AI/ML Solution Architect

• Demonstrated experience with:
• Hands-on development of end-to-end AI solutions to solve complex business problems.
• Cloud services and infrastructure with platforms such as AWS, Microsoft Azure, or Google Cloud.
• Have built or deployed systems powered by LLMs or generative models and understand how model behavior affects product experience.
• Proficiency in programming languages for AI development such as Python, R, or SQL, with experience in libraries/frameworks such as TensorFlow, PyTorch, Scikit-learn, Langchain, etc.
• Experience with big data technologies such as Hadoop and Spark.
• Implementing required security and privacy controls when developing AI-enabled prototypes, including proper data handling, masking/anonymization, and secure storage based on defined standards.
• Applying cloud platform security features (e.g., encryption, identity and access management, secure API integrations) to ensure AI applications adhere to enterprise and regulatory requirements.
• Executing security-related tasks such as integrating authentication, enforcing role-based access, and configuring secure data pipelines as part of delivering production-ready AI solutions.
• Identifying and addressing security or privacy considerations during development and proactively collaborating with security stakeholders to validate implementation.
• Documenting security-relevant design decisions, data flows, and privacy considerations to support Responsible AI practices and audit transparency.
• Collaborating with internal stakeholders to create AI-enabled solutions for repeatable business problems and develop functional prototypes to validate feasibility and applicability of AI technologies to practical use cases and challenges.
• Fostering innovation by identifying new AI technologies or methodologies that can enhance current processes or solve new challenges.
• Establishing best practices in AI governance principles ensuring ethical use, transparency, risk management while delivering high-quality services to clients.
• Leadership and direct supervisory experience of teams include conducting performance appraisals, mentoring and coaching, oversight and review of work, coordination across teams, and understanding how to motivate.

Your Educational And Professional Qualifications

• Bachelor’s degree in a relevant discipline (e.g., Computer Science or related field).
• 5+ years working in professional services or industry.
• A minimum of 3-year hands-on experience with Generative Artificial Intelligence technology experimentation, prototyping, solutioning and deployment.
• Familiarity with cloud-based AI technologies and platforms is strongly preferred.
• Professional Certification such as AWS Certified Solutions Architect or Azure Solutions Architect are preferred.