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.
Senior Software Engineer
Time Tracking Platform - Greenfield - AI-First Development
About the Project
Building a best-in-class time tracking platform from the ground up. This is a greenfield opportunity — no legacy constraints, no technical debt — The platform will integrate natively with the tools our customers already live in. AI-first engineering team. Leveraging AI coding assistants, LLM-augmented workflows, and intelligent automation as a natural part of how you build — not as an afterthought. The system will be used by approximately 3,000 users
The platform will:
Track individual time entries aligned to mapping them under Capex and Opex category
Associate time entries with projects and token usage
Integrate with existing tools such as Linear, Airtable, and Slack
Leverage bots/agents to provide intelligent suggestions based on calendars, activity, and messaging patterns
Be delivered as a greenfield solution, with no migration dependency on legacy systems
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
Engagement Details
Duration: ~6 months
Time zone: East Coast alignment required
Work style: Highly collaborative, execution‑focused, minimal bureaucracy
or continue with email
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.
Senior Software Engineer
Time Tracking Platform - Greenfield - AI-First Development
About the Project
Building a best-in-class time tracking platform from the ground up. This is a greenfield opportunity — no legacy constraints, no technical debt — The platform will integrate natively with the tools our customers already live in. AI-first engineering team. Leveraging AI coding assistants, LLM-augmented workflows, and intelligent automation as a natural part of how you build — not as an afterthought. The system will be used by approximately 3,000 users
The platform will:
Track individual time entries aligned to mapping them under Capex and Opex category
Associate time entries with projects and token usage
Integrate with existing tools such as Linear, Airtable, and Slack
Leverage bots/agents to provide intelligent suggestions based on calendars, activity, and messaging patterns
Be delivered as a greenfield solution, with no migration dependency on legacy systems
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
Engagement Details
Duration: ~6 months
Time zone: East Coast alignment required
Work style: Highly collaborative, execution‑focused, minimal bureaucracy
Sign in
To continue your applicationor continue with email
By continuing you agree to our Terms & Privacy Policy.
Similar jobs
Show more