About this role

Job Title: AI / ML Specialist L3

Key Responsibilities

Lead the design and architecture of AI / ML solutions for CEPT and customer use cases.

Identify high-impact AI use cases in consultation with domain teams, application teams and business

stakeholders.

Prepare technical architecture, solution design, implementation roadmap and feasibility assessment for AI

projects.

Guide L2 AI / ML developers in model development, coding standards, testing, deployment and documentation.

Design and implement enterprise-level AI solutions including predictive analytics, anomaly detection, fraud risk

scoring, NLP, GenAI, RAG-based knowledge systems and intelligent monitoring.

Define data requirements, model selection strategy, evaluation metrics and deployment approach.

Review model accuracy, bias, explainability, performance, scalability and security compliance.

Design MLOps pipelines for model versioning, deployment, monitoring, retraining and performance tracking.

Ensure secure and responsible use of AI, especially in handling government, citizen, employee and financial data.

Coordinate with DevOps, database, application, security and infrastructure teams for production deployment.

Review APIs, integration design and performance of AI models in production systems.

Prepare governance documents, model cards, risk assessment notes, security notes, SOPs and technical

documentation.

Conduct knowledge transfer, training and technical mentoring for CEPT officials and L2 resources.

Monitor performance of deployed AI solutions and recommend optimisation / retraining wherever required.

Provide L3-level support for critical AI / ML production issues.

Required Technical Skills

Strong expertise in Python and AI / ML frameworks such as TensorFlow, PyTorch, scikit-learn, Keras, XGBoost or

equivalent.

Strong understanding of supervised, unsupervised and deep learning techniques.

Expertise in NLP, LLMs, embeddings, vector databases, semantic search and RAG architecture.

Experience in Generative AI implementation, prompt engineering, model evaluation, guardrails and AI

governance.

Experience in fraud analytics, anomaly detection, predictive modelling, risk scoring and operational analytics.

Strong knowledge of databases, data pipelines, ETL, data quality and large-scale data processing.

Experience in API-based model deployment using FastAPI / Flask / Django or equivalent.

MLOps experience including Docker, Kubernetes, CI/CD, model monitoring, versioning and retraining workflows.

Exposure to cloud / on-premise AI infrastructure, GPU environments and scalable deployment architecture.

Knowledge of cybersecurity, data privacy, auditability and responsible AI principles.

Ability to prepare technical architecture documents, SOPs and governance frameworks.

Experience and Qualification

Experience: Minimum 5-8 years of experience in AI / ML, data science, enterprise analytics or AI solution

implementation.

For AI Architect / Lead role: 8-10 years of experience in enterprise AI architecture, MLOps, large-scale data

platforms and team leadership will be desirable.

Essential Qualification: Bachelor’s / Master’s degree in Computer Science / IT / Electronics / AI / Data Science /

Engineering or equivalent.

Desirable: Advanced certification in AI / ML / Data Science / Cloud / Cybersecurity.

Expected Deliverables

AI use case identification and prioritisation report.

Feasibility assessment and solution architecture documents.

Model design, review and validation reports.

MLOps and deployment architecture.

AI governance, security and risk assessment documents.

Production deployment plan and monitoring framework.

Technical review of L2 deliverables.

Training and knowledge transfer material.

Periodic performance and optimisation reports.