python ai platform engineer
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Job description
Think of it like Vercel for financial research - just as Vercel lets you spin up a new project with vercel init and handles all the infrastructure behind the scenes, we want to be able to declare an array of financial research processes and have the system handle orchestration, execution, and delivery. The goal is to make spawning new research representations as frictionless as starting a new Vercel project - define what you want, and the platform takes care of the rest.RequirementsExpert-level Python proficiency, as it is a primary language for all development. Deep technical knowledge of relational databases (Postgre SQL), including schema normalization, writing complex joins, query optimization, and managing indexing for high-concurrency environments. Proficiency with No SQL Databases, with a deep understanding of when to use document, key-value, or vector stores to handle unstructured LLM outputs and high-velocity research data. Comprehensive knowledge of deployment approaches
Requirements
including experience with CI/CD pipelines, containerization (Docker/Kubernetes), and different deployment strategies. Multi-platform deployment experience, with the ability to navigate and deploy across various environments ranging from serverless to traditional cloud providers (AWS, GCP, or Azure). Proven experience with serverless compute (e.g., Modal) and cloud-native architectures. Hands-on experience with LLM APIs including direct integration with Open AI, Anthropic, x AI, or Google. Familiarity with AI orchestration frameworks such as Pydantic AI. High level of resourcefulness and the ability to quickly master new concepts as the AI landscape evolvesNice to have skills:Experience working with financial data providers like S&P Global, Fact Set, or SEC Edgar Familiarity with modern AI tooling APIs such as Exa or ParallelResponsibilities:Write clean, maintainable Python code to build out the core orchestration engine and API layers Develop and debug durable execution logic, implementing state management, automated retries, and cost-control triggers for long-running tasks Build and maintain integrations for LLM providers and financial data APIs, ensuring high availability and low latency Design and implement database schemas in Postgre SQL and No SQL stores, writing optimized queries and managing migrations Create unified API abstractions that allow the system to switch between different LLM models and storage backends via configuration Build automated test suites and evaluation pipelines to validate the accuracy of LLM outputs and system performance Configure and automate deployment pipelines across multiple platforms, including CI/CD orchestration and container management Build and manage scalable infrastructure using serverless compute (Modal) and cloud-native services to ensure high availabilityBenefitsAwesome projects with an impact Udemy courses of your choice Team-buildings, events, marathons & charity activities to connect and recharge Workshops, trainings, expert knowledge-sharing that keep you growing Clear career path Absence days for work-life balance Flexible hours & work setup - work from anywhere and organize your day your way", "employmentType": "FULL_TIME", "industry": "Senior Python", "jobLocation" : { "@type": "Place", "address": { "@type": "PostalAddress", "streetAddress": "Valencia", "addressLocality": "Valencia", "addressRegion": "Valencia", "addressCountry": "ES", "postalCode": "n/a" } }, "salaryCurrency": "EUR", "title": "Senior python ai platform engineer", "hiringOrganization" : { "@type" : "Organization", "name" : "Intellectsoft" } }