Nigel Bungaroo

About

Senior AI Software Engineer with 6+ years of experience building scalable AI platforms, distributed systems, and cloud-native applications across enterprise SaaS and AI infrastructure environments. Specialized in AI-powered backend platforms including LLM integrations, RAG pipelines, semantic search systems, and automation workflows. Strong expertise in Python, Node.js, TypeScript, React, and event-driven microservices, with a proven track record delivering low-latency, scalable, multi-tenant systems and leading architecture decisions for end-to-end full-stack solutions that improve scalability, reliability, and engineering efficiency in production.

Experience

• Senior AI Engineer · CouldTalk10-01-2023

  Senior AI Engineer contributing to cloud-native AI platforms enabling enterprise conversational intelligence and intelligent automation. Owned key backend architecture decisions and development of distributed AI services deployed across AWS and Azure. Key Contributions • Architected scalable backend services for AI-driven applications using Node.js, Python, TypeScript, and microservices architecture, supporting high-volume production workloads. • Designed LLM-powered agent workflows using OpenAI APIs and orchestration frameworks, enabling multi-step reasoning, tool execution, structured responses, and autonomous task completion. • Engineered RAG architectures integrating vector databases, embedding pipelines, semantic search, and enterprise knowledge sources to improve retrieval accuracy and contextual response quality. • Orchestrated distributed AI inference workflows using Kafka, Redis, BullMQ, and Celery to manage asynchronous processing and high-throughput workloads. • Built AI observability dashboards using React and TypeScript, integrating OpenTelemetry traces and evaluation metrics to monitor model behavior, latency, and production performance. • Implemented real-time communication workflows using WebSockets for streaming conversational responses and live AI interaction updates. • Defined production architecture patterns for LLM applications, including orchestration workflows, evaluation strategies, and reliability standards. Achievements • Improved conversational response reliability by 32% through prompt engineering and evaluation-driven optimization. • Reduced backend processing latency by 30% through Redis queue optimization, database tuning, and asynchronous orchestration. • Expanded platform capacity to support 65K+ daily conversations through AWS/Azure modernization and Terraform-based infrastructure automation. • Improved deployment reliability through automated testing and CI/CD pipeline optimization.

• Fullstack & Backend Engineer · Pinecone12-01-2021 – 07-01-2023

  Developed distributed AI infrastructure, semantic search services, and cloud platforms supporting enterprise retrieval applications. Key Contributions • Developed backend services using Node.js, Python, Flask, and REST APIs for distributed AI and automation workflows. • Engineered scalable microservices powering embedding pipelines, vector search infrastructure, and high-throughput processing using asynchronous messaging and distributed service communication patterns. • Optimized PostgreSQL queries and indexing strategies to improve ingestion performance and retrieval efficiency. • Built internal dashboards with React and TypeScript for monitoring ingestion pipelines and operational workflows. • Designed API integrations connecting ingestion pipelines, embedding services, and distributed processing workflows. • Partnered with ML and product teams to bring AI features into production, improving reliability, scalability, and operational readiness. Achievements • Reduced data retrieval latency by 33% through database optimization and Redis caching. • Improved platform reliability by 23% with enhanced monitoring, automated testing, and fault handling. • Delivered multiple enterprise platform releases by resolving performance bottlenecks and scalability challenges.

• Software Engineer · Objectway02-01-2019 – 10-01-2021

  Promoted from Software Engineering Intern to Junior Software Engineer, contributing to backend applications, automation tools, and internal enterprise platforms. Key Contributions • Engineered internal tooling using Python and SQL to process, validate, and manage engineering data. • Automated engineering workflows with Linux-based scripting and backend utilities, reducing manual effort. • Optimized database performance through query tuning, indexing, and data validation. • Developed and maintained backend features, automation tools, and internal enterprise systems used by engineering teams. • Created engineering documentation for internal platforms, automation workflows, and operational processes. Achievements • Reduced manual data processing time by 28% through workflow automation. • Improved test result accuracy with automated validation and data quality checks. • Delivered reliable internal tools adopted across multiple engineering teams.

Education

• University of Milano-BicoccaBachelor of Science, Computer Science

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