AI/ML Cloud Engineering Consultant

Roles & Responsibilities

• Project Delivery:
• Assess existing infrastructure, applications, and data workflows, including ML workloads, to determine requirements for modernization and MLOps integration.
• Design and implement scalable, secure AI/ML pipelines using MLFlow and related tools on AWS.
• Deploy, configure, and manage Kubernetes clusters (EKS or unmanaged) for production AI/ML workloads.
• Develop and maintain DevOps pipelines to automate ML model training, deployment, and monitoring.
• Troubleshoot LangChain and LangGraph scripts in Python, debug pipelines from logs and templates
• Create migration or modernization plans outlining the approach, timeline, and dependencies.
• Evaluate applications and workloads for cloud and ML compatibility, identifying needed modifications.
• Apply Infrastructure as Code (IaC) to provision and manage cloud resources reliably.
• Follow best practices in cloud security, compliance, networking, and performance optimization.
• Communicate project progress and outcomes effectively with technical and non-technical stakeholders.


• Collaboration & Knowledge Sharing:
• Work directly with client technical stakeholders to gather requirements and provide updates.
• Contribute actively to agile ceremonies, including stand-ups, sprint planning, and retrospectives.
• Share expertise with colleagues on AI/ML concepts, Kubernetes, DevOps, and cloud best practices.
• Support pre-sales activities by helping estimate efforts and contributing technical insights when needed.

Competencies we are looking for:

• Minimum Requirements:
• 3+ years of professional experience in cloud engineering, AI/ML engineering, or MLOps delivering solutions in AWS environments.
• 2+ years experience deploying and managing Kubernetes clusters (EKS and/or unmanaged).
• 1+ years experience  in building and maintaining DevOps pipelines for ML workflows with MLFlow or similar ML lifecycle management tools, including troubleshooting and debugging.
• Able to demonstrate solid knowledge of AI/ML engineering, DevOps practices, and modern cloud architecture in interviews.
• Able to demonstrate proficiency in container orchestration, Kubernetes, and cloud-native design principles with examples of past work and in interviews.
• Experience scripting (e.g., Python, Bash) and automating tasks.
• Understanding of networking, cloud security, and scalability best practices.
• Experience working effectively in agile Scrum teams.


• Preferred Requirements:
• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
• Prior consulting experience working with enterprise clients on AI/ML or cloud engineering projects.
• AWS Certifications (e.g., Solutions Architect – Associate or Professional).
• Experience with Kubernetes ecosystem tools like Helm, ArgoCD, or Istio.
• Familiarity with MLOps tools like Kubeflow or SageMaker.
• Knowledge of security, compliance standards, and disaster recovery practices in cloud environments.

What we offer:

• Great salary and benefits - Health (HDHP & PPO Plans), dental, and vision insurance, HSA, EAP, as well as a 401k with company match
• Work/life balance - Ippon offers generous PTO, parental leave, medical leave, and flexible schedules
• A fun, creative, and healthy work environment, focused on teamwork, knowledge-sharing, and exceptional delivery
• Opportunities to expand your portfolio and work with different companies and industries
• Career growth, up-skilling, cross-training, and leadership opportunities