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 45 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)
Why Join Us
• Opportunities to work on transformative projects, cutting edge technology and innovative solutions with leading global firms across industry sectors.
• Continuous investment in employee growth and professional development with a strong focus on up & re skilling.
• Competitive compensation & benefits, ESOPs and international assignments.
• Supportive environment with healthy work life balance and a focus on employee well being.
• Open culture that values diverse perspectives, encourages transparent communication and rewards contributions.
