[Hiring] Senior AI & MLOps Engineer @INFOYA

Role Description

This is a remote position. Infoya is looking for a hands-on Senior AI & MLOps Engineer with strong expertise in Agentic AI, GenAI, cloud engineering and MLOps/LLMOps. The candidate will be responsible for deploying and managing Infoya's AI-powered products across enterprise cloud environments, ensuring scalability, security and production reliability. The role requires strong technical expertise along with the ability to independently engage with client architects, infrastructure teams and business stakeholders.

Key Responsibilities

• Deploy and manage Agentic AI/GenAI solutions across AWS, Azure and GCP, including private and hybrid cloud environments.
• Design and implement scalable, secure cloud architectures for AI applications.
• Build and manage CI/CD pipelines, containerization and deployment automation.
• Implement MLOps/LLMOps practices, AI monitoring, observability and performance optimization.
• Integrate AI platforms with enterprise applications, APIs, databases and authentication systems.
• Work directly with client cloud, infrastructure and security teams to manage deployments and resolve technical challenges.
• Own end-to-end technical implementation from POC to production go-live.
• Collaborate with internal AI product engineering teams to improve deployment efficiency and reliability.

Qualifications

• AI/GenAI: LLMs, Agentic AI, RAG, Python, LangChain/LangGraph.
• Cloud: Strong hands-on expertise in at least two of AWS, Azure and GCP.
• DevOps: Docker, Kubernetes, Terraform, Helm, CI/CD.
• MLOps/LLMOps: MLflow, Vertex AI, Azure ML, SageMaker or equivalent tools.
• Monitoring: Prometheus, Grafana, OpenTelemetry or equivalent.
• Security: IAM, RBAC, OAuth, cloud networking and secrets management.
• Soft Skills: Strong client communication, stakeholder management and problem-solving.

Requirements

• 7–12 years of overall IT experience.
• 4+ years in Cloud/DevOps/MLOps engineering.
• 2+ years of hands-on AI/GenAI application deployment or integration.
• Proven experience deploying enterprise applications into production.
• Ability to independently manage client technical discussions and deployment challenges.

Preferred

• Experience deploying Agentic AI products in enterprise environments.
• Multi-cloud, private cloud or hybrid cloud deployment experience.
• AWS, Azure or GCP certifications.