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.

Experience
8-10 yrs