Software Craftsperson/Typescript- II

Accountabilities: Own complex software initiatives end to end, from design and implementation through testing, production readiness, and ongoing improvement. Build and maintain scalable, reliable backend systems and APIs using TypeScript and strong software craftsmanship principles. Design and deliver production-ready features while balancing business scope, technical quality, performance, and long-term maintainability. Build AI-powered applications and workflows using LLMs, AI agents, agentic frameworks, and modern AI tooling. Work with technologies such as OpenAI, Claude, agentic frameworks, and AI skills/tooling to create reliable and useful AI experiences. Identify technical and product risks beyond the immediate scope of assigned work and proactively drive appropriate solutions. Contribute to engineering excellence through testing, code quality, refactoring, tooling, DevEx, and DORA-oriented practices. Collaborate closely with clients and internal stakeholders to clarify requirements, establish priorities, and align technical work with desired outcomes. Mentor and support fellow engineers, contributing to knowledge sharing, technical growth, and a strong learning culture. Apply AI-assisted and agentic development workflows to accelerate design, development, testing, and delivery where appropriate. Build and integrate browser-based experiences, including Chrome Extensions, when required by projects. Promote responsible and pragmatic engineering practices focused on quality, reliability, maintainability, and client success. Requirements 3–6 years of professional software engineering experience with a demonstrated track record of owning and delivering complex production systems. Strong hands-on experience developing production-grade applications using TypeScript. Practical experience developing AI- or LLM-powered applications, including AI agents and agentic workflows. Experience working with platforms and technologies such as OpenAI, Claude, or comparable LLM ecosystems. Experience with Mastra or similar LLM and agent orchestration frameworks. Experience building or integrating Chrome Extensions and other browser-based applications. Understanding of Responsible AI principles, including evaluation, reliability, safety, privacy, and appropriate handling of AI-generated outputs. Experience using AI skills and tooling to extend the capabilities of AI agents. Strong system-design capabilities, with the ability to develop scalable, maintainable, reliable, and observable systems. Strong engineering practices, including Test-Driven Development (TDD), CI/CD, code reviews, refactoring, and Agile or Extreme Programming practices. Good understanding of REST and/or gRPC APIs, relational databases, performance optimization, source control, and technical documentation. Strong problem-solving, ownership, communication, and collaboration skills. Ability to work effectively with clients and distributed teams while proactively identifying issues and driving them toward resolution. Python experience is a plus, particularly for production applications and AI/LLM systems. Familiarity with technologies such as LangChain, LlamaIndex, Agno, vector databases, AI evaluation or observability tools, Docker, Kubernetes, or Terraform is advantageous. Experience with React.js or other modern frontend frameworks is a plus. A continuous-learning mindset and genuine interest in software craftsmanship, AI-native development, and improving engineering practices. Benefits Fully remote, remote-first working environment with structured flexibility. Shared core hours that support effective collaboration while preserving individual autonomy. Twice-yearly in-person coworking sprints, with travel expenses covered. Annual company retreat with travel expenses covered. Dedicated learning and professional development budget. Conference talk sponsorship opportunities. Comprehensive medical and term insurance coverage. Employee-friendly leave policies. Home office fund to support an effective remote workspace. Collaborative engineering culture centered on pairing, refactoring, experimentation, continuous learning, and software excellence. Opportunities to work with modern AI technologies and influence AI-native development practices.