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Senior Backend Engineer for AI‑Driven Systems (Remote)
Senior backend engineer building scalable APIs and data pipelines in Python/FastAPI to power AI-driven products, integrating with cloud services and message brokers.
AI Platform & DevOps Engineer | AWS, Kubernetes
Build and scale the infrastructure for deploying AI models and agents on Kubernetes, focusing on reliability and deployment pipelines.
Senior Full Stack Backend Engineer
Build and maintain high-performance backend APIs in Python/FastAPI, integrate systems via RabbitMQ, and design scalable ETL pipelines for AI-driven products on Azure/GCP.
London-Based DevOps Engineer (Product Platform)
Designs and manages cloud infrastructure and CI/CD pipelines for AI/ML workloads, ensuring scalable, secure, and reliable production systems.
Senior DevOps Engineer (Infrastructure & MLOps)
Designs and manages cloud infrastructure and CI/CD pipelines for AI/ML platforms using AWS, Docker, Kubernetes, and GitHub/GitLab, while implementing MLOps workflows.
Senior DevOps Engineer
Leads cloud and AI/ML infrastructure on AWS and Azure, building scalable, secure platforms for analytics, underwriting, and fraud detection while driving DevOps maturity and automation.
Senior DevOps Engineer
Senior DevOps Engineer designs and maintains cloud infrastructure using Terraform and Azure DevOps, automates MLOps workflows, and ensures high availability of AI/ML platforms across AWS and Azure.
Backend Developer (Python) - COM INGLÊS - Remoto
Builds scalable FastAPI services in Python that expose data models and ML models on Databricks, integrating with Azure and MLOps tooling for a global fintech team.
Software developer senior - ia
Senior software engineer building AI solutions in Python/.NET, integrating LLMs, RAG, and MCP with cloud and vector databases to enable scalable, secure AI across the company.
Lead DevOps Engineer
Lead the cloud infrastructure, CI/CD pipelines, and operational engineering for scalable AI platforms at a global financial markets infrastructure provider, designing secure, observable, and resilient systems.
ML DevOps Engineer
Build and scale ML infrastructure for a quantitative trading firm, designing feature stores, MLOps pipelines, and data lakes to support petabyte-scale time-series models in low-latency environments.
Senior DevOps Engineer
Senior DevOps Engineer builds and secures AWS and Kubernetes platforms for a deep-tech AI/robotics company, automating CI/CD pipelines and ensuring compliance with modern cloud-native practices.
DevOps Engineer
Build and own cloud infrastructure for an AI-driven materials discovery platform, focusing on GPU compute, CI/CD, and reproducibility to accelerate scientific breakthroughs.
DevOps Engineer
Design and maintain Azure cloud infrastructure, Kubernetes clusters, and CI/CD pipelines for a platform supporting AI/ML models and applications.
DevOps Engineer (Product)
Build and scale cloud infrastructure and CI/CD pipelines for a psychological science startup integrating generative AI and ML, ensuring reliability, security, and rapid product delivery.
DevOps Engineer
Build and maintain cloud and Kubernetes infrastructure for a fintech company’s digital banking and AI platform, automating CI/CD and ensuring high availability in a regulated environment.
DevOps Engineer (Product) DevOps Engineer - Product (London, UK)
Build and scale cloud infrastructure and CI/CD pipelines for a behavioral-science AI platform, deploying ML models and ensuring reliability, security, and observability across AWS/GCP/Azure.
DevOps Engineer
Build and maintain cloud-native infrastructure for a healthcare data platform, using AWS, Kubernetes, Terraform, and CI/CD pipelines to support scalable, regulated SaaS and ML workflows.
Lead Data Scientist : Remote
Lead a team to build and deploy computer vision and multimodal LLM models on Azure, setting technical direction and mentoring engineers to solve real-world challenges.
Data & AI Engineer
Design, build, and deploy enterprise-scale AI/ML solutions using Python, SQL, and frameworks like TensorFlow/PyTorch, with cloud platforms (Azure/AWS/GCP) and MLOps practices.