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Senior MLOps Engineer with 8+ years of experience building, deploying, and operating production-grade ML and GenAI systems. Proven track record scaling LLM-powered applications, multi-agent workflows, and end-to-end MLOps pipelines from research to reliable, monitored production. Experienced across startups and Fortune 500 environments, with strong focus on LLM reliability, latency optimization, model lifecycle automation, and cloud-native ML platforms. Skilled in building scalable backend/platform services, observability, CI/CD, and infrastructure-as-code to support dependable AI operations at scale.…Senior MLOps Engineer with 8+ years of experience building, deploying, and operating production-grade ML and GenAI systems. Proven track record scaling LLM-powered applications, multi-agent workflows, and end-to-end MLOps pipelines from research to reliable, monitored production. Experienced across startups and Fortune 500 environments, with strong focus on LLM reliability, latency optimization, model lifecycle automation, and cloud-native ML platforms. Skilled in building scalable backend/platform services, observability, CI/CD, and infrastructure-as-code to support dependable AI operations at scale.

Teddy Ambona

AI Engineer, Software Engineer, Back-End Developer

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Senior MLOps Engineer with 8+ years of experience building, deploying, and operating production-grade ML and GenAI systems. Proven track record scaling LLM-powered applications, multi-agent workflows, and end-to-end MLOps pipelines from research to reliable, monitored production. Experienced across startups and Fortune 500 environments, with strong focus on LLM reliability, latency optimization, model lifecycle automation, and cloud-native ML platforms. Skilled in building scalable backend/platform services, observability, CI/CD, and infrastructure-as-code to support dependable AI operations at scale.…Senior MLOps Engineer with 8+ years of experience building, deploying, and operating production-grade ML and GenAI systems. Proven track record scaling LLM-powered applications, multi-agent workflows, and end-to-end MLOps pipelines from research to reliable, monitored production. Experienced across startups and Fortune 500 environments, with strong focus on LLM reliability, latency optimization, model lifecycle automation, and cloud-native ML platforms. Skilled in building scalable backend/platform services, observability, CI/CD, and infrastructure-as-code to support dependable AI operations at scale.

Available to hire

Senior MLOps Engineer with 8+ years of experience building, deploying, and operating production-grade ML and GenAI systems. Proven track record scaling LLM-powered applications, multi-agent workflows, and end-to-end MLOps pipelines from research to reliable, monitored production.

Experienced across startups and Fortune 500 environments, with strong focus on LLM reliability, latency optimization, model lifecycle automation, and cloud-native ML platforms. Skilled in building scalable backend/platform services, observability, CI/CD, and infrastructure-as-code to support dependable AI operations at scale.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

French

Fluent

Work Experience

Senior MLOps Engineer at ZS | United States (remote)

May 1, 2024 - Present

Built and scaled GenAI/LLMOps infrastructure for enterprise-grade, low-code/no-code AI agent platforms used across Fortune-500 clients. Architected and operated real-time multi-agent GenAI systems (AutoGen/Agno + LangGraph) supporting RAG, Text-to-SQL, TTS, and tool-using React-style agents. Reduced end-to-end voice interaction latency by 90% (30s to ~3s) via streaming inference, async orchestration, and voice-first pipelines. Implemented LLM observability and tracing (LangFuse) to diagnose prompt failures, hallucinations, latency spikes, and agent coordination issues. Improved LLM reliability and safety with custom guardrails and collaboration with library founders. Designed scalable LLM execution pipelines using Celery + Redis for background inference and caching, and built automated LLM evaluation pipelines including LLM-as-a-judge.

Senior MLOps Engineer at TeraMind | United States (remote)

October 1, 2023 - April 30, 2024

Led MLOps and ML platform efforts for cybersecurity SaaS serving 10,000+ customers in a fully async, globally distributed team. Designed and implemented end-to-end MLOps pipelines for containerized NLP/LLM models, from research notebooks to production services. Productionized model training and inference pipelines using Kubeflow Pipelines on Vertex AI. Owned and operated GKE-based ML infrastructure including cluster provisioning, scaling, and reliability. Deployed decentralized observability (Grafana, Loki) for ML workloads, inference services, and data pipelines. Implemented model and data lineage, governance, and IAM-based access control. Led and mentored a team of 7 data scientists to enforce production-quality ML code and deployment standards. Load-tested and optimized GPU-backed inference services (HuggingFace with TorchServe/Seldon, CUDA) and improved data processing performance by migrating Pandas pipelines to Polars. Built CI/CD pipelines (Bitbucket Pipelines, Cloud Build) for

MLOps Engineer at Shell | London, England, United Kingdom

April 1, 2021 - December 31, 2022

Built and operated MLOps systems supporting revenue-critical energy forecasting and trading analytics at a global energy company. Productionized forecasting models (solar, wind, power prices) from Jupyter notebooks into versioned, monitored ML services. Designed ML pipelines using statistical and deep learning models (ARIMAX, LSTM, STL) for large-scale time-series forecasting. Implemented end-to-end ELT pipelines sourcing sensor and third-party data via APIs and transforming it in Azure Databricks. Established CI/CD and GitOps workflows for ML services, improving deployment safety and rollback reliability. Refactored Excel-driven research workflows into modular, testable Python ML code, achieving 100% test coverage. Built and distributed internal Python packages encapsulating ML and domain logic. Mentored 4 engineers on MLOps, testing, and production ML best practices. Deployed and monitored business-critical ML systems, handling on-call incidents and escalation.

Software Engineer (ML/Platform) at Prism FP | London, United Kingdom

July 1, 2019 - March 31, 2021

Built and operated backend systems for a SaaS trading and analytics platform in quantitative finance. Designed and built microservice-based backend architecture using Flask, Docker, Kubernetes, and Helm. Improved system observability and reliability with OpenTracing, Jaeger, and Grafana instrumentation. Built and deployed containerized backend services following cloud-native best practices. Implemented asynchronous workload handling using SQS queues and Lambda workers, preventing API saturation. Developed and operated Airflow-based ELT pipelines ingesting data from S3, vendor APIs, and web scraping. Diagnosed and resolved production data and performance issues. Implemented quantitative libraries and analytics features for the trading analytics SaaS platform.

Data Analyst - ETF Capital Markets at Lyxor Asset Management | London, United Kingdom

August 1, 2018 - June 30, 2019

Owned end-to-end data pipelines supporting ETF analytics and reporting. Tuned SQL performance for complex queries and managed resource-intensive computations with Python. Wrote ETL processes in Python (object-oriented programming), VBA, BQuant, and batch jobs. Designed and built a Flask-based web application for automated report distribution. Delivered analytics dashboards (Tableau) that could translate into business stories. Maintained and improved the ETF spread monitoring tool using real-time data.

Front Office Data Analyst at Lyxor Asset Management | Paris Area, France

July 1, 2017 - December 31, 2017

Supported ETF launches and front-office analytics with Python and SQL. Assisted fund managers and sales with data analysis using Python (pandas) and VBA. Built Python tools for data quality monitoring, web scraping, and internal services. Performed big data analysis and visualization with Tableau. Managed SQL database-related projects.