Note: The job is a remote job and is open to candidates in USA. Momento USA is a global technology consulting firm seeking an AI Platform Lead Engineer. The role involves leading the technical strategy for AI/ML platforms, architecting robust AI infrastructure, and mentoring engineering teams to deliver innovative AI solutions that drive business transformation.

Responsibilities

• Implement the AWS and per the approved architecture and security design
• Build and maintain landing zones, accounts, networking, IAM, and Snowflake account/role structures
• Operate as the on-the-ground infrastructure lead, coordinating closely with customer security and cloud teams
• Enable AI Engineers with reusable platform components (Bedrock setup, Cortex enablement, secure data zones)
• Drive infrastructure code reviews, environment promotions, and platform governance
• Design and implement scalable AI/ML platforms supporting model training, deployment, monitoring, and lifecycle management
• Drive adoption of cloud-native and hybrid architectures for AI workloads
• Ensure platform reliability, performance, and security at scale
• Lead cross-functional engineering teams, providing technical guidance and mentorship
• Collaborate with product, data science, and business stakeholders to align AI platform capabilities with organizational goals
• Define long-term AI infrastructure strategy and roadmap
• Establish best practices for MLOps, CI/CD pipelines, and automated workflows
• Implement monitoring, observability, and governance frameworks for AI models
• Optimize cost efficiency and resource utilization across cloud and on-prem environments
• Stay ahead of emerging AI/ML technologies, frameworks, and tools
• Evaluate and integrate new solutions to enhance platform capabilities
• Champion innovation by fostering a culture of experimentation and continuous improvement

Skills

• 14+ years of experience in software engineering, with at least 5+ years focused on AI/ML platforms
• Proven expertise in cloud platforms (Azure, AWS, Google Cloud Platform) and container orchestration (Kubernetes, Docker)
• Strong knowledge of MLOps frameworks (Kubeflow, MLflow, SageMaker, Vertex AI)
• Hands-on experience with distributed systems, data pipelines, and model deployment at scale
• Proficiency in programming languages such as Python, Java, or Go
• Deep understanding of AI/ML lifecycle management, including monitoring, retraining, and governance
• Excellent leadership, communication, and stakeholder management skills
• Experience in building Enterprise AI platforms for large-scale organizations
• Familiarity with data engineering tools (Spark, Kafka, Databricks)
• Exposure to generative AI and LLM deployment frameworks
• Track record of leading global teams and delivering complex AI initiatives

Company Overview

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