Technical Architect

2 days ago

Chicago, United States Echo Global Logistics Full time
Echo Global Logistics is a leading provider of technology-enabled transportation management services. As a third-party logistics provider, we simplify transportation management for our clients and carriers, handling crucial tasks so they can focus on what they do best. From coast to coast, dock to dock, and across all major transportation modes, Echo connects businesses that need to ship their products with carriers who transport goods quickly, securely, and cost-effectively.Position Overview

As an Technical Architect with a focus on Artificial Intelligence and MLOps, you will lead the architecture, design, and integration of AI-driven solutions across the enterprise. This role requires extensive experience in architecting data science platforms, MLOps pipelines, and designing data structures for large-scale AI models. You will collaborate with business and technical teams to address complex challenges, drive the adoption of AI technologies, and ensure scalable, high-performance solutions that align with business goals.

Job Duties & Responsibilities
  • Architect and design AI, Data Science, and MLOps solutions that scale across the enterprise, supporting both experimentation and production environments.
  • Develop a deep understanding of business needs and technical roadmaps to architect cross-functional solutions for data science initiatives.
  • Design data structures and databases that effectively support machine learning models, AI workloads, and data-driven applications.
  • Lead efforts to build and optimize MLOps pipelines to enable seamless model development, testing, deployment, and monitoring across the enterprise.
  • Decompose AI/ML challenges into technical components such as data ingestion pipelines, feature stores, model repositories, and API endpoints, and produce detailed architectural documentation.
  • Collaborate with data scientists, engineers, and DevOps teams to ensure smooth integration of AI models into business applications.
  • Provide technical leadership in the evaluation and selection of AI platforms, tools, and frameworks for model training, versioning, and lifecycle management.
  • Ensure solutions adhere to enterprise architecture standards, including security, scalability, performance, and compliance requirements.
  • Identify and mitigate architectural risks related to AI/ML solutions, including issues related to data integrity, model performance, and operationalization challenges.
  • Lead knowledge-sharing sessions to align stakeholders on technical architectures and solutions.
  • Continuously evaluate emerging technologies and trends in AI, machine learning, and data science, incorporating these into the organization‘s technology roadmap.

Required Skills

  • BA or BS, preferably in Computer Science, Engineering, Data Science, or related discipline, or equivalent work experience.
  • 10+ years of hands-on experience in the design and implementation of complex, high-volume software systems, with at least 5+ years focusing on AI/ML architecture, data science solutions, and MLOps.
  • Expertise in data architecture, including designing and optimizing data structures for large-scale machine learning models and AI applications.
  • Extensive experience with MLOps frameworks (e.g., Kubeflow, MLflow, Seldon) and cloud-based data science platforms (AWS Sagemaker, Google AI, or Azure AI).
  • Proven experience in building end-to-end AI/ML solutions - from data pipelines to model deployment and monitoring.
  • Strong knowledge of machine learning algorithms model lifecycle management, and model deployment best practices.
  • Expertise in cloud architectures (AWS, Azure, GCP), containerization (Docker, Kubernetes), and CI/CD pipelines.
  • Experience in designing and developing event-driven architectures* microservices, and API-based integrations.
  • Solid understanding of enterprise security best practices for AI, including secure model access, data privacy, and compliance.
  • Experience with relational and NoSQL databases to support AI/ML data storage and retrieval.
  • Leadership experience mentoring and guiding technical teams in AI, MLOps, and data science.

Preferred Skills
  • Cloud certifications - preferably AWS Certified Solutions Architect or Machine Learning.
  • Hands-on experience with AI governance frameworks to ensure compliance and ethical AI practices.
  • Experience with enterprise-level digital transformation projects that leverage AI and automation.

Work environment/physical demands summary:

This job operates in an office environment and uses a computer, telephone and other

office equipment as needed to perform duties. The noise level in the work environment is typical of

that of an office with an open seating floor plan. The employee may encounter frequent interruptions throughout the work day. The employee is regularly required to sit, talk, or hear.

All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, status as a qualified individual with a disability, or Vietnam era or other protected veteran.

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