AI / ML Architect

Job Title: AI / ML Architect

Location: Pune

Experience required: 8+ years relevant

The AI Engineer Architect plays a pivotal role in enabling safe responsible and enterprise ready AI adoption within the Exponential Engineer Program This role focuses on demystifying AI for BFSI contexts teaching participants how to integrate AI capabilities into complex systems without compromising compliance security or reliability The trainer will guide engineers through AI lifecycle management risk mitigation and practical integration patterns ensuring AI becomes a governed system component rather than an uncontrolled bolton

Key Responsibilities

• Design and deliver comprehensive modules on AI system behavior lifecycle and failure modes contextualized for BFSI environments
• Teach integration patterns for AI services eg LLM APIs predictive analytics into enterprise applications using REST gRPC and event driven architectures
• Explain AI drift data and model bias and regulatory implications including GDPR PCI DSS and emerging AI governance frameworks
• Guide participants on embedding AI across the SDLC requirements AI discoverability design placement and boundaries development safe API consumption testing scenario expansion and operations drift monitoring
• Demonstrate secure AI consumption practices including prompt engineering for developers API authentication OAuth2OIDC and audit logging
• Collaborate with Full Stack Engineer and Data Architect trainers to ensure seamless integration of AI components with application and data layers
• Simulate real world BFSI project scenarios such as AI assisted credit risk scoring or fraud detection highlighting compliance and human in the loop controls
• Support capstone projects by reviewing AI integration strategies failure handling mechanisms and governance artefacts

Required Experience

• 8+ years of overall technology experience with at least 3-6 years in AIML systems engineering
• Hands-on experience integrating AI services into enterprise applications via APIs and SDKs
• Exposure to BFSI or other regulated domains with understanding of compliance and risk management
• Proficiency in Python for AI workflows and Java for enterprise integration contexts
• Familiarity with AI platforms and tools such as TensorFlow PyTorch conceptual OpenAI APIs Azure Cognitive Services or AWS AI services
• Experience implementing observability for AI components including logging metrics and drift detection

Core Skills Competencies

• Deep understanding of AI system behavior and lifecycle management
• Knowledge of BFSI regulatory frameworks and AI governance principles
• Ability to articulate complex AI concepts to non AI engineers and business stakeholders
• Strong collaboration skills for working with application and data architecture teams
• Expertise in riskware design failure mode analysis and human in the loop patterns
• Excellent communication and facilitation skills for workshops and executive presentations

Example Deliverables

Detailed training modules on AI lifecycle integration patterns and risk mitigation

Hands-on labs demonstrating secure AI API consumption and drift monitoring

Capstone project artefacts including AI integration design fallback strategies and compliance checklists

Reference architectures for AI enabled BFSI systems with documented governance controls

Preferred Certifications

Certified Artificial Intelligence Practitioner CAIP or equivalent

AWS Certified Machine Learning Specialty or Azure AI Engineer Associate

TOGAF or similar architecture certification added advantage

Reporting Collaboration

• Reports to Program Director Exponential Coach Collaborates closely with Full Stack Engineer Data Architect QA Architect and Business Analyst trainers to ensure cohesive delivery and integrated learning outcomes