Roles & Responsibilities
- Project Delivery:
- Collaborate with client and internal stakeholders to 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 (both managed, e.g., EKS, and unmanaged) for production-grade AI/ML workloads.
- Develop and maintain robust DevOps pipelines to automate ML model training, deployment, and monitoring in cloud environments.
- Troubleshoot implementations and understand how to work with templates (e.g. Bogie), Jenkins logs, and implementations of LangChain and LangGraph in Python
- Independently seek and explore solutions to roadblocks before escalating
- Create detailed migration or modernization plans outlining approach, timeline, resources, dependencies, and risks.
- Evaluate applications and workloads for cloud and ML compatibility, identifying any modifications needed for seamless transitions.
- Implement Infrastructure as Code (IaC) principles to provision and manage cloud resources and AI/ML infrastructure reliably.
- Ensure adherence to best practices in cloud security, compliance, networking, and performance optimization.
- Communicate project plans, progress, and outcomes effectively with both technical and non-technical stakeholders.
- Leadership & Client Development:
- Serve as the primary point of contact for client technical stakeholders, building trusted relationships and ensuring high levels of satisfaction throughout engagements.
- Advise senior stakeholders by translating complex business problems into actionable AI/ML cloud architectures and solutions.
- Contribute actively in agile ceremonies, including stand-ups, sprint planning, and retrospectives, modeling effective team participation.
- Mentor and coach consultants and junior engineers on AI/ML concepts, Kubernetes, DevOps, and cloud best practices, fostering a collaborative team culture.
- Support pre-sales activities by interpreting client needs, scoping solutions, estimating efforts, and presenting proposals to prospective clients.
- Promote the Ippon brand through thought leadership activities, including blogging, speaking engagements, and participation in conferences and industry events.
- Identify opportunities to expand engagement scope, collaborating with Client Success and Sales teams to formalize new projects.
Competencies we are looking for:
- Minimum Requirements:
- 5+ years of professional experience in cloud engineering, AI/ML engineering, or MLOps, with a track record of delivering solutions in AWS environments.
- 5+ years demonstrated expertise deploying and managing Kubernetes clusters (both EKS and unmanaged).
- 2+ years hands-on experience with MLFlow or equivalent ML lifecycle management tools.
- 2+ years developing, maintaining, and debugging DevOps pipelines to support ML workflows.
- Deep expertise in DevOps practices, and modern cloud architecture.
- Proficiency with container orchestration, Kubernetes, and cloud-native design principles.
- Strong foundation in scripting (e.g., Python, Bash) and automation frameworks.
- Solid understanding of networking, cloud security, and scalability best practices.
- Experience working effectively in agile Scrum settings, with consistent contributions to stand-ups and team activities.
- Demonstrated ability to advise senior stakeholders and communicate directly with clients and internal teams.
- Ability to self-direct, conduct technical discovery, and work independently or collaboratively
- Preferred Requirements:
- Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related technical field.
- Prior consulting experience advising enterprise clients on AI/ML strategies and cloud-native architectures.
- AWS Certified Solutions Architect – Professional or equivalent advanced AWS certifications.
- Advanced knowledge of Kubernetes ecosystem tools such as Helm, ArgoCD, or Istio.
- Experience with additional MLOps tools (e.g., Kubeflow, SageMaker).
- Familiarity with security and compliance standards, encryption technologies, and disaster recovery best practices in cloud-based ML environments.
- Team lead or technical lead experience on AI/ML or cloud engineering projects.
- Proven consulting skills with the ability to build relationships and collaborate effectively across teams and with clients.
- Excellent communication and presentation skills, able to clearly articulate technical solutions and recommendations to both technical and business audiences.
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