This Lead Software Engineer role at HERE Technologies offers a fantastic opportunity for experienced professionals to drive innovation in location data. With a focus on Java, Scala, or Python and AWS, candidates will lead end-to-end architecture and operational excellence for distributed services. The emphasis on AI coding assistants and LLM concepts also makes this a forward-thinking position for those interested in cutting-edge development practices.
About the Role
As a Lead Software Engineer at HERE Technologies, you will be instrumental in driving the design, development, and evolution of complex, scalable services. This role involves end-to-end ownership of features and platform enhancements, from design and implementation through deployment and operations, while actively contributing to engineering best practices and fostering a strong team culture.
HERE Technologies is a leading location data and technology platform company, empowering customers to achieve better outcomes by providing solutions that fuel innovation and improve people's lives. You will join a team dedicated to enhancing the accuracy of places and location data at scale, building software that ingests signals, evaluates trust, and translates insights into actionable improvements for their map and places database.
The ideal candidate is an experienced software engineer with strong problem-solving skills, a commitment to building high-quality systems, solid technical expertise, and a collaborative, impact-driven mindset. The role requires a thoughtful, data-informed approach to technical decision-making and an interest in leveraging AI-powered coding assistants to boost productivity.
Responsibilities
Drive the design, development, and evolution of complex, scalable services
Own features and platform enhancements end to end—from design and implementation through deployment and operations
Contribute to engineering best practices and foster a strong team culture
Demonstrate expert-level proficiency in Java, Scala, and/or Python, with the ability to design, review, and guide the development of complex, large-scale systems
Lead end-to-end architecture, development, and operational excellence for distributed services on AWS
Define and drive technical strategy, influence system design decisions, and set engineering direction across multiple teams or domains
Develop clear, high-quality technical proposals and architectural blueprints to support strategic decision-making
Collaborate closely with product managers, architects, and globally distributed engineering teams to align on vision and execution
Make high-impact technical decisions, balancing scalability, reliability, cost, and delivery timelines
Mentor and coach engineers and senior engineers, strengthening overall technical capability and engineering excellence
Proactively identify and champion opportunities for innovation, automation, and AI adoption
Lead cross-team initiatives and ensure predictable delivery of complex, multi-component programs
Strong hands-on experience with AI coding assistants (e.g., GitHub Copilot)
Skilled in crafting high-quality prompts for system design, refactoring, testing, and documentation
Solid understanding of LLM concepts, including RAG patterns and hallucination mitigation
Requirements
7+ years of experience
Strong coding experience in Java, Scala, or Python, with the ability to design and maintain complex, production-grade services
Hands-on experience building and operating scalable services in a cloud environment, preferably AWS
Experience working with distributed systems, service-oriented architectures, and modern development practices
The ability to communicate technical ideas clearly through written and visual documentation
Experience collaborating with global and cross-functional stakeholders
A thoughtful, data-informed approach to technical decision-making
An interest in using AI-powered coding assistants (such as Copilot) to improve productivity, including writing effective prompts for coding, debugging, testing, and documentation
A mentoring mindset and a commitment to continuous learning and improvement
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