Jobs at HERE Technologies

Leads technical product management for engineering services supporting digital map data extraction, processing, merging, and validation. Translates stakeholder needs into technical requirements and acceptance criteria, manages roadmaps, requirement intake, software issues, risks, dependencies, and delivery plans. Partners with engineering leadership and teams to solve complex problems and ensure end-to-end execution.

Leads reporting, analytics, and data management initiatives for the Chief Customer Office. Owns Tableau dashboards and reporting solutions, translates business needs into analytics, improves data quality and governance, supports data warehouse projects, manages access controls, and evaluates analytics technologies. Partners with sales, finance, IT, security, and transformation teams to deliver accurate insights for pipeline, revenue, bookings, forecasting, and operational decision-making.

Develop and support software for map processing, validation, and delivery to automotive customers for autonomous driving. Responsibilities include architecture ownership, coding, testing, debugging data pipelines, documentation, code reviews, releases, and improving engineering practices within an Agile team.

Build and operate AWS infrastructure supporting AI Hub and CatalystAI. Develop CI/CD pipelines, manage infrastructure as code, deploy Dockerized services, monitor reliability, troubleshoot issues, implement security and secrets management, and support API integrations. Collaborate with development and platform teams to improve deployment workflows, documentation, operational readiness, and automation for AI tooling and developer platforms.

Develop statistical, experimental design, sampling, analytics, and machine learning solutions to measure and improve HD map and location product quality. Build quality estimators, A/B experiments, data workflows, computing tools, and models while collaborating with map experts, engineers, and data scientists. The role focuses on reliable quality measurement, uncertainty analysis, and data-driven process improvement.

Execute risk-based IT audit engagements covering SOX ITGCs, application controls, cybersecurity, cloud, privacy, AI governance, and technology operations. Responsibilities include audit planning, risk assessments, control testing, reporting, remediation validation, SOC report reviews, third-party risk assessments, and stakeholder collaboration. The role also contributes to audit methodology improvements, automation, analytics, and governance across emerging technologies.

Build and lead production AI/ML components, including embeddings, retrieval, agents, and multimodal systems, for reuse across domain teams. Translate architectural direction into technical specifications and production-ready implementations, make implementation-level decisions, identify scalability issues, and mentor engineers. The role requires deep expertise in representation learning, vector search, retrieval-augmented systems, deep learning, LLMs, agent frameworks, distributed systems, and ML engineering.

Lead the architecture, development, deployment, and monitoring of production-grade machine learning systems for high-definition, ADAS, ISA, and IVI maps. Lead work across computer vision, NLP, deep learning, Generative AI, Agentic AI, MLOps, data ingestion, model training, inference, and scalable cloud or in-vehicle deployment. Provide technical leadership, conduct architecture and code reviews, integrate ML outputs with mapping workflows, and translate business requirements into reliable ML system designs.

Design, develop, and deploy production-grade AI systems using generative AI, LLMs, agentic architectures, retrieval, deep learning, and multimodal models. Build scalable representation and vector-search layers, lead experiments, optimize and evaluate models, and apply responsible AI practices. Collaborate cross-functionally to solve spatial and business challenges, mentor engineers and data scientists, and contribute to patents and publications. The role requires strong Python and ML framework expertise, production MLOps experience, and independent architectural decision-making.

Lead the architecture and delivery of production AI and machine learning platforms, including representation learning, embeddings, vector search, retrieval-augmented generation, foundation models, agentic AI, and multimodal systems. Set technical direction, evaluate emerging technologies, define measurable success criteria, mentor engineers and data scientists, and collaborate with research, engineering, and product teams on scalable, explainable, responsible solutions for spatial and operational challenges.

Lead enterprise AI strategy and delivery, building and scaling LLM-powered applications, agentic systems, RAG/vector retrieval, orchestration, evaluation, governance, and production-grade AI platforms. Partner with engineering, data, cloud, security, and business stakeholders to deploy secure, observable, and scalable AI solutions and drive organizational adoption and transformation.

Lead AI risk analyst responsible for assessing risks across safety, privacy, security, fairness, transparency, oversight, and compliance. The role supports AI governance reviews, vendor assessments, regulatory and certification activities, and continuous improvement of governance frameworks and processes. It also develops policies, guidance, training, and practical recommendations while collaborating with Product, Engineering, Security, Privacy, Legal, Procurement, and external stakeholders.

Leads end-to-end ADAS and autonomous driving professional services engagements across EMEA. Owns solution architecture, delivery quality, customer relationships, technical escalations, presales support, RFIs/RFQs, pilots, and commercial outcomes. Collaborates with product, sales, automotive solutions, and engineering teams to develop scalable solutions, reusable assets, and delivery improvements for OEMs, Tier-1 suppliers, and strategic partners.

Leads AI/ML strategy, technical vision, and delivery of scalable machine learning platforms for map editing and maintenance. Drives generative AI, agentic AI, computer vision, LLM, automation, MLOps, governance, observability, security, and responsible AI adoption. Mentors data scientists, leads multidisciplinary initiatives, translates business needs into measurable solutions, and influences executives, customers, vendors, and partners.

Leads the website experience strategy and roadmap for HERE.com and related sites. Owns product prioritization, sprint planning, backlog management, releases, user acceptance testing, CMS architecture, and digital experience optimization. Partners with marketing, technology, infrastructure, UX, content, and development teams to improve engagement, lead generation, platform sign-ups, and website KPIs using analytics, martech, experimentation, and customer insights.

Leads technical pre-sales activities for enterprise customers, including discovery workshops, RFQ responses, technical demonstrations, proof-of-concept development, solution architecture, and implementation support. Acts as a trusted technical advisor, translates customer requirements into HERE platform solutions, mitigates delivery risks, and collaborates with sales, product, business, and partner teams. The role requires extensive technical pre-sales or consulting experience, enterprise software expertise, strong customer-facing communication, and Mandarin fluency.

Own and continuously improve the company-wide software error and defect management framework. Govern Jira workflows, templates, fields, dashboards, KPIs, SLAs, and reporting while defining integrations and data mappings with systems such as ServiceNow. Lead defect lifecycle practices, process governance, escalation, and cross-functional alignment across multiple products and teams without direct authority.

Design, build, deploy, and optimize production-grade generative AI agents, copilots, and intelligent workflows. Lead end-to-end delivery from solution design and prompt engineering to deployment, monitoring, and continuous improvement. Partner with business stakeholders to transform processes for AI-first execution, define KPIs, ensure governance and security, provide training and change management, and contribute reusable frameworks and best practices across the AI Center of Excellence.

Design, build, and operate an enterprise AI Hub providing shared runtime, CI/CD, model registry, observability, governance, and developer tooling to enable scalable, secure production AI and self-service capabilities across cloud and hybrid environments.

Develop Responsible AI governance tooling, technical guardrails, risk assessments, MCP scanners, and compliance automation for AI systems and agents. Build production-grade software integrated with CI/CD pipelines, support OSS compliance workflows, improve security and reliability, and translate governance requirements into engineering solutions. The role also involves technical documentation, training, stakeholder communication, and establishing organization-wide Responsible AI practices.