AI Solutions Lead

Job Summary:
We are looking for an AI Solutions Lead  to support our ongoing critical project activities. The ideal candidate is responsible for lead the architecture, design, and end-to-end delivery of complex AI/ML solutions and translate business requirements into scalable and secure AI system architectures.

Key Responsibilities:
*Lead the architecture, design, and end-to-end delivery of complex AI/ML solutions.
*Define and implement AI strategy in alignment with enterprise goals and digital transformation initiatives.
*Translate business requirements into scalable and secure AI system architectures.
*Oversee the development and deployment of AI/ML models in production environments.
*Guide data scientists, engineers, and developers in adopting AI best practices and technologies.
*Drive MLOps and AI lifecycle automation including model training, versioning, testing, deployment, and monitoring.
*Design AI solutions integrated with enterprise platforms (Microsoft, Salesforce, ERP, CRM, data lakes, APIs).
*Ensure responsible AI practices, including ethical considerations, bias mitigation, and regulatory compliance.
*Collaborate with C-level stakeholders and business units to assess use cases, prioritize projects, and define success metrics.
*Mentor and lead technical teams; influence architectural decisions across business units.

Role Requirements and Qualifications:
1.AI/ML Expertise:
*Strong knowledge of machine learning, deep learning, NLP, computer vision, and generative AI.
*Hands-on experience with frameworks like TensorFlow, PyTorch, Scikit-learn, Hugging Face, OpenAI APIs.
2.Architecture & System Design:
*Proven experience in designing scalable and secure cloud-native AI solutions.
*Deep understanding of microservices, APIs, event-driven architectures, and real-time inference systems.
3.MLOps & DevOps:
*Experience with tools like MLflow, Kubeflow, Airflow, SageMaker Pipelines, Vertex AI Pipelines.
*Knowledge of CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes).
4.Data & Integration:
*Familiarity with data engineering tools (Spark, Kafka), data lakehouses (Delta Lake, Snowflake), and ETL pipelines.
*Ability to integrate AI with enterprise platforms and legacy systems via RESTful APIs or middleware.
*Strong leadership experience managing multidisciplinary AI/ML teams.
*Ability to drive architecture governance, code quality, and technical standards.
*Excellent communication and presentation skills to influence technical and non-technical stakeholders.
*Strategic thinker with a passion for AI innovation and enterprise transformation.

Preferred Experience:
*10+ years of experience in software or data architecture roles, with 4–5 years focused on AI/ML.
*Track record of delivering AI projects at scale in one or more of the following domains: financial services, healthcare, government, telecom, or retail.
*Familiarity with regulatory frameworks for data and AI (e.g., GDPR, HIPAA, ISO 42001).
*Preferred Certifications:
*AWS Certified Machine Learning – Specialty
*Microsoft Azure AI Engineer Associate
*Google Professional Machine Learning Engineer
*TOGAF or other architecture frameworks (optional but valuable)
*Responsible AI or ethical AI certifications (optional)