Senior AI Engineer

IndiaRemoteFull-timesenior

Machine Learning EngineerData

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Requirements Summary

5+ years of software engineering experience, with significant hands-on experience building AI, machine learning, or advanced analytics solutions.

Technical Tools

Machine Learning EngineerData

This role focuses on designing, developing, and deploying production-grade AI solutions that create measurable business value across complex enterprise environments. You will turn business opportunities into scalable AI applications, agents, services, and reusable capabilities. The position combines hands-on AI engineering with modern software architecture, cloud-native development, and AI lifecycle practices. You will work with multidisciplinary teams spanning Product, Architecture, AI Science, Platform, and Data Engineering. The role offers the opportunity to work with LLMs, RAG, agentic AI, and other emerging technologies while helping establish reliable and reusable AI capabilities. You will also contribute to secure, maintainable, and enterprise-ready solutions that can be scaled across multiple business environments.

Design, develop, and deploy scalable AI solutions, applications, services, workflows, and reusable capabilities that address real business needs.
Develop and optimize Large Language Model (LLM) applications using prompt engineering, Retrieval-Augmented Generation (RAG), fine-tuning, agentic workflows, and modern AI engineering techniques.
Build AI capabilities that can be deployed and supported reliably in production and across enterprise environments.
Implement and support MLOps, DataOps, and LLMOps practices covering model lifecycle management, deployment, monitoring, governance, and continuous improvement.
Contribute to scalable, reliable, maintainable, and secure AI architectures that meet enterprise standards for performance and supportability.
Collaborate with Product Owners, Architects, AI Scientists, Platform Engineering, and Data Engineering teams to industrialize and scale trusted AI solutions.
Translate business opportunities into practical AI applications, agents, and reusable technical capabilities.
Apply strong software engineering practices, architecture patterns, APIs, microservices, CI/CD, and cloud-native development principles to AI solutions.
Contribute to the continuous improvement of AI engineering standards, processes, and reusable capabilities across the enterprise.

Requirements

~1 min read

5+ years of software engineering experience, with significant hands-on experience building AI, machine learning, or advanced analytics solutions.
Strong proficiency in Python and modern AI development frameworks, libraries, and tooling.
Proven experience developing, deploying, and supporting production-grade AI, machine learning, or data-driven solutions in cloud environments.
Strong understanding of software engineering practices, architecture patterns, APIs, microservices, CI/CD, and cloud-native development.
Good understanding of modern AI methodologies, including LLMs, semantic models, knowledge and context graphs, RAG, and agentic AI architectures.
Strong analytical and problem-solving skills, with the ability to translate complex business needs into scalable technical solutions.
Effective communication and collaboration skills for working across multidisciplinary engineering and product teams.
Experience building AI solutions for regulated industries such as life sciences, diagnostics, healthcare, or advanced manufacturing is a plus.
Experience developing AI capabilities for knowledge extraction, decision support, process optimization, or workflow automation across enterprise data ecosystems is desirable.
Knowledge of Responsible AI and enterprise AI governance, including model evaluation, explainability, bias assessment, and compliance with emerging AI regulations and frameworks, is an advantage.