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AI Security Architect - Manager
Grant Thornton INDUS —Kolkata, West Bengal
- Azure
- Master's degree
- AWS

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AI Security Architect - Manager
Grant Thornton INDUS —Kolkata, West Bengal
We are seeking a highly experienced Principal AI/ML Architect with 12+ years of experience to lead the design and development of enterprise-scale AI platforms,…

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AI Security Architect - Manager

Grant Thornton INDUS -
Kolkata, West Bengal

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Job details

Qualifications

TensorFlow
CI/CD
Azure
Cloud architecture
Law
Kubernetes
PyTorch
Master's degree
Microservices
AWS
Docker
Product development
Machine learning
Distributed systems
Continuous integration
APIs
S3
Data science
Redshift
AI
Python
Analytics

Full job description

Job ID: 865220

10 - 15 Years

1 Opening

Bengaluru, Kolkata

Role description

We are seeking a highly experienced Principal AI/ML Architect with 12+ years of experience to lead the design and development of enterprise-scale AI platforms, including agentic AI systems and generative AI solutions.

This role requires deep expertise in LLM architecture, AI product development, and advanced analytics, combined with strong engineering foundations in cloud, MLOps, and distributed systems. You will drive end-to-end AI strategy—from research and prototyping to production deployment—while ensuring responsible and governed AI adoption.

Key Responsibilities

AI & GenAI Architecture

Design and implement scalable AI platforms supporting agentic AI systems and autonomous workflows
Architect and optimize LLM-based systems, including fine-tuning, inference, and orchestration
Build advanced RAG (Retrieval-Augmented Generation) pipelines and multi-agent systems
Develop multimodal AI systems (text, image, audio) for enterprise use cases
Lead AI product development from concept to production deployment

Machine Learning & Advanced Analytics

Develop and deploy predictive models and advanced analytics solutions
Design scalable ML systems for real-time and batch processing
Implement optimization techniques such as PEFT, LoRA, QLoRA, and mixed precision training
Apply reinforcement learning approaches including RLHF (Reinforcement Learning with Human Feedback)
Ensure robustness using frameworks like RAG Triad (retrieval, augmentation, generation evaluation)

Architecture & Engineering

Design systems using microservices and hexagonal architecture patterns
Build and maintain scalable data pipelines and API integrations
Ensure seamless integration between AI services and enterprise platforms
Lead system design reviews and ensure high availability, scalability, and security

MLOps & Platform Engineering

Implement end-to-end MLOps pipelines, including CI/CD for ML systems
Deploy and manage models using Kubernetes and Docker
Establish model monitoring, drift detection, and performance tracking
Automate model lifecycle management and continuous retraining workflows

Cloud & Data Platforms

Architect and manage AI workloads across cloud platforms:

AWS (S3, SageMaker, Redshift, Glue)
GCP and Azure ecosystems

Work with modern data platforms such as Databricks and Cosmos DB
Optimize large-scale data processing and storage for AI workloads

Responsible AI & Governance

Define and implement AI governance frameworks
Ensure compliance with responsible AI principles (fairness, explainability, transparency)
Implement guardrails and safety mechanisms for LLM systems
Align AI systems with enterprise risk, compliance, and regulatory requirements

Skills

12+ years of experience in AI/ML engineering, architecture, or data science
Strong expertise in Generative AI and LLM architectures
Proven experience building AI products at scale
Deep understanding of agentic AI systems and autonomous agents
Expertise in advanced analytics and predictive modeling

Technical Expertise

AI frameworks: LangChain, LangGraph, RAG, RLHF, multimodal AI
LLM optimization: PEFT, LoRA, QLoRA, mixed precision
Strong experience with Python and ML frameworks (PyTorch, TensorFlow)
MLOps: CI/CD pipelines, model monitoring, lifecycle management
Containers & orchestration: Kubernetes, Docker
Architecture: microservices, hexagonal architecture

Cloud & Data Expertise

Strong experience with:

AWS (S3, SageMaker, Redshift, Glue)
GCP and Azure
Databricks, Cosmos DB

Experience designing large-scale data pipelines and distributed systems

Preferred Qualifications

Experience leading AI/ML teams or large-scale transformation programs
Strong background in AI platform engineering
Experience with multi-agent orchestration frameworks
Knowledge of AI security and adversarial ML
Contributions to AI research, patents, or open-source projects

About Grant Thornton INDUS

‘Grant Thornton INDUS’ comprises GT U.S. Shared Services Center India Pvt Ltd and Grant Thornton U.S. Knowledge and Capability Center India Pvt Ltd. Grant Thornton INDUS is the shared services center supporting the operations of Grant Thornton LLP, the U.S. member firm of Grant Thornton International Ltd. Established in 2012, Grant Thornton INDUS employs professionals across a wide range of disciplines including Tax, Audit, Advisory, and other operational functions. What sets us apart isn’t just what we do – it’s how we do it. We support and enable the firm’s purpose of making business more personal and building trust into every result. We’re collaborators – obsessed with quality and ready for anything – who understand the value of strong relationships. Our professionals are well integrated to seamlessly support the U.S. engagement teams, help increase Grant Thornton’s access to a wide talent pool, and improve operational efficiencies. Empowered people, bold leadership, and distinctive client service are imbibed in the culture at Grant Thornton INDUS. We are a transparent, competitive, and excellence-driven firm that offers an opportunity to be part of something significant. In addition, professionals at Grant Thornton INDUS serve communities in India through inspirational and generous services to give back to the communities they work in. Grant Thornton INDUS has its offices in two locations in India – Bengaluru and Kolkata

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