Software Engineer

GitHub Actions AWS Lambda Slack API Descrição da oferta de emprego 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

• 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, 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

The ideal candidate must have strong Java skills, AWS experience, and be comfortable integrating with various APIs and tools. This 6-month engagement emphasizes collaboration and execution, leveraging modern development practices., * 5+ years of professional software engineering experience.

• Strong proficiency in Java, with experience in microservices.
• Deep knowledge of AWS and related services., * Design and build scalable Java microservices on AWS.
• Define and own the data model for time tracking.
• Integrate with existing tools via APIs.

Conhecimentos

Java proficiency AWS expertise AI tooling knowledge REST API design Spring Boot, 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

• Duration: ~6 months
• Time zone: East Coast alignment required
• Work style: Highly collaborative, execution-focused, minimal bureaucracy