Principal Architect – AI/ML

Company Description Synergech is a cross-border technology solutions provider specializing in digital and business process solutions for a diverse range of clients.

The company focuses on automating and streamlining processes to improve efficiency, ensure compliance, and reduce operational costs.

Synergech leverages state-of-the-art digital services to support organizations through end-to-end transformation journeys.

By using cutting-edge tools and technologies, the company helps clients enhance customer engagement and deliver seamless omnichannel experiences across the entire customer lifecycle.

Role Description The Principal Architect – AI/ML will lead the design and implementation of end-to-end AI and machine learning architectures that power Synergech’s digital and business process solutions.

This full-time, on-site role in Raleigh, NC involves working closely with product, engineering, and business stakeholders to define AI/ML roadmaps, select appropriate technologies, and ensure solutions are scalable, secure, and aligned with client needs.

Day-to-day responsibilities include architecting data pipelines and model deployment frameworks, reviewing solution designs, guiding teams on best practices, and performing technical due diligence for new initiatives. The Principal Architect will also mentor AI/ML engineers and data scientists, establish coding and model governance standards, and stay current with emerging tools and frameworks to continuously improve the organization’s AI capabilities.

Qualifications

• Strong expertise in AI/ML solution architecture, including designing end-to-end systems for model development, deployment, monitoring, and lifecycle management.

• Hands-on experience with machine learning and deep learning techniques, such as supervised and unsupervised learning, NLP, recommendation systems, and computer vision (as relevant to business needs).

• Proficiency with common AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, Spark ML, MLflow, Kubeflow, or equivalent platforms).

• Solid background in data engineering concepts, including data modeling, ETL/ELT pipelines, streaming/batch processing, and integration with data lakes and warehouses.

• Experience designing cloud-native AI/ML solutions on major cloud platforms (e.g., AWS, Azure, or GCP), including use of managed AI/ML services and containerization/orchestration.

• Strong software engineering practices, including object-oriented programming, version control, CI/CD for ML workflows, testing, and code review.

• Proven ability to translate business requirements into AI/ML solutions, including stakeholder engagement, requirements gathering, and clear communication of technical trade-offs.

• Demonstrated leadership in mentoring technical teams, setting standards, and driving architectural decisions in complex, multi-team environments.

• Excellent problem-solving skills, with a focus on performance, scalability, security