Software Engineer
Role details
Job location
Tech stack
Job description
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
Requirements
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, OAuth2.0 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. OAuth2.0, 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.