Nadeem Ahmad

Leading enterprise GenAI platform architecture on Amazon Bedrock for regulated financial services clients — where accuracy, governance, and audit traceability are non-negotiable.

▸ Architected multi-agent AI system using Amazon Bedrock (Claude 3.5 Sonnet) — specialised Extraction and Inference agents for processing unstructured enterprise communications at scale. ▸ Designed serverless AI pipelines using AWS Lambda with synchronous invocation — optimised for low latency, compliance-critical financial services workflows. ▸ Built enterprise data integration layer (DynamoDB + PostgreSQL) with confidence-based human-in-the-loop validation — ensuring every AI decision is auditable and explainable. ▸ Designed LLM evaluation pipelines using curated datasets — monitoring accuracy, detecting hallucination, and maintaining production-grade model governance continuously. ▸ Defining enterprise AI governance frameworks: model evaluation, drift monitoring, compliance controls, and full audit traceability across financial services programs.

9 years progressively evolving from deep telecom engineering (BSS/OSS, charging, VoLTE) through supply chain and cloud-native architecture to enterprise AI — delivering production AI systems for Tier-1 operators and FinTech clients across EU, APAC, and MEA.

▸ Delivered AI-driven 5G network change automation: 70% reduction in manual effort, 3+ weeks faster rollout cycles across live network domains. ▸ Architected RAG-based KYC & fraud detection platform for regulated financial services: 50% faster compliance processing, 12% improvement in fraud detection accuracy. ▸ Led technical program delivery of Ericsson Wallet (mobile financial services) Azure-native platform: AKS + Terraform + Databricks + telemetry pipeline — 15% cloud cost optimisation in a regulated FinTech environment. ▸ Built GenAI-based OCC to cCAF migration pipeline for Bharti's charging systems — 30% faster migration at enterprise scale. ▸ Implemented enterprise MLOps and LLMOps across Azure, AWS, and GCP (Kubernetes, Docker, OpenShift) — XAI, bias detection, and governance standards embedded from design. ▸ Defined enterprise AI architecture standards and governance frameworks — Zero Trust, GDPR alignment, and audit traceability adopted across global delivery teams.

Supply Chain & Network Operations

▸ Led network inventory management and equipment demand planning across multi-country telecom infrastructure programs — using Oracle DB-backed pipelines and Python automation scripts to improve planning accuracy and reduce procurement lead times. ▸ Automated vendor and procurement workflows using Python scripting integrated with Oracle DB — reducing manual procurement processing effort and accelerating equipment ordering cycles for network rollout programs.

▸ Started as core telecom practitioner — automating BSS/charging systems using ML (supervised, unsupervised, reinforcement learning) before evolving into full enterprise AI architecture ownership.

Telecom systems integration and supply chain operations role — delivering IN/VAS solutions, managing network migrations, and supporting procurement and inventory workflows across live operator environments.

▸ Implemented and integrated IN/VAS telecom solutions across live operator networks — supporting installation, upgrade, and migration programs including HLR migration of 1 M+ subscribers. ▸ Managed supply chain coordination for telecom equipment deployment — tracking network inventory, coordinating vendor deliveries, and maintaining procurement records using Oracle DB-backed workflows. ▸ Built Python automation scripts for inventory tracking and procurement data processing — reducing manual effort in supply chain reporting and equipment lifecycle management. ▸ Supported end-to-end logistics for network rollout and upgrade programs — from requirement gathering through deployment, ensuring SLA compliance and operational continuity.