You’re the person who gets curious when two systems tell different stories. You like digging into the data, spotting the pattern everyone else missed, and figuring out what to change. And there’s a moment you love even more than solving the puzzle: watching someone use what you built and say, “That just made my day easier.”
As a Technical Solutions Analyst, you’ll lead the technical side of bringing new clients on board. You’ll learn how their teams work, configure AI workflows around their needs, and test them together before launch. Once they’re live, you’ll use real customer data to see what’s working, spot where people still get stuck, and make the next version better.
What you’ll do:
• Lead the technical side of onboarding. Meet with new clients to understand how they work today, agree on what a successful launch looks like, and build a rollout plan around their systems and priorities.
• Build and launch the solution. Use the platform’s admin console to configure workflows, integrations, field defaults, and business rules. Test with real client examples and guide users through setup. When an issue comes up on a live call, investigate it with the client and propose a next step.
• Make messy data usable. Get to know unfamiliar datasets. Profile what’s missing, what’s duplicated, and what looks like the same thing under three different names. Map fields across systems and normalize formats, IDs, and units so the records can work together.
• Find the pattern behind the misses. Break down results by source, file format, or record type. Is accuracy slipping across the board, or is one group pulling down the average? Follow the outliers and look for the few changes that would help the most.
• Run experiments and check your work. Build a set of examples with known answers. Try a change to a matching rule, prompt, or configuration, then compare results against your baseline. Check whether you caught more valid matches and whether you introduced new false matches along the way.
• Follow the data when something breaks. Read logs, inspect JSON payloads, and trace API requests and responses from clients’ ERP systems. Determine whether the issue started in the source data, the integration, the platform, or the ERP itself. Give engineering a clear bug report with steps to reproduce it.
• Make each rollout better than the last. Watch how the solution performs after launch. Turn recurring issues into reusable configurations, better validation checks, or clear feature specs for engineering. Test fixes before release using the cases that exposed the problem.
What you’ll bring:
• A degree in a technical field. Computer science, information systems, engineering, data science, or a related technical discipline.
• Experience at a software company. You’ve worked on a software product in a technical role, such as implementation, solutions, technical support, or product operations.
• You enjoy working with clients. You ask good questions, translate what you hear into a technical plan, and can guide users through a new workflow with confidence.
• You like exploring data. You’ve cleaned, joined, or mapped datasets before. When something jumps out, you can explain what you found, how you checked it, and what you’d try next.
• You understand how technical systems fit together. You’re comfortable working with APIs, structured data, logs, and application settings. You can follow a record across several systems and figure out where it changed.
• You understand AI models and enjoy analyzing how they perform. You’ve worked with large language models and understand how data quality, structure, and context affect their outputs. You can structure prompts, use representative datasets to spot patterns in errors, and measure whether your changes improve results.
• You explain your thinking clearly. You can show a customer what happened in plain language and give an engineer enough detail to reproduce it. You can also keep several investigations moving and make it clear what you’ve learned and what’s next.
Tools you’ll use:
You’ll use the platform’s admin console for client setup, Jira for bug reports, Asana for rollout tasks, and Slack and Email to stay in touch. Basic SQL for exploring datasets and JavaScript for custom field logic are helpful.
Familiarity with order workflows, from quotes and sales orders through shipping and freight, is helpful.
What success looks like:
Clients know what’s happening at each step and feel comfortable using the workflows you helped launch. You can show where accuracy improved or where people spend less time fixing exceptions. When the next client has a similar setup, the team can build on what you learned.
Principals only. Recruiters, please don't contact this job poster.