunities to work on generative artificial intelligence, predictive modelling, and intelligent automation solutions.

Exposure to artificial intelligence architecture, experimentation, and production implementation.

Collaboration with business, data engineering, and technology teams.

Opportunity to develop reusable artificial intelligence architectures, frameworks, and engineering patterns.

Experience in responsible artificial intelligence, governance, security, and regulatory compliance.

Opportunities to coach teams and build organizational artificial intelligence capabilities.

Exposure to modern cloud data platforms and enterprise artificial intelligence technologies.