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Back-end engineer building high-performance, real-time messaging and AI agent systems at scale using Node.js, TypeScript, Golang, and AWS.
Build and operate petabyte-scale data transfer pipelines for sensor data from global automotive partners, using Python, Terraform, Azure, Flyte, and Kafka within a hybrid London-based team.
This Lead Python Developer role involves building autonomous AI agent systems and RAG pipelines for a global insurance organization's greenfield AI platform. The position focuses on backend development using Python, Azure, and LLM technologies to create intelligent, agent-to-agent solutions.
Solutions Engineer at Build, an AI-powered real estate tech startup. You'll embed with domain experts to build and ship agentic AI workflows and internal tools that automate real estate development and acquisitions processes, owning everything from design through deployment.
Build and own modular AI workflow operations and evaluation harnesses for an agentic AI platform serving institutional real estate, ensuring output quality meets the bar of senior professionals.
Owns the platform experience—workflow builders, external integrations (email, Slack, API), and internal automation—for an AI company building agentic workflows for institutional real estate.
AI Engineer owning 'Dougie,' an agentic AI harness for institutional real estate workflows — building memory layers, wiring grading into execution, improving agent orchestration (planning, tool use, recovery), and reducing human-in-the-loop time in production.
Hands-on AI Engineer building production agentic workflows for real estate diligence, planning, and execution using LLMs, Python, RAG, and agent frameworks in NYC.
Design, develop, and maintain backend APIs (public and internal) for a text-to-speech platform, driving performance and reliability across payments, analytics, subscriptions, and TTS systems.
Build and maintain core healthcare systems in Java/Kotlin, deploying modern CI/CD pipelines and AI tools to support Scandinavian social care.
Advance voice and multimodal AI agents for real restaurant environments, owning modeling problems across prompting, fine-tuning, evaluation, dataset development, and production behavior.
AI Evaluation Engineer runs evaluations at scale, statistically measures factual grounding and accuracy lift, and builds metrics frameworks using Python and data-science techniques for LLM evaluation.
Machine Learning Engineer on Grammarly's Responsible AI team, building scalable end-to-end NLP/ML solutions to improve safety and fairness across all Grammarly products, working closely with linguists and data scientists.
Lead/Senior/Staff QA Engineer owning quality for LLM-based AI agent systems in heavy industry, designing evaluation frameworks, golden datasets, and regression suites using Python and tools like LangSmith or promptfoo.
QA Engineer owning evaluation frameworks for non-deterministic LLM-based AI agent systems in heavy industry, building golden datasets, regression suites, and adversarial tests using Python and eval tooling integrated into CI/CD.
Build reinforcement learning environments that evaluate AI models on software tasks (bug fixing, refactoring, etc.) using MCP tools, designing reproducible environments and deterministic verification systems.
Builds and evolves MCP servers, tools, and graph-RAG pipelines to expose platforms to LLMs (e.g., Claude, Gemini) using Python, RAG, and vector databases, collaborating with product, data, and QA teams in an agile model.
Senior Data Scientist partnering with the SEO Marketing team to drive company-level SEO growth through metric development, causal inference experiments, A/B/MVT testing, and machine learning on web architecture, using SQL and Python/R.
Builds and operates cloud infrastructure for real-time AI services, focusing on reliability, scalability, and security using AWS, Docker, Terraform, and CI/CD tools.
Infrastructure Engineer building and operating the cloud platform beneath AI products, writing production code and automating work across the full service lifecycle using Python, Docker, AWS/Azure, ECS/Lambda, Terraform/OpenTofu, and Datadog.
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