MontyCloud is redefining CloudOps with AI-powered automation. Our AI team is leading efforts in intelligent CloudOps by making DAY2 cloud management effortless.

As a Lead AI Engineer, you will play a key role in building and scaling AI-first solutions that enhance developer efficiency, intelligent automation, and next-gen cloud autonomy. This role is ideal for those passionate about AI-driven automation and pioneering AI agents that transform cloud management.

• Design, develop, and scale AI-powered features across MontyCloud’s CloudOps Copilot and innovation initiatives.
  

• Lead and architect AI/ML integration across CloudOps Copilot and AI Innovation initiatives.

• Evaluate, fine-tune, and integrate existing AI/ML models (LLMs, NLP, etc.) into MontyCloud’s platform.
  

• Optimize AI inference pipelines for scalability, performance, and cost efficiency, including techniques like model distillation where applicable.
  

• Establish best practices for AI consumption, API-based model integration, and MLOps workflows.
  

• Collaborate with platform and data engineers to enable AI-powered cloud automation.
  

• Identify and implement AI applications for internal productivity tools across engineering, sales, and operations.
  

• Ensure responsible AI adoption, including model usage policies, bias mitigation, and continuous monitoring.
  

• Mentor AI engineers and work cross-functionally to drive AI-led innovation.
  

• 8+ Years of experience in AI/ML engineering, with 3+ years in a leadership role.
  

• Proven expertise in consuming and integrating AI/ML services and APIs (e.g., OpenAI, Hugging Face, AWS Bedrock, SageMaker).
  

• Strong proficiency in MLOps, AI inference optimization, RAG, Graph-RAG, model fine-tuning, and efficiency techniques such as model quantization, pruning, and model distillation.

• Hands-on experience with Python, API development, LangChain (or similar libraries), and vector databases.
  

• Deep knowledge of cloud platforms (AWS/GCP/Azure) and deploying AI models in cloud environments.
  

• Experience with Kubernetes, Docker, Terraform.

• Strong problem-solving skills with the ability to drive AI adoption across teams.
  

• Experience in AI-driven developer tools, automation, or cloud operations.
  

• Experience with serverless AI model deployment and cost-efficient hosting strategies.