About the RoleTechnical Solution Architects (TSAs) own the technical side of every customer implementation at Loop: taking a signed enterprise customer from scope to live production, designing how their data lands in Loop, building the integrations and rules their business needs, and leading the cutover. This is an AI-first engineering role: TSAs build and operate the agentic workflows that configure tenants, author rules, validate data, and triage issues, and write the skills, harnesses, and evals that make those agents trustworthy in production, with the explicit goal of automating last quarter's work to take on harder work this quarter. It is also a client-facing delivery role, with technical discovery alongside customer architects and ERP teams, committed go-live dates, and real escalations from some of the largest supply chains in the world. The role sits within Loop's Solution Delivery function, partnering with Implementation Managers, Customer Success, and Product and Engineering, and is distinct from Loop's Forward Deployed Engineering team, which explores zero-to-one product opportunities within Engineering.
This is an in-person role based in San Francisco, CA, with the expectation of being in the office 4+ days per week.
Ability to travel up to 25%.
What You'll Do- Own technical delivery for a portfolio of enterprise customer implementations, from signed scope through production go-live, working to committed dates and go-live gates and holding the quality bar: every implementation validated against real customer data before cutover.
- Lead technical discovery with customer stakeholders: turn signed scope into specific, testable requirements, make the design decisions on data model, field mapping, and integration patterns, and partner with Sales and Solutions Engineering on feasibility and effort for non-standard requirements before signature.
- Build and operate agentic workflows for delivery: encode implementation know-how as skills and runbooks agents execute, design the harnesses they run in, and write the evals that prove they are correct before they touch production.
- Design and build customer integrations: EDI and carrier feeds, SFTP and API ingestion, ERP and payment-system egress (SAP, NetSuite, Oracle, TMS platforms), and custom parsers and transformations for messy real-world data.
- Configure the customer's tenant: audit policies, rating and contract logic, cost allocation and GL coding rules, carrier and payee setup, and the cutover from test to production.
- Be the technical voice to the customer when things go wrong: diagnose, fix what is configuration, and hand Engineering a clean, reproducible product issue when it is not.
- Turn what you learn in the field into product: feed patterns, gaps, and tooling needs back to Product and Engineering so each implementation is faster than the last.
About You- You build with AI agents as a matter of course. You use coding agents daily for real engineering work, and you think in terms of what to delegate, how to structure context and tools so an agent succeeds, and how to verify its output. You can explain where agents fail and what you do about it.
- You are a hands-on engineer: TypeScript or Python, SQL, and cloud infrastructure (AWS), with hands-on experience integrating enterprise systems such as ERPs, TMS platforms, EDI, SFTP, and APIs.
- You are credible with enterprise customers. You can run a technical call with a customer's architects, push back on scope, and keep a difficult escalation constructive.
- You are comfortable owning outcomes with minimal oversight: dates, go-lives, and customers are yours.
- You thrive in a role that changes shape. You would rather automate a process and move on than keep doing it by hand.
- You communicate clearly in writing and in person, with technical and business audiences alike.
- You have experience at an early-stage or high-growth company and are used to wearing multiple hats.
Nice to Have - Deep understanding of agentic AI architecture: multi-agent systems, tool use and MCP, context engineering, agent harnesses, evaluation frameworks and evals, prompt and skill design, guardrails, and observability for LLM-driven workflows.
- Experience shipping agentic workflows to production and operating them: persistent agents, human-in-the-loop design, and measuring reliability over time.
- Experience owning a full customer deployment from problem to working production system, in a solutions architect, forward deployed engineer, implementation, or field engineering role.
- Supply chain, logistics, freight, or transportation domain experience; freight audit, freight payment, or accounts payable is a plus.
- Experience with distributed systems, workflow orchestration, or data pipelines at scale.
Compensation and BenefitsThe base pay range for this role is $175,000 to $195,000 annually. This range reflects the base pay that Loop reasonably expects to pay for the position at the time of hire. Actual compensation will depend on job-related factors, including experience, skills, qualifications, location, and business needs.
In addition to base salary, this role may be eligible for an annual performance bonus and equity. This role is also eligible for Loop's benefits, including health, dental, and vision insurance, 401(k) match, paid time off, paid holidays, and parental leave.
