Ai Engineer Global It Infrastructure Pune (India)

Role Summary

The AI Engineer contributes to the end-to-end delivery of AI/ML solutions within the Office of Innovation, working alongside broader platform teams. This role spans model development support, GenAI application building, infrastructure automation, and governance tooling, making it an ideal position for an engineer ready to deepen expertise across the full AI delivery stack. The successful candidate is technically sharp, eager to grow, and comfortable operating in a quick-paced innovation workplace within a global enterprise.

Key Responsibilities

AI/ML Model Development

Build, train, and evaluate ML models, contributing to the full model lifecycle from data preparation through to deployment.

Conduct exploratory data analysis, feature engineering, and model experimentation; document findings clearly.

Support model validation, testing, and performance benchmarking activities.

Generative AI & LLM Applications

Develop and maintain GenAI-powered applications including chatbots, summarization tools, document processing pipelines, and internal copilots.

Implement prompt engineering patterns, retrieval-augmented generation (RAG) pipelines, and tool-augmented agents using established frameworks.

Participate in the evaluation of current LLM capabilities and contribute to internal proof-of-concepts.

AI Infrastructure & MLOps

Support the building and maintenance of ML pipelines, including data ingestion, preprocessing, training automation, and model serving.

Manage and monitor deployed models; identify and escalate performance degradation, drift, or anomalies.

Contribute to infrastructure-as-code for AI workloads across cloud environments (AWS, Azure, or GCP).

AI Governance & Quality

Assist in producing governance documentation: model cards, data lineage records, and risk assessment inputs.

Implement monitoring and logging frameworks to support auditability and compliance requirements.

Apply responsible AI checklists and flag potential bias, fai Role Summary

The AI Engineer contributes to the end-to-end delivery of AI/ML solutions within the Office of Innovation, working alongside broader platform teams. This role spans model development support, GenAI application building, infrastructure automation, and governance tooling, making it an ideal position for an engineer ready to deepen expertise across the full AI delivery stack. The successful candidate is technically sharp, eager to grow, and comfortable operating in a quick-paced innovation workplace within a global enterprise.

Key Responsibilities

AI/ML Model Development

Build, train, and evaluate ML models, contributing to the full model lifecycle from data preparation through to deployment.

Conduct exploratory data analysis, feature engineering, and model experimentation; document findings clearly.

Support model validation, testing, and performance benchmarking activities.

Generative AI & LLM Applications

Develop and maintain GenAI-powered applications including chatbots, summarization tools, document processing pipelines, and internal copilots.

Implement prompt engineering patterns, retrieval-augmented generation (RAG) pipelines, and tool-augmented agents using established frameworks.

Participate in the evaluation of current LLM capabilities and contribute to internal proof-of-concepts.

AI Infrastructure & MLOps

Support the building and maintenance of ML pipelines, including data ingestion, preprocessing, training automation, and model serving.

Manage and monitor deployed models; identify and escalate performance degradation, drift, or anomalies.

Contribute to infrastructure-as-code for AI workloads across cloud environments (AWS, Azure, or GCP).

AI Governance & Quality

Assist in producing governance documentation: model cards, data lineage records, and risk assessment inputs.

Implement monitoring and logging frameworks to support auditability and compliance requirements.

Apply responsible AI checklists and flag potential bias, fai