Senior AI Engineer

We are looking for Ph.d professionals (only from Supply Chain, Logistics, Energy, Oil & Gas, Mining, Aerospace, and Industrial Manufacturing domains).

We are building cutting-edge AI solutions that transform operations across asset-intensive industries such as Supply Chain, Logistics, Energy, Mining, Aerospace, and Industrial Manufacturing. As an AI Engineer, you will play a critical role in designing, developing, and deploying scalable AI systems with a strong focus on Generative AI, Large Language Models (LLMs), and production-grade machine learning applications.

This role is ideal for someone with strong engineering depth who can bridge research and productionbuilding robust AI platforms, optimizing LLM workflows, and delivering high-impact solutions across forecasting, route optimization, anomaly detection, predictive maintenance, and intelligent automation.

With hands-on industry experience, you are expected to bring expertise in AI system design, ML engineering, LLM deployment, and scalable software development within fast-paced startup environments.

You Will :

• Design, build, and deploy production-grade AI/ML systems with strong emphasis on Generative AI and LLM-powered applications.

• Develop and optimize end-to-end LLM pipelines including RAG architectures, fine-tuning, prompt orchestration, evaluation, and observability.

• Build scalable backend services and APIs for AI applications using modern engineering best practices.

• Implement and productionize transformer-based models and GenAI workflows for enterprise use cases.

• Design vector search systems, embedding pipelines, and retrieval frameworks for knowledge-intensive applications.

• Partner closely with Product, Engineering, and Business teams to translate operational challenges into scalable AI solutions.

• Drive experimentation, benchmarking, model evaluation, and performance optimization with scientific rigor.

• Improve inference efficiency, latency optimization, cost management, and reliability of deployed AI systems.

• Establish guardrails, hallucination detection, monitoring, and responsible AI practices for production deployments.

• Contribute to MLOps workflows including CI/CD, model lifecycle management, observability, and cloud deployment.

• Stay current with the latest advancements in LLMs, agentic systems, foundation models, and applied AI engineering.

You'll Have :

• Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field.

• Hands-on industry experience in AI Engineering, Machine Learning Engineering, Applied AI, or related roles.