Senior AI Engineer (ML / Deep Learning / GenAI) in India at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior AI Engineer (ML / Deep Learning / GenAI) in India.

This role is centered on building intelligent, production-grade AI systems that transform complex business workflows into scalable, reliable, and reusable AI capabilities. You will work across the full AI lifecycle, from model design and experimentation to deployment, monitoring, and continuous retraining in production environments. The focus is on both classical machine learning and modern generative AI solutions, including RAG-based systems and agentic architectures. A key dimension of the role is ensuring AI solutions can scale across multiple customers with strong guardrails, evaluation frameworks, and multi-tenant reliability. You will collaborate closely with MLOps, DevOps, and architecture teams to industrialize AI systems and establish reusable engineering standards. The environment is highly collaborative, product-driven, and focused on delivering measurable real-world impact through AI.

• Design, build, and deploy end-to-end AI solutions using machine learning, deep learning, and generative AI techniques based on business and product requirements.
• Develop and maintain scalable pipelines for training, evaluation, deployment, monitoring, and automated retraining of AI models.
• Build and productionize GenAI applications such as RAG systems and agent-based workflows with robust evaluation frameworks and safety guardrails.
• Deploy AI services for real-time and batch inference, ensuring performance, scalability, and cost efficiency.
• Implement model observability practices including performance tracking, drift detection, data quality monitoring, alerting, and production troubleshooting.
• Design and support multi-tenant AI solutions that can be safely reused across multiple customers with consistent performance and governance.
• Collaborate with platform, DevOps, and engineering teams to integrate AI systems into CI/CD pipelines and production environments.
• Define and enforce best practices for model lifecycle management, versioning, and automated retraining workflows.

• 5+ years of experience in AI/ML engineering, including at least 2+ years working on GenAI or LLM-based systems.
• Strong proficiency in Python for machine learning, automation, and production-grade AI system development.
• Hands-on experience building GenAI applications such as RAG pipelines or AI agents, including evaluation and guardrail design.
• Proven experience deploying and operating ML models in production with monitoring, retraining, and observability frameworks.
• Experience with cloud platforms, preferably Azure (Azure ML), with exposure to OCI considered a plus.
• Strong understanding of MLOps practices, including CI/CD pipelines and tools such as MLflow.
• Experience containerizing and deploying services using Docker and cloud-native services such as Azure App Service or Azure Container Apps.
• Familiarity with orchestration tools such as Apache Airflow or Azure Data Factory / Azure ML pipelines.
• Good understanding of scalable system design principles, including latency optimization, caching, batching, and rate limiting strategies.
• Experience with deep learning frameworks such as PyTorch or TensorFlow is a plus.
• Strong communication skills and ability to collaborate effectively in cross-functional engineering teams.

• Opportunity to grow within a rapidly scaling global technology organization.
• Exposure to cutting-edge AI, GenAI, and cloud technologies in production environments.
• People-first culture with strong emphasis on collaboration and innovation.
• Comprehensive group mediclaim insurance coverage for employee and family.
• Company-paid personal accident insurance for additional financial protection.
• Career advancement opportunities supported by leadership and approved development paths.
• Competitive referral bonus program.
• Generous leave policy with 29 paid days off annually.
• Paid maternity leave benefits for eligible employees.
• Inclusive and diverse workplace committed to equal opportunity and accessibility.