Job Description

What's the role?

As a Senior Manager you will lead enterprise AI initiatives with a primary focus on designing, building, and scaling AI-native capabilities across the organization. The role is centered on full-stack AI leadership, spanning LLM-powered applications, agentic AI, orchestration frameworks, retrieval architectures, AI platforms, governance, model operations, and enterprise-grade deployment of intelligent solutions. In addition, you will:

• Define and execute the enterprise AI strategy and roadmap, with a strong emphasis on Generative AI, agentic AI, and AI-enabled business and operational transformation.
• Lead the design, development, and deployment of enterprise-grade AI solutions across the full stack, including model integration, application architecture, APIs, data pipelines, orchestration layers, and user-facing AI experiences.
• Build and operationalize LLM-powered applications such as copilots, assistants, intelligent search, knowledge agents, workflow agents, and autonomous task-execution systems.
• Design and implement agent-based systems using modern orchestration and coordination frameworks, including multi-agent workflows, tool use, memory patterns, guardrails, and human-in-the-loop controls.
• Drive adoption of core AI patterns and components such as prompt engineering, RAG, vector databases, embeddings, model routing, evaluation pipelines, and AI governance controls.
• Establish reusable AI engineering standards, reference architectures, development frameworks, security controls, and best practices for scalable enterprise adoption.
• Partner with engineering, platform, data, cloud, security, and business teams to identify and deliver high-value AI use cases with measurable outcomes.
• Evaluate emerging AI technologies, models, frameworks, and platforms, and recommend scalable adoption strategies aligned to enterprise architecture principles.
• Define AI lifecycle processes covering experimentation, prototyping, testing, evaluation, deployment, monitoring, risk management, and continuous improvement.
• Ensure responsible AI practices across solution design, including security, privacy, compliance, explainability, traceability, and model governance.
• Lead architecture and design reviews for AI solutions, ensuring performance, reliability, interoperability, and scalability across enterprise environments.
• Influence senior stakeholders on enterprise AI strategy and transformation priorities.
• Translate complex AI concepts into executive-ready business recommendations, implementation roadmaps, and investment cases.
• Contribute domain insight into IT Operations use cases such as incident intelligence, observability, automation, service desk augmentation, and operational analytics where relevant; this is a preferred but not primary expectation for the role.

Who are you?

You are someone who brings deep expertise across the end-to-end AI stack, including foundation models, prompt engineering, RAG, vector databases, agent frameworks, AI application architecture, evaluation, security, and scalable implementation patterns. Knowledge of IT Operations, observability, service management, and operational workflows is a secondary, nice-to-have capability that will help you contextualize AI use cases within an enterprise IT environment. Further you have the following skills & experience:

• Bachelor's degree in Computer Science, Engineering, Information Technology, Artificial Intelligence, Data Science, or a related field.
• 12-18 years of overall technology experience, with substantial recent experience in enterprise AI, machine learning platforms, generative AI, or intelligent automation domains.
• 5+ years of leadership experience managing enterprise-scale technology, AI engineering, platform, architecture, or innovation teams.
• Strong hands-on expertise with Large Language Models (LLMs), Generative AI, prompt engineering, RAG, vector databases, embeddings, and AI application development.
• Proven experience designing and implementing AI agents, agentic workflows, autonomous systems, AI copilots, and enterprise-grade AI solutions.
• Strong understanding of the complete AI stack, including data architecture, model integration, guardrails, evaluation, observability, security, governance, deployment, and scalability.
• Experience with enterprise AI ecosystems and frameworks such as OpenAI, Azure AI, Amazon Bedrock, LangChain, LangGraph, CrewAI, AutoGen, MCP, semantic orchestration tools, or similar technologies.
• Strong software engineering and solution architecture capability, including APIs, microservices, Python or equivalent programming, cloud-native design, and integration patterns for enterprise platforms.
• Experience building AI solutions in production environments with attention to reliability, monitoring, performance optimization, and business adoption.
• Excellent stakeholder management, executive communication, strategic thinking, and organizational transformation skills.

HERE is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, age, gender identity, sexual orientation, marital status, parental status, religion, sex, national origin, disability, veteran status, and other legally protected characteristics.

Who are we?

HERE Technologies is a location data and technology platform company. We empower our customers to achieve better outcomes – from helping a city manage its infrastructure or a business optimize its assets to guiding drivers to their destination safely.

At HERE we take it upon ourselves to be the change we wish to see. We create solutions that fuel innovation, provide opportunity and foster inclusion to improve people’s lives. If you are inspired by an open world and driven to create positive change, join us. Learn more about us on our YouTube Channel.

In this role you will be part of the NOC & Support Operations team acts as the 24×7 command center for platform reliability, proactively monitoring services, managing incidents, and leading major outage resolution. The team coordinates closely with engineering and business stakeholders to restore services quickly and minimize customer impact. Support Operations further ensures strong governance through standardized processes, clear communication, root cause analysis, and continuous improvement to enhance service stability and customer trust