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Amazon

Posted 27 Aug 2026

Lead Engineer

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Employment
Full time
Team
Software Engineering
Posted
27 Aug 2026

About the role

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 lead engineer, staff engineer, principal 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 and LangGraph; AI-powered developer tools and coding workflows; building AI-native products or features.
  • Evaluation, observability, reliability, and cost optimization 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.


What We're Looking For:

  • 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.
  • Product mindset: You understand the business impact behind technical decisions.
  • Bias for action: You are comfortable moving quickly while maintaining engineering quality.
  • Technical leadership: You influence through expertise, clarity, and execution rather than hierarchy.


Tech Stack:

  • Backend: Python, Node.js .
  • Frontend: TypeScript, Next.js .
  • AI: Generative AI / LLMs / AI Agents.
  • Engineering: APIs, Cloud, CI/CD, Distributed Systems.

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