Jobs
Senior Solutions Advisor
HiveMQ
United States
USD 160k-210k / year
Posted on May 5, 2026
Location
United States
Employment Type
Full time
Location Type
Remote
Department
RevenueSolutions Engineering
Compensation
- Estimated salary on target ernings $160K – $210K
HiveMQ is the Industrial AI Platform helping enterprises move from connected devices to intelligent operations. Built on the MQTT standard and a distributed edge-to-cloud architecture, HiveMQ connects and governs industrial data in real time, enabling global leaders like Audi, BMW, Eli Lilly, and Siemens to operationalize AI and drive innovation at scale.
At HiveMQ, our culture is Effortless → Empowered → Relentless. We make the complex simple, act with confidence and ownership, and never stop pushing the boundaries of what’s possible. Join us to power the future of intelligent industry.
HiveMQ's Vision for this role
The Solution Advisory team is HiveMQ's strategic technical front line. We are not just answering RFP questions or giving demos, we co-own the deal with our Account Executives, lead with business outcomes, and help our customers turn MQTT and the HiveMQ platform into measurable industrial and AI value.
As a Senior Solution Advisor, you will lead our most complex, strategic engagements across EMEA or the US. You will pair with 2 to 3 Account Executives on enterprise opportunities (typically influenced ARR target of $1.5M+), shape buying criteria before competitors do, and act as the trusted advisor that customer champions and executives call before they make a decision.
You will also be a multiplier for the team: contributing to our shared playbooks (discovery, value engineering, competitive positioning), and feeding field insights into Product and Engineering.
What you will do
Own the deal alongside the AE
Co-own opportunities from first call to close, with full accountability for the technical and business win
Run structured discovery using MEDDPICC: identify economic buyer, decision criteria, decision process, and quantifiable pain
Maintain deal hygiene in Salesforce and the Opportunity Qualifier so forecasts are honest and free of surprises
Lead with business outcomes (value selling)
Translate HiveMQ's technical capabilities into measurable customer outcomes (OEE, time-to-value, cost reduction, risk mitigation, AI readiness)
Build customer-specific ROI and TCO models, and use them to justify enterprise deals to economic buyers
Proactively shape evaluation criteria so the customer measures what HiveMQ wins on, not what competitors want to be measured on
Engage executives and shape strategy
Deliver C-suite and VP-level narratives with confidence and gravitas, lead Executive Briefing Center sessions and strategic workshops
Advise customers on multi-year transformation roadmaps spanning Unified Namespace, OT/IT convergence, edge connectivity, and AI-enabled manufacturing
Influence customer architecture decisions across multi-vendor ecosystems (cloud hyperscalers, streaming platforms, historians, MES/ERP)
Architect, advise, and challenge
Build reference architectures, do not just present them. Whiteboard under pressure and produce designs that survive contact with a real plant network
Lead co-design sessions with customers across edge, broker, data, and cloud layers; cover both current state and target state
Advise on the right patterns for resilience, scalability, security, and observability, grounded in HiveMQ's reference architectures and real customer deployments
Constructively challenge customer assumptions and design choices when they put the project at risk, offer better alternatives backed by experience and data, not by deference to the loudest voice in the room
Conduct architecture reviews of existing customer environments, surface technical risks early, and recommend mitigations before they become production incidents
Bridge OT and IT design conversations: translate plant-floor constraints into IT-grade architectures and vice versa, so both sides commit to the same blueprint
Run technically rigorous POVs
Scope Proofs of Value with co-defined success criteria (technical and business), clear timelines, milestones, and a defined path to commercial decision
Lead POV execution end to end: own the test plan, drive a consistent engagement cadence with the customer, and remove blockers as they appear
Close out each POV with a clear go / no-go outcome and a clean handover to the Customer Value Manager at signature
Position HiveMQ competitively
Position HiveMQ effectively against MQTT brokers and IoT cloud services (EMQX, AWS IoT Core, Azure IoT Hub, Mosquitto) as well as adjacent industrial data platforms (HighByte, Litmus, Cognite, Inductive Automation, and AVEVA-class suites)
Maintain depth on competitor moves across both broker and industrial-software categories, and feed competitive intelligence back into the team's playbooks
Handle tough technical and commercial objections with confidence, including comparisons that go beyond pure broker capability into UNS, contextualization, and industrial DataOps narratives
Coach the team and create leverage
Mentor Solution Advisors, shadow their calls, and run feedback circles
Contribute to team IP: reference architectures, vertical one-pagers, value engineering toolkits, demo environments, and battle cards
Represent HiveMQ externally through blogs, webinars, and regional conference speaking
Who you are
We hire Solution Advisors who already understand operational environments. Industrial fluency is a prerequisite, not a stretch goal. Platform, cloud, and AI knowledge are teachable on the job, OT instincts are not.
A strong candidate can:
Talk specifically about industrial environments without prompting: names plants, asset classes, protocols, vendors, and project failure modes, and does not speak in slideware abstractions
Describe a real deployment that went sideways and explain why, ideally including the organizational root cause and not just the technical one
Articulate why "move fast and break things" does not translate to OT, because the "things" are physical processes with real consequences
Distinguish IT buyers from OT buyers and explain how those buying centers behave differently
Hold a credible conversation with a plant engineer, controls engineer, or operations leader without falling back to vendor-marketing language
Build strong, long-term relationships with both technical and executive stakeholders, and level-shift between a CTO conversation about industrial AI and a deep-dive whiteboard on broker clustering in the same call
Push back when needed: challenge customer architecture and design decisions with evidence and alternatives, not deference
Believe value selling drives bigger, faster deals, and can prove it with examples
Thrive in a fast-paced, high-ownership, highly collaborative environment, and bring others up with you
The background we require
This is the floor. Candidates who do not meet it are not a fit, regardless of seniority or polish elsewhere.
You must have done at least one of the following:
Worked inside a manufacturer, energy company, utility, logistics operator, or similar industrial business in a technical or technical-adjacent role (data, automation, controls, OT engineering, plant IT, MES, historian, SCADA)
Worked at a system integrator delivering OT projects on customer sites
Worked at an industrial ISV or vendor whose product lives in plant or field environments (e.g. Inductive Automation, Litmus, HighByte, PTC / Kepware / ThingWorx / Velotic, Tulip, Cognite, AVEVA, GE Digital / Proficy, Siemens Industrial Edge, Rockwell FactoryTalk)
The test is firsthand exposure to brownfield realities: mixed-vintage equipment, uptime constraints, plant-floor politics, change windows, safety reviews, and the gap between what a tag says and what the asset is actually doing.
What does not count:
Pure IT, cloud, or SaaS background with no plant-floor or field exposure
"Industry" experience that is actually corporate IT at an industrial company (e.g. SAP rollouts, M365 migrations, IT helpdesk for a manufacturer), the work that matters happens below the IT / OT boundary
Heavy reliance on AI, agent, or generic-platform talking points to compensate for thin domain depth
What we are looking for
The ideal candidate has most of the following.
Advisory and commercial depth (Value Selling)
5+ years in software pre-sales, solution engineering, or solution architecture, including time in a senior or lead capacity on enterprise deals
Demonstrated success owning or co-owning enterprise opportunities of $500K+ ACV, with documented influence on $1.5M+ in annual ARR
Hands-on use of MEDDIC / MEDDPICC, structured discovery, and outcome-based qualification
Proven ability to build and present ROI / TCO business cases to economic buyers
Strong executive presence: comfortable presenting to C-level and VP audiences, handling tough questions, and navigating internal customer politics
Experience positioning against MQTT brokers and IoT cloud services (EMQX, AWS IoT Core, Azure IoT Hub, Mosquitto) and adjacent industrial data platforms (HighByte, Litmus, Cognite, Inductive Automation, AVEVA-class), and leading competitive bake-offs across both categories
Technical depth
Strong working knowledge of MQTT (3.1.1 and 5), including QoS semantics, session handling, retained messages, shared subscriptions, and topic design
Good understanding of the HiveMQ Platform: broker architecture, clustering, Enterprise Security Extension (TLS, AuthN/AuthZ, realms), Bridge and Kafka extensions, Data Hub policies and transformations, Edge protocol adapters, Control Center
Comfortable with Kubernetes for production workloads (StatefulSets, Helm, the HiveMQ Operator, monitoring with Prometheus / Grafana)
Familiar with at least one major cloud (AWS, Azure, or GCP) and with networking concepts (TCP/IP, WebSockets, PrivateLink / Private Endpoint, load balancing)
Solid grounding in enterprise security, reliability, interoperability, and observability
Working knowledge of databases relevant to IoT data flows (PostgreSQL, MySQL, MS SQL) and of streaming patterns
Development and automation skills
Comfortable reading and writing code to prototype integrations, build custom demos, or unblock customer POVs without waiting for engineering
Hands-on with at least one of Java/Kotlin, Python, JavaScript/Node.js
Familiar with containerization (Docker) and Infrastructure as Code (Terraform, Ansible, Helm)
Comfortable with scripting (Bash, PowerShell), REST APIs, and basic CI/CD concepts
Should be able to write or extend HiveMQ extensions, Edge protocol adapters, or Data Hub policies/transformations to address specific customer requirements after an initial training
Industry and domain expertise
Has stood up real systems in industrial environments, not just demoed software; bonus if you have done implementation work at a system integrator or industrial ISV before moving into pre-sales
Comfortable across the IT / OT boundary: can talk to a controls engineer about PLCs and a cloud architect about Kubernetes in the same call
Working knowledge of at least one major industrial protocol (MQTT, OPC UA, or Modbus). You do not need to be expert in all of them, but you do need to know the world they live in
Deep knowledge in at least 2 of: Smart Manufacturing / IIoT, Connected Vehicles & Mobility, Energy & Utilities, Logistics, with experience weighted toward Discrete Manufacturing, Pharma, and Process industries (our current ICP focus)
Familiarity with industrial standards and protocols relevant to your verticals: ISA-95, Unified Namespace (UNS), Sparkplug B, OPC UA, MODBUS TCP, VDA5050, and others such as Siemens S7, ADS Beckhoff, MTConnect
Understands why a clean cloud-native architecture often does not survive contact with a real plant network, and knows what good integration patterns look like in brownfield environments
Awareness of OT/IT convergence patterns and the role of MQTT in industrial AI / data platforms
Soft skills and ways of working
We weigh soft skills as heavily as the technical buckets above. A strong Senior Solution Advisor combines the following, consistently and without prompting:
Discovery as a discipline, not a checklist: asks layered, business-anchored questions, listens for what is not being said, and reframes customer pain into quantifiable outcomes before reaching for a demo
Executive presence and level-shifting: moves credibly between a CxO conversation about industrial AI strategy and a whiteboard session on broker clustering or UNS modeling within the same engagement, adjusting depth and language to the room
Constructive pushback: challenges customer assumptions, AE expectations, and internal product positioning when the evidence supports it, and does so with data and alternatives rather than friction
Follow-through and operational rigor: owns commitments end to end, closes loops with customers and internal stakeholders, keeps Salesforce and the Opportunity Qualifier honest, and is the person teammates trust to land what they said they would land
Self-awareness and coachability: knows where their depth ends, asks for help early, debriefs wins and losses with intellectual honesty, and applies feedback visibly in the next engagement
Collaboration and multiplier behavior: lifts peers and junior Solution Advisors, contributes to shared IP (playbooks, reference architectures, battle cards), and treats team success as part of personal success
Collaboration and influence
Strong written and verbal communication; able to present at customer meetings, webinars, and conferences
Experience mentoring or coaching less senior pre-sales colleagues
Comfortable contributing to internal thought leadership: playbooks, reference architectures, content
Logistics
Located in EMEA (preferably UK, Germany, Austria, or France) or in the United States
Willing to travel up to 25% for customer engagements, partner sessions, and conferences
Bonus points
Multilingual (English plus French, German, or Spanish)
Hands-on experience with industrial AI, agentic workflows, ontologies, or DataOps in a manufacturing or energy context
Prior experience as an Executive Sponsor for strategic enterprise accounts
Published blog posts, whitepapers, or conference talks in the IoT / industrial space
How we will measure success
Influenced ARR (target $1.5M+ per year) and contribution to new logo acquisition
Win rate on engaged opportunities, and compression of demo to POV to signature cycle time
Accuracy of POV scoping (deals close without surprise re-pricing) and Opportunity Qualifier (MEDDPICC) completeness
Number of executive engagements led, reference customers developed, and team IP / thought leadership produced
Mentorship impact: progression of Solution Advisors you coach
To learn more about HiveMQ, a good place to start is our customer case studies:https://www.hivemq.com/customers/
EXCERPT FROM OUR CUSTOMER LIST
https://www.hivemq.com/customers/
Informations about our job advertisements
Job advertisements of HiveMQ GmbH are always directed at female, male and various applicants, regardless of age, gender, religion, sexual identity, disability, race, ethnic origin, world view, etc. The selection of a candidate is exclusively based on qualifications. For organisational reasons, we cannot return application documents and cannot reimburse any expenses that you incur during the application process.
Compensation Range: $160K - $210K