Capgemini

Tokenization in Confidential AI

Posted On

Feb. 4, 2026

Location

Bangalore, Karnataka

Experience Level

Experienced Professionals

Job Type

Permanent

Apply By

Feb. 25, 2026

Job Description

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Your Role

We are seeking a skilled and experienced professional in Tokenization, Confidential AI , Python and privacy-preserving techniques into AI/ML to join our team across PAN India Location. The ideal candidate will have 6 to 12 years hands-on experience with Confidential AI and Tokenization and a strong understanding of security protocols, operating systems, and application onboarding processes.

Develop and integrate tokenization,, and privacy-preserving techniques into AI/ML training and inference pipelines.
Implement secure data‑in‑use protections using Confidential Compute technologies such as Intel SGX, AMD SEV, and GPU/TEE enclaves.
Build reusable security components across the AI lifecycle—data ingestion, feature engineering, model training, scoring, and output.
Collaborate with AI/ML teams, product owners, and data‑security stakeholders to define and enforce secure architecture patterns.
Validate model behavior using tokenized/obfuscated features and support explainability techniques like SHAP and integrity checks.
Ensure adherence to enterprise standards for encryption, key management, data handling, and privacy compliance.
Optimize the performance of secured AI workloads across on‑prem, GPU, and cloud‑native environments.
Design and integrate AI workloads with enterprise systems such as APIs, feature stores, vector databases, and batch/streaming pipelines.
Apply expertise in PKI, TLS, secure data‑movement frameworks, and containerized deployments (Docker/Kubernetes).
Prepare architectural documentation, design artifacts, and best‑practice guidelines to support secure AI adoption across business units.

Your Profile

3 to 12 years of experience in Develop and integrate tokenization, Confidential AI, Python and privacy-preserving techniques into AI/ML training and inference pipelines.
Strong understanding of AI, Middleware, IAM, Cloud & containerized deployments .
Experience in onboarding various platforms (Applications, Databases, Storage) into encryption tools.
Familiarity with Public Key Infrastructure (PKI) is a plus.

What you'll love about working here

You can shape your career with us. We offer a range of career paths and internal opportunities within Capgemini group. You will also get personalized career guidance from our leaders.
You will get comprehensive wellness benefits including health checks, telemedicine, insurance with top-ups, elder care, partner coverage or new parent support via flexible work.
At Capgemini, you can work on cutting-edge projects in tech and engineering with industry leaders or create solutions to overcome societal and environmental challenges

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of €22.1 billion.
Make it real | www.capgemini.com

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