Senior AI Software Engineer

Jobtailor

Paris

Sur place

EUR 90 000 - 130 000

Plein temps

14 jours+

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Résumé du poste

Jobtailor is seeking a backend engineer to design, build, and operate production-grade Python services powering a conversational AI platform. You will develop low-latency, high-throughput systems using FastAPI, asynchronous programming, and WebSockets, while designing distributed architectures that stay reliable under high traffic.

You will collaborate with AI, product, and engineering teams to translate agent capabilities into scalable production systems and optimise critical execution paths

Qualifications

Expert-level Python skills with production backend experience.
Strong knowledge of asynchronous programming (asyncio, concurrency, multiprocessing).
Experience with FastAPI and API architecture in real-world services.
Experience building low-latency, real-time systems in production.
Understanding of distributed/event-driven design and scalability.
Experience with AI agent integration and LLM tooling is a plus.
Familiarity with Docker, Linux, CI/CD pipelines, and cloud platforms.

Responsabilités

Design, build, and operate production-grade backend systems for a conversational AI platform.
Build low-latency services using Python, FastAPI, and async programming.
Develop real-time event-driven systems with WebSockets, streaming, queues.
Design distributed architectures for reliability under heavy production traffic.
Improve AI agent orchestration and LLM-powered applications.
Integrate LLM APIs, AI frameworks, and external AI providers.
Use Redis and caching to enhance latency and throughput.
Profile systems, identify bottlenecks, and optimise critical paths.
Enhance resilience, observability, and production debugging.
Write unit, integration, and load tests.
Create modular architectures that scale with product growth.
Collaborate with AI, product, and engineering teams; translate capabilities into production systems.
Review AI-generated code for quality, security, and maintainability.
Work with AI coding tools to accelerate development and tuning.

Connaissances

Python

Asynchronous programming

FastAPI

WebSockets

Redis

Docker

Linux

Kubernetes

CI/CD

Cloud platforms

Outils

Redis

Docker

Kubernetes

CI/CD pipelines

Description du poste

Design, build, and operate production-grade backend systems powering our conversational AI platform.
Build low-latency, high-throughput services using Python, FastAPI, and asynchronous programming.
Develop real-time, event-driven systems using WebSockets, streaming technologies, queues, and parallel processing.
Design distributed architectures that remain reliable and responsive under significant production traffic.
Build and improve AI agent orchestration systems and LLM-powered applications.
Integrate LLM APIs, AI frameworks, communication infrastructure, and external AI providers into the platform.
Use technologies such as Redis and caching layers to improve latency, throughput, and system efficiency.
Profile production systems, identify performance bottlenecks, and optimise critical execution paths.
Improve system resilience, fault tolerance, observability, and production debugging capabilities.
Write comprehensive unit, integration, and load tests.
Design clean, modular, and maintainable architectures that can evolve as the product scales.
Work closely with AI, product, and engineering teams to translate agent capabilities into reliable production systems.
Use AI coding tools to accelerate development, debugging, testing, refactoring, and technical exploration.
Review and validate AI-generated code for architectural flaws, hallucinations, security issues, and maintainability risks.
Write a significant amount of production code while improving the overall engineering quality of the platform.

Requirements

Expert-level Python skills and strong experience building production backend systems.
Advanced knowledge of Python asynchronous programming, including asyncio, concurrency, and multiprocessing.
Strong experience with FastAPI and API architecture.
Experience building low-latency, high-throughput, or real-time systems in production.
Strong understanding of distributed and event-driven system design.
Hands-on experience with technologies such as:
WebSockets
Streaming systems
Message queues
Redis and caching
Parallel processing
Event-driven architectures
Experience building AI agents, LLM applications, or AI orchestration platforms.
Production experience with modern AI technologies such as LangChain or equivalent frameworks, MCP, LLM APIs, and real-time communication platforms such as LiveKit or equivalent.
Strong understanding of scalable architecture, system decomposition, modularity, resilience, and fault tolerance.
Experience with observability, performance profiling, latency optimisation, load testing, and production debugging.
Strong software engineering fundamentals, including clean architecture, maintainability, and automated testing.
Comfort working with Docker, Linux, CI/CD pipelines, Kubernetes fundamentals, and at least one major cloud platform such as GCP, AWS, or Azure is a strong advantage.
AI-Native Software EngineeringYou should already be using AI coding tools such as Claude Code, Codex, Cursor, Gemini CLI, or equivalent tools as part of your daily engineering workflow.
We are looking for engineers who know how to:
Break complex engineering problems into clear, AI-executable tasks.
Write precise technical specifications and prompts.
Orchestrate multiple AI coding agents or workflows in parallel.
Rapidly review, test, and validate AI-generated code.
Identify hallucinations, security vulnerabilities, and architectural weaknesses.
Refactor AI-generated code into clean and maintainable production software.
Use AI to accelerate debugging, testing, documentation, and refactoring—not only initial code generation.
Increase development output without reducing engineering quality or accountability.
Using AI tools is not a substitute for strong engineering fundamentals. You must be able to understand, challenge, and take full ownership of everything that enters production.
Comfort working closely with AI researchers, product teams, and infrastructure engineers to turn experimental capabilities into reliable production systems.
Eligibility to work in France is required.

Core Competencies

Demonstrates expert-level Python programming skills and advanced knowledge of asynchronous programming, with a strong focus on building low-latency, high-throughput backend systems. Proficient in designing distributed architectures and integrating AI technologies to enhance system performance and reliability.

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