Artificial Intelligence (AI) Solution Architect

A leading global professional services firm specializing in technology-driven solutions for enterprise clients across industries such as finance, healthcare, and manufacturing. With a commitment to innovation, the company delivers commissioning, validation, and IT services, empowering clients to achieve operational excellence through cutting-edge technologies like AI and machine learning.

Responsibilities

Design and implement scalable AI/ML solutions, including data pipelines, model development, and deployment, to address client business challenges; Collaborate with stakeholders to gather requirements, translate business needs into technical architectures, and present solutions to technical and executive audiences; Build and deploy AI/ML models using cloud platforms (e.g., AWS, Azure, GCP) and frameworks (e.g., TensorFlow, PyTorch), ensuring alignment with business objectives; Lead discovery sessions and workshops to define AI use cases, develop proofs-of-concept (PoCs), and validate technical feasibility; Mentor junior architects and engineers, fostering expertise in AI/ML methodologies and ensuring adherence to best practices; Monitor emerging AI/ML trends and technologies, integrating innovative approaches into solution designs; Ensure solutions comply with industry standards (e.g., SOC2, ISO 27001) and cybersecurity policies, particularly for regulated industries.

Requirements

US citizenship or permanent residency required; visa sponsorship not available; Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; 5+ years of experience in solutions architecture or a related role, with at least 2 years focused on AI/ML model development and deployment; Proficiency in programming languages such as Python, Java, or Scala, and AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn); Strong experience with cloud platforms (AWS, Azure, or GCP) and MLOps tools (e.g., MLFlow, Weights & Biases); Hands-on experience with data science pipelines, including feature engineering, model training, and deployment; Excellent communication skills for presenting technical concepts to diverse audiences, including C-level executives.

Nice to have

Master’s or Ph.D. preferred; Experience in regulated industries (e.g., finance, healthcare) or federal projects is a plus; Preferred certifications: AWS Certified Machine Learning – Specialty, Google Cloud Professional ML Engineer, or equivalent.

Benefits

15% bonus; Competitive salary with performance-based bonuses; Comprehensive health, dental, and vision insurance; 401(k) plan with company match; Paid time off, including vacation, sick leave, and holidays; Professional development opportunities, including training and certification support; Flexible hybrid work environment with opportunities for remote work; Access to cutting-edge technologies and collaborative projects with global clients.