AI Architect

Job Summary

This role combines deep technical expertise, business acumen, and people leadership, enabling the delivery of scalable, secure, and compliant AI solutions across the enterprise.

What is the Opportunity?

As an AI Architect, you will play a key role in shaping AI strategy within risk and compliance. You will design enterprise-grade AI architectures, lead multi-disciplinary teams, and partner with business stakeholders to deliver solutions that are aligned with regulatory expectations and business priorities.

You will work at the intersection of data, technology, and risk, leveraging advanced analytics, PySpark-based data platforms, and Generative AI (LLMs) to drive meaningful outcomes.

What Will You Do?

Lead AI Architecture & Innovation

• Design and implement end-to-end AI/ML and Generative AI architectures
• Define standards for multi-LLM orchestration, RAG pipelines, and AI governance
• Ensure solutions are scalable, secure, explainable, and aligned with regulatory requirements

Hands-On Development & Engineering

• Build and optimize large-scale data pipelines using PySpark
• Develop AI/ML models using Python, TensorFlow, PyTorch, Scikit-learn
• Implement LLM-powered applications using frameworks such as LangChain, LlamaIndex, Hugging Face
• Work across multiple LLM platforms (enterprise and open-source)
• Develop APIs and microservices to operationalize AI solutions

Lead & Develop High-Performing Teams

• Lead a cross-functional team of developers, data engineers, and business analysts
• Provide technical leadership, mentorship, and code review oversight
• Drive agile delivery practices, including sprint planning and solution design sessions
• Partner with business analysts to ensure clear translation of business needs into technical solutions

Deliver Risk & Compliance Solutions

• Lead AI initiatives across: Credit Risk, Fraud Detection ,KYC & Transaction Monitoring ,Regulatory Reporting
• Ensure compliance with model risk management, explainability, and audit requirements

Build Scalable Data & AI Platforms

• Architect data solutions leveraging PySpark, Spark, and distributed data ecosystems
• Enable ingestion and processing of structured and unstructured data for AI/LLM use cases
• Implement data governance, lineage, and quality controls

Enable MLOps & LLMOps

• Establish end-to-end MLOps pipelines for model lifecycle management
• Implement LLMOps practices including prompt management, evaluation, and optimization
• Monitor model performance, drift, bias, and compliance risks

Collaborate & Influence

• Partner with risk, compliance, and business leaders to define AI opportunities
• Communicate complex technical concepts in a clear, business-focused manner
• Lead workshops, stakeholder sessions, and executive presentations

What Do You Need to Succeed?

Must-have

• 8+ years of experience in AI/ML, data engineering, or related fields
• 3+ years in architecture and team leadership roles
• Strong hands-on expertise in: Python and PySpark
• Strong hands-on expertise in AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn)
• Experience with Generative AI and multiple LLMs
• Proven experience in banking or financial services, with focus on risk and compliance
• Demonstrated experience leading cross-functional teams (developers and business analysts)
• Strong understanding of model governance and regulatory frameworks

Nice-to-have

• Experience with LangChain, Hugging Face
• Knowledge of vector databases (Pinecone, FAISS, Weaviate)
• Experience with real-time data processing (Kafka, Spark Streaming)
• Familiarity with cloud platforms (AWS, Azure, GCP)
• Understanding of Responsible AI and Explainable AI (XAI)