Product Manager
$130k - $160k per yearHTS Engineering Ltd.
Job MandateThe Product Manager reports to the Director, Business Solutions, who, as Product Owner, sets product vision, strategy, and priorities. As a trusted advisor to the Product Owner, the Product Manager helps shape KORE’s AI and application strategy and translates it into product goals, roadmaps, and a prioritized backlog. The primary focus of the role is building KORE’s enterprise AI platform from the ground up – integrating third-party large language models (LLMs), business applications, and external services to deliver AI capabilities across HTS’s 20 locations in the US and Canada. The role also supports KORE’s business applications, including TRAX, through their ongoing enhancement and modernization, and develops expert knowledge of HTS’s business as a manufacturers’ representative to represent the voice of its users.
This is an individual contributor role with no direct reports. The Product Manager leads through influence, aligning Enterprise Delivery, Engineering, Architecture, and Solution Specialists so that each initiative is clearly defined and delivers measurable business value. Decisions on product direction, roadmap commitments, and priorities across initiatives rest with the Product Owner;
the Product Manager hasauthority to make day-to-day product decisions within that approved direction, brings evidence-based recommendations to inform strategic decisions, and keeps the Product Owner consulted and informed. Enterprise Delivery decides when and how approved work lands, and Engineering builds and runs the technology.
Major Responsibilities:AI Platform Strategy & Roadmap
Develops and maintains the AI platform roadmap within the direction set by the Product Owner, recommending the sequencing of capabilities – such as generative AI assistants, retrieval-augmented generation (RAG) over enterprise content, and AI agents that automate business workflows – based on business value, feasibility, and risk.
Identifies and assesses AI use cases with stakeholders across HTS and KORE, recommends priorities to the Product Owner, and validates approved use cases through prototypes and pilots before scaling.
Defines high-level requirements for third‑party integrations with LLM providers, business applications, and external services through APIs and connectors, in partnership with Architecture and Engineering.
Leads the evaluation of LLMs, AI vendors, and tools against criteria such as output quality, latency, cost, security, data residency, and vendor lock‑in, and provides recommendations to inform build, buy, or partner decisions.
Defines quality and evaluation criteria for AI capabilities – including accuracy, grounding, hallucination rates, and user feedback – and monitors their performance, usage, and operating cost in production.
Embeds responsible AI practices – data privacy, access control, human oversight, transparency, and guardrails – into product requirements, in partnership with Architecture and Security.
KORE Application Product Management
Translates the Product Owner’s strategy into roadmaps for KORE’s business applications, including TRAX, balancing new capabilities, enhancements, and production needs with the modernization of legacy functionality.
Leads product planning for legacy application modernization, proposing target capabilities, phased migration and retirement plans, and continuity of data and business workflows for Product Owner approval, in partnership with Architecture.
Assesses legacy functionality based on usage and business value, recommends what to retain, redesign, replace, or retire, and identifies where AI can simplify or automate existing processes.
Reviews roadmaps regularly against changes in business needs, capacity, and technology direction, and brings proposed changes to the Product Owner for approval before they are made.
Business Domain Expertise & Voice of the User
Develops and maintains an expert understanding of HTS’s business as a manufacturers’ representative – including sales, quoting, order management, project tracking, commissions, and relationships with manufacturers and customers – by working directly with users across the business.
Represents the voice of users in product decisions, translating their workflows, pain points, and business drivers into clear problem statements and product requirements.
Leads problem and solution discovery through user interviews, data analysis, research, and experiments, partnering with Business Solutions Specialists on business‑process validation and with Architecture on feasibility.
Backlog & Prioritization
Maintains a single prioritized product backlog aligned to the approved roadmaps, defining epics and high-level requirements with clear business context and expected outcomes.
Has authority to make day‑to‑day product decisions within the approved roadmap, including backlog sequencing, requirement detail, discovery approach, and AI evaluation methods.
Consults the Product Owner before changes to approved direction, roadmap commitments, or priorities across initiatives, presenting options, trade‑offs, and a recommendation, and communicates decisions to delivery teams.
Works with Enterprise Delivery Business Analysts, who elaborate epics into detailed requirements, user stories, and acceptance criteria, and with UX/UI Designers to ensure design work reflects product intent.
Uses estimates and capacity inputs from Enterprise Delivery and Engineering to inform prioritization and roadmap commitments.
Stakeholder Alignment & Product Outcomes
Defines product goals and value measures – such as adoption, efficiency, time saved, and return on investment – and tracks results after release.
Keeps the Product Owner informed of progress, risks, and emerging issues, and communicates roadmap progress and approved priority changes to stakeholders, translating AI concepts and constraints into clear business terms.
Participates in release‑readiness and user acceptance reviews to confirm solutions meet product intent, while Enterprise Delivery owns release governance and testing.
Supports go‑live and adoption planning, and uses user feedback and usage data to inform future iterations.
Supports the Director, Business Solutions, with portfolio investment decisions, vendor evaluations, and negotiations.
Working Conditions:
Hybrid of remote work and office setting
Office setting - Open, collaborative office space (may vary by location)
Fast paced environment with tight deadlines
Reliable access to personal transportation is a requirement
Minimum Required Technical Skills/Qualifications:Knowledge, Education, Training:Bachelor’s degree or higher in Computer Science, Engineering, Business, or a related field;
product management or AI certifications (e.G., Pragmatic Institute, CSPO, or AI product management programs) are assets.
Experience:
5+ years of product management experience with B2B or enterprise software
2+ years leading product management for AI or generative AI platform capabilities in production – such as multi‑model LLM integration, connections to business applications and external services, evaluation and monitoring frameworks, and AI governance – beyond individual AI features
Proven experience developing roadmaps and managing prioritized backlogs in an agile environment
Experience leading application modernization, such as moving legacy or ERP applications to modern, cloud-based architectures, is an asset
Experience in the manufacturers’ representative, distribution, HVAC, or construction industries is an asset
Technical Skills:
Strong working knowledge of generative AI and LLM concepts, including prompt engineering, RAG, embeddings and vector search, fine‑tuning trade‑offs, AI agents and tool use, model evaluation, and hallucination risk
Understanding of AI platform architecture and integration patterns, including APIs, connectors and protocols such as the Model Context Protocol (MCP), identity and access, data pipelines, and cloud AI services from major LLM providers
Familiarity with responsible AI, data privacy, and security practices, and frameworks such as the NIST AI Risk Management Framework
Strong quantitative analysis skills and a data‑driven approach to problem solving, including measuring AI quality, usage, and cost
Working knowledge of product discovery and prioritization frameworks (e.G., OKRs, RICE, Jobs‑to‑be‑Done)
Understanding of UX/UI principles, including conversational and AI‑assisted experiences, sufficient to evaluate design work
Understanding of application modernization approaches (e.G., refactor, re‑architect, replace, incremental migration) and cloud‑native architecture is an asset
Experience managing product in JIRA is an asset;
familiarity with ClickUp and Microsoft 365 is an asset
Minimum Required Behavioural / Soft Skills:
Strong communication skills, with the ability to explain complex AI and technical concepts to business stakeholders and leadership
Proven ability to lead through influence and to manage multiple stakeholders and competing requests
Operates with clear decision rights – acts decisively within approved direction and brings strategic trade‑offs to the Product Owner early
Curious and committed to continuous learning in a fast‑evolving AI landscape
Deep empathy for users and a commitment to understanding the business domain first‑hand
Self‑motivated, highly organized, and able to prioritize effectively in a fast‑paced environment
Comfortable managing ambiguity, complexity, and interdependencies within a product development cycle
Salary Range:$130k-$160k
#J-18808-Ljbffr
This is an individual contributor role with no direct reports. The Product Manager leads through influence, aligning Enterprise Delivery, Engineering, Architecture, and Solution Specialists so that each initiative is clearly defined and delivers measurable business value. Decisions on product direction, roadmap commitments, and priorities across initiatives rest with the Product Owner;
the Product Manager hasauthority to make day-to-day product decisions within that approved direction, brings evidence-based recommendations to inform strategic decisions, and keeps the Product Owner consulted and informed. Enterprise Delivery decides when and how approved work lands, and Engineering builds and runs the technology.
Major Responsibilities:AI Platform Strategy & Roadmap
Develops and maintains the AI platform roadmap within the direction set by the Product Owner, recommending the sequencing of capabilities – such as generative AI assistants, retrieval-augmented generation (RAG) over enterprise content, and AI agents that automate business workflows – based on business value, feasibility, and risk.
Identifies and assesses AI use cases with stakeholders across HTS and KORE, recommends priorities to the Product Owner, and validates approved use cases through prototypes and pilots before scaling.
Defines high-level requirements for third‑party integrations with LLM providers, business applications, and external services through APIs and connectors, in partnership with Architecture and Engineering.
Leads the evaluation of LLMs, AI vendors, and tools against criteria such as output quality, latency, cost, security, data residency, and vendor lock‑in, and provides recommendations to inform build, buy, or partner decisions.
Defines quality and evaluation criteria for AI capabilities – including accuracy, grounding, hallucination rates, and user feedback – and monitors their performance, usage, and operating cost in production.
Embeds responsible AI practices – data privacy, access control, human oversight, transparency, and guardrails – into product requirements, in partnership with Architecture and Security.
KORE Application Product Management
Translates the Product Owner’s strategy into roadmaps for KORE’s business applications, including TRAX, balancing new capabilities, enhancements, and production needs with the modernization of legacy functionality.
Leads product planning for legacy application modernization, proposing target capabilities, phased migration and retirement plans, and continuity of data and business workflows for Product Owner approval, in partnership with Architecture.
Assesses legacy functionality based on usage and business value, recommends what to retain, redesign, replace, or retire, and identifies where AI can simplify or automate existing processes.
Reviews roadmaps regularly against changes in business needs, capacity, and technology direction, and brings proposed changes to the Product Owner for approval before they are made.
Business Domain Expertise & Voice of the User
Develops and maintains an expert understanding of HTS’s business as a manufacturers’ representative – including sales, quoting, order management, project tracking, commissions, and relationships with manufacturers and customers – by working directly with users across the business.
Represents the voice of users in product decisions, translating their workflows, pain points, and business drivers into clear problem statements and product requirements.
Leads problem and solution discovery through user interviews, data analysis, research, and experiments, partnering with Business Solutions Specialists on business‑process validation and with Architecture on feasibility.
Backlog & Prioritization
Maintains a single prioritized product backlog aligned to the approved roadmaps, defining epics and high-level requirements with clear business context and expected outcomes.
Has authority to make day‑to‑day product decisions within the approved roadmap, including backlog sequencing, requirement detail, discovery approach, and AI evaluation methods.
Consults the Product Owner before changes to approved direction, roadmap commitments, or priorities across initiatives, presenting options, trade‑offs, and a recommendation, and communicates decisions to delivery teams.
Works with Enterprise Delivery Business Analysts, who elaborate epics into detailed requirements, user stories, and acceptance criteria, and with UX/UI Designers to ensure design work reflects product intent.
Uses estimates and capacity inputs from Enterprise Delivery and Engineering to inform prioritization and roadmap commitments.
Stakeholder Alignment & Product Outcomes
Defines product goals and value measures – such as adoption, efficiency, time saved, and return on investment – and tracks results after release.
Keeps the Product Owner informed of progress, risks, and emerging issues, and communicates roadmap progress and approved priority changes to stakeholders, translating AI concepts and constraints into clear business terms.
Participates in release‑readiness and user acceptance reviews to confirm solutions meet product intent, while Enterprise Delivery owns release governance and testing.
Supports go‑live and adoption planning, and uses user feedback and usage data to inform future iterations.
Supports the Director, Business Solutions, with portfolio investment decisions, vendor evaluations, and negotiations.
Working Conditions:
Hybrid of remote work and office setting
Office setting - Open, collaborative office space (may vary by location)
Fast paced environment with tight deadlines
Reliable access to personal transportation is a requirement
Minimum Required Technical Skills/Qualifications:Knowledge, Education, Training:Bachelor’s degree or higher in Computer Science, Engineering, Business, or a related field;
product management or AI certifications (e.G., Pragmatic Institute, CSPO, or AI product management programs) are assets.
Experience:
5+ years of product management experience with B2B or enterprise software
2+ years leading product management for AI or generative AI platform capabilities in production – such as multi‑model LLM integration, connections to business applications and external services, evaluation and monitoring frameworks, and AI governance – beyond individual AI features
Proven experience developing roadmaps and managing prioritized backlogs in an agile environment
Experience leading application modernization, such as moving legacy or ERP applications to modern, cloud-based architectures, is an asset
Experience in the manufacturers’ representative, distribution, HVAC, or construction industries is an asset
Technical Skills:
Strong working knowledge of generative AI and LLM concepts, including prompt engineering, RAG, embeddings and vector search, fine‑tuning trade‑offs, AI agents and tool use, model evaluation, and hallucination risk
Understanding of AI platform architecture and integration patterns, including APIs, connectors and protocols such as the Model Context Protocol (MCP), identity and access, data pipelines, and cloud AI services from major LLM providers
Familiarity with responsible AI, data privacy, and security practices, and frameworks such as the NIST AI Risk Management Framework
Strong quantitative analysis skills and a data‑driven approach to problem solving, including measuring AI quality, usage, and cost
Working knowledge of product discovery and prioritization frameworks (e.G., OKRs, RICE, Jobs‑to‑be‑Done)
Understanding of UX/UI principles, including conversational and AI‑assisted experiences, sufficient to evaluate design work
Understanding of application modernization approaches (e.G., refactor, re‑architect, replace, incremental migration) and cloud‑native architecture is an asset
Experience managing product in JIRA is an asset;
familiarity with ClickUp and Microsoft 365 is an asset
Minimum Required Behavioural / Soft Skills:
Strong communication skills, with the ability to explain complex AI and technical concepts to business stakeholders and leadership
Proven ability to lead through influence and to manage multiple stakeholders and competing requests
Operates with clear decision rights – acts decisively within approved direction and brings strategic trade‑offs to the Product Owner early
Curious and committed to continuous learning in a fast‑evolving AI landscape
Deep empathy for users and a commitment to understanding the business domain first‑hand
Self‑motivated, highly organized, and able to prioritize effectively in a fast‑paced environment
Comfortable managing ambiguity, complexity, and interdependencies within a product development cycle
Salary Range:$130k-$160k
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Vacancy posted 2 hours ago
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