Zensar Technologies - AI Architect

AI Architect

Job Description :

We are seeking a AI Architect to lead strategic AI transformation initiatives within the Banking, Financial Services, and Insurance (BFSI) domain. This role demands deep hands-on experience in AI, Machine Learning (ML), and Generative AI (GenAI), along with the ability to engage directly with C-level stakeholders, align technical delivery with business objectives, and drive enterprise-wide adoption of advanced AI solutions. The ideal candidate is a techno-strategic leader who can take AI/ML/GenAI projects from ideation to productionbuilding architectures, leading cross-functional teams, and ensuring regulatory and operational alignment in BFSI environments.

Key Responsibilities :

- Define and articulate a clear and compelling AI vision and strategy for the BFSI domain, aligning with business goals, regulatory frameworks, and competitive landscape.

- Lead the identification and prioritization of high-impact AI/ML/GenAI use cases across various BFSI functions (e.g., risk management, customer experience, fraud detection, compliance, lending, wealth management, insurance underwriting).

- Engage directly with C-level stakeholders to understand their strategic priorities, present AI capabilities, and build consensus around AI-driven transformation initiatives.

- Architect scalable, secure, and robust AI/ML/GenAI solutions tailored to the specific needs and constraints of the BFSI industry.

- Design end-to-end AI pipelines, including data ingestion, preprocessing, feature engineering, model development, deployment, monitoring, and governance.

- Select appropriate AI/ML algorithms and GenAI models based on business requirements, data characteristics, and performance metrics.

- Define the technology stack and infrastructure requirements for AI/ML/GenAI platforms, considering on-premise, cloud, and hybrid environments.

- Leverage deep understanding of the BFSI domain, including industry-specific processes, data nuances, and regulatory requirements (e.g., GDPR, CCPA, KYC/AML, data privacy laws specific to financial services and insurance).

- Design AI solutions that adhere to relevant regulatory guidelines, ethical considerations, and risk management frameworks within the BFSI sector.

- Collaborate with legal and compliance teams to ensure AI deployments meet all necessary requirements.

- Develop and implement strategies for leveraging Generative AI technologies (e.g., Large Language Models, diffusion models) to create innovative solutions within the BFSI domain (e.g., content generation, synthetic data, enhanced customer interactions, code generation).

- Evaluate and select appropriate GenAI models and frameworks, considering factors like performance, cost, and ethical implications.

- Lead and mentor cross-functional teams of data scientists, ML engineers, software developers, and business analysts throughout the AI project lifecycle.

- Provide technical guidance, architectural oversight, and ensure effective collaboration to deliver high-quality AI solutions.

- Foster a culture of innovation, experimentation, and continuous learning within the AI team.

- Define and oversee the development and maintenance of a centralized AI/ML/GenAI platform that enables efficient model development, deployment, and management.

- Establish robust AI governance frameworks, including model validation, monitoring, explainability, and responsible AI practices.

- Implement best practices for MLOps (Machine Learning Operations) to streamline the deployment and scaling of AI models in production.

- Stay abreast of the latest advancements in AI, ML, and GenAI technologies, evaluating their potential applicability and value within the BFSI context.

- Drive the adoption of new tools, frameworks, and methodologies to enhance the organization's AI capabilities.

- Define key performance indicators (KPIs) for AI models and solutions.

- Implement robust monitoring systems to track model performance, identify drift, and trigger retraining or remediation processes.

- Drive continuous optimization of AI models and infrastructure for efficiency and accuracy.

Required Skills :

- Deep Expertise in AI/ML : Extensive hands-on experience (10+ years) in designing, developing, and deploying AI and Machine Learning models using various algorithms and techniques (e.g., supervised learning, unsupervised learning, deep learning, natural language processing, time series analysis).

- Generative AI Proficiency : Strong understanding and practical experience with Generative AI concepts, models (e.g., LLMs, Transformers), and frameworks.

- BFSI Domain Acumen : Significant and demonstrable experience working within the Banking, Financial Services, and Insurance (BFSI) domain, with a strong understanding of industry-specific challenges, data characteristics, and regulatory landscape.

- Cloud Platforms : Extensive experience with at least one major cloud platform (AWS, Azure, GCP) and its AI/ML/GenAI services (e.g., SageMaker, Azure Machine Learning, Vertex AI).

- Programming Proficiency : Strong proficiency in Python and relevant AI/ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Transformers).

- Data Engineering Fundamentals : Solid understanding of data engineering principles, data warehousing concepts, and experience working with large datasets and data pipelines.

- API Development & Integration : Experience in designing and implementing APIs for integrating AI models with other systems.

- MLOps Practices : Familiarity with MLOps principles and tools for automating and managing the ML lifecycle.

- Communication & Presentation Skills : Excellent verbal and written communication skills, with the ability to effectively communicate complex technical concepts to both technical and non-technical audiences, including C-level executives.

- Leadership & Collaboration : Proven ability to lead and mentor technical teams and collaborate effectively with cross-functional stakeholders.

- Problem-Solving & Analytical Skills : Strong analytical and problem-solving skills with the ability to translate business challenges into technical solutions.

- Understanding of AI Ethics & Responsible AI : Knowledge of ethical considerations and responsible AI practices, particularly within the context of the BFSI industry.

Preferred Skills :

- Advanced degrees (Master's or PhD) in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

- Experience with specific BFSI use cases (e.g., credit risk modeling, fraud detection, algorithmic trading, personalized banking, insurance claims processing).

- Familiarity with data governance frameworks and tools relevant to the BFSI sector.

- Experience with deploying AI models in production environments with high scalability and reliability requirements.

- Knowledge of containerization technologies (Docker, Kubernetes).

- Experience with specific GenAI use cases within BFSI (intelligent document processing, virtual assistants, synthetic data generation for model training).

- Relevant certifications in AI/ML or cloud platforms.