About Xebia
For more than 25 years, our global network of passionate technologists and pioneering craftspeople has delivered cutting-edge technology and game-changing consulting to companies on the brink of AI driven digital transformation. Since 2001, we have grown into a full service digital consulting company with 6000+ professionals working on a worldwide ambition. Driven by the desire to make a difference, we keep innovating. Fuelling the growth of our company with our knowledge worker culture. When teaming up with Xebia, expect in-depth expertise based on an authentic, value-led, and high quality way of working that inspires all we do.
At Xebia, we put ‘People First’—committed to attracting diverse talent and fostering an inclusive, respectful workplace where everyone is valued for their contributions. We welcome all individuals and evaluate solely on the quality of their work and teamwork.
Role Overview
As a Senior Software Engineer on this team, you will own the design and delivery of core backend services, drive integration architecture with third-party platforms, and help establish the engineering patterns. You will work closely with product, design, and customer-facing teams to ensure what gets built solves real problems elegantly.
Key Responsibilities
Platform & Backend Engineering
- Design and build scalable, highly available Java microservices on AWS from scratch
- Define and own the data model for time tracking entities — entries, projects, users, billing cycles
- Architect RESTful and event-driven APIs consumed by web, mobile, and third-party clients
- Own the full AWS infrastructure for your services: Lambda, ECS/EKS, RDS/Aurora, SQS, S3, CloudWatch
- Implement CI/CD pipelines using GitHub Actions or AWS Code Pipeline, with automated testing gates
Integrations
- Build bi-directional sync between the time tracking platform and Airtable bases via the Airtable API
- Integrate with Linear to link time entries to issues, projects, and cycles — keeping both systems in sync
- Develop Slack workflows: slash commands, interactive modals, notifications, and Bolt-based event subscriptions
- Design an integration framework that can onboard new third-party connectors without re-architecting core services
- Handle webhooks, OAuth 2.0 flows, token management, and rate limiting for all external platforms
AI-First Development
- Use AI coding assistants (e.g. GitHub Copilot, Claude, Cursor) as a core productivity tool throughout development
- Implement AI-powered features: intelligent time entry suggestions, anomaly detection, natural language querying of time data
- Leverage LLMs for smart auto-categorization of time entries based on calendar, Linear activity, or Slack context
- Contribute to prompt engineering, RAG pipelines, or fine-tuning workflows as the product roadmap evolves
- Evaluate and recommend AI/ML services (AWS Bedrock, SageMaker, OpenAI, Anthropic APIs) appropriate to each use case
Quality & Collaboration
- Write clean, well-tested Java code — unit, integration, and contract tests are non-negotiable
- Participate in architecture reviews, PR reviews, and cross-functional planning sessions
- Contribute to runbooks, ADRs (Architecture Decision Records), and internal documentation
Required Qualifications
Core (Must-Have)
- 5+ years of professional software engineering experience
- Backend: Strong Java proficiency
- Spring Boot or Quarkus for microservices; experience with reactive frameworks (Vert.x, WebFlux) a plus
- Cloud: Deep AWS expertise
- Hands-on experience with Lambda, ECS or EKS, RDS/Aurora, SQS/SNS, API Gateway, IAM, CloudFormation or CDK
- APIs: REST API and event-driven architecture design and implementation
- OAuth 2.0, webhook design, idempotency, and third-party API integration patterns
- AI Tooling: Demonstrable AI-first mindset
- Regular use of AI coding tools and willingness to bring LLM-powered features into production
- Greenfield: Proven ability to contribute meaningfully on a greenfield project — from blank canvas to production
Integration Experience (Highly Desirable)
- Airtable API — reading/writing records, managing bases, handling webhooks
- Linear API or GraphQL-based project management tool integrations
- Slack Bolt SDK — building apps, slash commands, modals, interactive components
- Experience building a reusable integration or connector framework
AI / ML (Desirable)
- Working knowledge of LLM APIs (OpenAI, Anthropic, AWS Bedrock)
- Experience with prompt engineering, RAG, or embeddings in a production context
- Familiarity with AWS SageMaker or similar ML deployment pipelines
- Understanding of responsible AI practices — latency, cost, hallucination mitigation
Nice to Have
- Experience in the time tracking, workforce management, or project management SaaS domain
- Frontend exposure — React or TypeScript — to collaborate closely with full-stack requirements
- Familiarity with multi-tenancy patterns and SaaS billing / subscription models
- Contributions to open-source projects or public technical writing
- Experience with observability tooling: Datadog, Open Telemetry, AWS X-Ray