Software Engineer – AI

Spendesk

Backend Software Engineer responsible for creating backend services for AI-native experiences at Spendesk. Collaborating with cross-functional teams to design, build, and operate scalable solutions.

Posted 6/3/2026full-timeParis • 🇫🇷 FranceMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AWSDistributed SystemsJavaScriptKafkaNode.jsPostgresTypeScript

About the role

Key responsibilities & impact

Design, build, and operate backend services and APIs that power conversational and agentic AI features.
Implement the services needed for context management, tool invocation, rich content access, and multi-step orchestration.
Build robust patterns for integrating LLMs through AWS Bedrock, including retries, fallbacks, tracing, and cost-aware usage.
Ensure these services are designed for production from day one, with strong standards on reliability, maintainability, and security.
Partner with the IC5 Staff Engineer to implement the architecture supporting AI-native product experiences.
Contribute to reusable service boundaries, contracts, and interfaces that can be adopted across squads.
Help define how applicative squads can expose MCP-compatible tools and capabilities to central AI services.
Translate high-level architectural direction into concrete technical implementations and scalable engineering patterns.
Own complex backend components end-to-end, from design and implementation to deployment and maintenance.
Contribute directly to proof-of-concepts and experiments, then harden the successful ones into reliable production services.
Review code, challenge design decisions, and raise the quality bar on backend engineering within the squad.
Instrument services with logs, tracing, and metrics to ensure strong production visibility and fast iteration.
Help define and uphold quality standards around latency, failure handling, cost efficiency, and resilience.
Collaborate with Product Managers and Designers to turn AI product concepts into concrete backend capabilities.

Requirements

What you’ll need

Significant experience on backend software engineering experience in production environments.
A strong track record of designing and shipping scalable backend services with clear ownership of reliability and maintainability.
Experience contributing to complex technical projects in fast-paced product organizations.
Ideally, hands-on exposure to AI-enabled or LLM-backed product features in production.
Strong backend engineering skills with TypeScript / Node.js or adjacent technologies.
Good fluency in service design, asynchronous architectures, and resilient distributed systems.
Experience integrating APIs and external services into robust product backends.
Practical experience, or strong interest, in integrating LLMs into production systems, ideally using platforms such as AWS Bedrock, OpenAI, or Anthropic.
Familiarity with technologies such as Kafka, SQS, Step Functions, PostgreSQL, and modern observability practices.
Highly autonomous and comfortable owning ambiguous technical problems from framing to delivery.
Able to work effectively in partnership with a Staff Engineer while independently delivering complex components.
Product-minded, customer-focused, and capable of translating business needs into backend systems.
Curious about AI-native product design and motivated by building durable foundations, not just short-term demos.
Fluent in written and spoken English, our business language.

Benefits

Comp & perks

Flexible on-site and remote policy
Latest Apple equipment — the tools you need to excel
Access to Moka.care — for emotional and mental health wellbeing
Great office snacks — to fuel your day
A positive team to work with daily!
Location-specific benefits tailored to each market, including health insurance, wellness allowances, commuter support, meal vouchers, and gym memberships — ensuring you're well supported wherever you're based.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

backend software engineeringscalable backend servicesTypeScriptNode.jsservice designasynchronous architecturesresilient distributed systemsAPI integrationLLM integrationproduction systems

Soft Skills

autonomousproblem-solvingcollaborationcustomer-focusedcommunicationcuriosityownershipadaptabilitytechnical framingdelivery