Senior AI Platform Engineer

Job description

Accountabilities: Design and build reusable platform capabilities supporting LLM applications, AI agents, RAG, tool calling, and AI workflows. Develop scalable data and knowledge pipelines covering ingestion, embeddings, retrieval, vector search, metadata, and knowledge management. Build secure integrations between AI applications, enterprise data, and business systems using APIs, MCP, tool calling, and comparable integration patterns. Develop reusable frameworks, libraries, services, SDKs, and developer tooling that allow engineering teams to build AI applications efficiently. Establish technical standards and patterns for AI deployment, observability, evaluation, monitoring, and lifecycle management. Define and improve approaches for measuring AI quality, accuracy, latency, reliability, security, and cost. Take AI capabilities from experimentation and prototyping through reliable, scalable, and maintainable production deployment. Ensure AI platform capabilities comply with security, privacy, authentication, authorization, access control, and data governance requirements. Work with Engineering, Product, and IT teams to identify AI opportunities and translate ambiguous business needs into practical technical solutions. Evaluate emerging AI models, frameworks, infrastructure technologies, and development approaches to determine their potential business value. Contribute to the evolution of platform architecture, engineering standards, and reusable AI capabilities across the organization. Promote strong data engineering and platform practices around data modeling, data quality, secure data access, and operational reliability. Requirements: 5+ years of professional experience in data engineering, platform engineering, backend engineering, or a closely related discipline, with experience building and operating production systems. Strong proficiency in Python and SQL. Hands-on experience building and deploying production applications or services using LLMs and generative AI. Practical experience with RAG, embeddings, vector search, tool/function calling, AI agents, or enterprise knowledge systems. Strong data engineering fundamentals, including data pipelines, data modeling, data quality, and secure data access. Experience with Snowflake, Databricks, or comparable modern data platforms, together with tools such as dbt, Airflow, or similar technologies. Proven experience building shared AI infrastructure, platforms, or reusable AI capabilities rather than focusing exclusively on individual AI applications. Experience taking AI systems from experimentation and proof of concept through reliable production deployment. Solid understanding of security, authentication and authorization, privacy, access control, and data governance. Strong ability to translate ambiguous AI opportunities into practical, scalable engineering solutions. Excellent communication and collaboration skills, with the ability to work effectively across Engineering, Product, IT, and other stakeholders. Experience with AWS Bedrock or other managed foundation-model platforms is an advantage. Hands-on experience with MCP (Model Context Protocol) or comparable approaches for connecting AI systems to enterprise tools and data is a plus. Experience with LLM evaluation, AI observability, monitoring, quality management, or responsible AI practices is desirable. Familiarity with LangChain, LangGraph, vector databases, search technologies, internal developer platforms, SDKs, APIs, or reusable infrastructure is a strong advantage. Fluent professional proficiency in English, both written and spoken. Reliable home internet connection suitable for fully remote work. Benefits: Fully remote working environment with the flexibility to work from home. Ability to work from anywhere within the permitted employment locations and time-zone range, subject to local work authorization. Approximately 40 days of paid time off per year, including holidays and vacation, or more where required by local regulations. Mental health and wellbeing support. Monthly wellbeing allowance that can be used across a broad range of eligible services and activities. Flexible parental leave, including at least three months of paid leave for new parents, subject to applicable local requirements. Work-from-home stipend for laptop and home office equipment. Fully distributed, international working environment with colleagues across multiple countries and cultures. Asynchronous and collaborative working model designed for globally distributed teams. Opportunity to work on foundational AI infrastructure and influence how AI applications are developed and operated at scale. Exposure to cutting-edge technologies including LLMs, AI agents, RAG, MCP, vector search, modern data platforms, and AI governance. Strong opportunity for technical ownership, professional growth, and meaningful impact within a global technology organization. Inclusive and diverse environment that values autonomy, trust, collaboration, and continuous progress. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1 This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior AI Platform Engineer based in France. This is a senior engineering opportunity focused on building the foundational platform layer behind secure, production-grade AI applications. You will design shared infrastructure, services, integrations, and developer tooling that enable teams to build and scale AI capabilities efficiently. The role combines hands-on work with LLMs, AI agents, RAG, tool calling, and AI workflows with strong data engineering and platform engineering practices. You will leverage modern cloud and data technologies to turn experimental AI use cases into reliable, scalable production systems. Working across Engineering, Product, and IT, you will establish technical patterns, reusable capabilities, and governance standards for AI development. This fully remote role is ideal for an experienced engineer who enjoys solving foundational problems and shaping how AI is built and operated across an organization.