Sales Engineer, Warehouse Robotics Automation

The Role

Become the internal authority on Prime Robotics' full product portfolio within your first 60 days
Lead technical discovery sessions to uncover customer pain points and design tailored automation solutions — including labor reduction modeling and ROI analysis
Drive the full sales cycle alongside our commercial team, from qualification and solution concepting through proposal, executive presentation, and close
Engage SVP- and director-level stakeholders across warehouse, e-commerce, and manufacturing sectors to build trusted advisor relationships
Act as a go-to-market resource for pre-commercial and emerging product lines, identifying new use cases and leading pilot programs
Partner with engineering and customer success teams to ensure seamless handoffs and high client satisfaction through implementation
Apply data science and process automation tools to accelerate the requirements analysis and proposal process

Requirements

• 5+ years in solutions engineering, sales engineering, or technical consulting within warehouse automation, material handling, or robotics
• Hands-on experience with automation technologies such as ASRS, AMRs, AutoStore, shuttle systems, WMS/WES, sortation, or pick-to-light/voice/vision
• Proven ability to lead complex, multi-stakeholder sales cycles for deals in the $1M-$50M+ range
• Comfort presenting technical solutions and financial business cases to C-suite and SVP-level audiences
• Strong quantitative skills — you can build ROI models, forecast labor savings, and size solutions based on operational data
• Proficiency with CAD tools (AutoCAD, Configura) and simulation/modeling software; familiarity with data science tools (Python, SQL) is a plus
• Excellent project management skills; PMP or Six Sigma certification a plus
• Bachelor's degree in industrial engineering, Mechanical Engineering, or a related technical field; MBA a plus

Pay

The minimum expected base salary for this role is $120,000 annually informed by external market data. Actual offers will depend on factors such as the candidate's experience, education, training, key or critical skills, and current market and business conditions.