Principle Engineer

Responsibilities:

• Own the technical architecture and engineering direction for key products and platforms.
• Design and develop scalable, high-performance, and reliable applications using Python, TypeScript, Node.js, and Next.js .
• Drive an AI-first approach to product and engineering, identifying opportunities to integrate AI/LLMs into products, workflows, and developer experiences.
• Build and integrate AI-powered features and intelligent workflows into production applications.
• Make key decisions around system architecture, technology choices, scalability, performance, security, and reliability.
• Lead the design and development of backend services, APIs, and modern web applications.
• Collaborate closely with Product, Design, and Engineering teams to translate business requirements into scalable technical solutions.
• Establish and drive engineering best practices, including coding standards, design reviews, testing, observability, and documentation.
• Mentor senior engineers and influence engineering teams through technical leadership.
• Conduct architecture and code reviews and ensure high standards of engineering quality.
• Identify technical bottlenecks and continuously improve system performance, reliability, and developer productivity.
• Evaluate emerging AI and engineering technologies and assess their applicability to Kily's products.
• Drive technical initiatives from concept to production, taking end-to-end ownership of complex engineering problems.

Requirements:

• Strong experience as a Principal Engineer, Staff Engineer, Lead Engineer, or equivalent senior technical role.
• Strong hands-on expertise in Python.
• Strong proficiency in TypeScript and Node.js .
• Strong experience building modern web applications using Next.js .
• Strong understanding of software architecture, distributed systems, APIs, and scalable application design.
• Proven experience building and operating production-grade applications.
• Strong understanding of engineering fundamentals including data structures, algorithms, design patterns, testing, and system design.
• Strong experience with cloud-native application development and modern engineering practices.
• Strong understanding of CI/CD, version control, observability, and production engineering.
• Demonstrated ability to make architecture decisions and influence engineering teams.
• Strong problem-solving and analytical skills.
• Excellent communication and stakeholder-management skills.

AI-First Mindset:

We are particularly interested in engineers who actively use AI as part of their engineering and product development workflow.

Experience with any of the following would be highly valuable:

• LLMs / Generative AI.
• OpenAI, Anthropic, Gemini or similar APIs.
• AI agents and agentic workflows.
• RAG and vector databases.
• Prompt engineering and evaluation.
• LLM orchestration frameworks such as LangChain/LangGraph.
• AI-powered developer tools and coding workflows.
• Building AI-native products or features.
• Evaluation, observability, reliability, and cost optimisation of AI systems.
• Deep AI expertise is not mandatory if you have a strong AI-first mindset and demonstrated ability to rapidly learn and apply emerging AI technologies.

Good to Have:

• Experience designing AI-native or AI-powered SaaS products.
• Experience with microservices and distributed systems.
• Experience with AWS/GCP/Azure.
• Experience with PostgreSQL, Redis, MongoDB or similar databases.
• Experience with Docker and Kubernetes.
• Experience with event-driven architectures and messaging systems.
• Open-source contributions or strong engineering portfolio.
• Experience working in fast-paced startup/product environments.

Nice to Have:

• Builder mentality: You enjoy taking ambiguous problems from 01
• AI-first thinking: You naturally look for ways AI can improve products and engineering.
• Strong ownership: You take responsibility for outcomes, not just tasks.
• Technical depth: You can go deep into architecture and code when required.