🇳🇱 Netherlands · 2h ago
AI Solutions Engineer
Fini
LinkedInjuniorEnglish-friendly
About the roleFini is building the future of enterprise customer support, and is backed by top investors including YC and Matrix. Our self-learning AI agents autonomously resolve up to 90% of customer tickets, lift CSAT by double digits, and cut support costs for companies like Bitdefender, TrainingPeaks, and Cover Genius.Getting an enterprise AI agent into production means understanding how a business works: its policies, its systems, its customers, and the situations where getting something wrong matters. It takes someone who can sit with a customer, unpack a messy workflow, build the solution, and stay close until it works reliably.We’re looking for an AI Solutions Engineer to own that journey, from technical discovery through deployment and ongoing performance. This is a forward-deployed engineering role. You’ll work directly with customers and our engineering team to connect systems, configure agent workflows, define what “correct” looks like, and get agents performing reliably in the real world.Fini’s self-learning tooling is central to that work. You’ll build the evaluation signal that powers the improvement loop, diagnose what’s holding an agent back, and verify that each iteration delivers better customer outcomes.What you will own: Enterprise deployments, end to endOwn the technical implementation from the first customer working session through go-live and beyond. Understand customer workflows, translate business requirements into agent behavior, and agree on measurable success criteria. Lead working sessions, resolve technical dependencies, and keep customers informed as their deployment progresses.Integrations and agent workflowsConnect Fini to customer help desks, knowledge sources, and backend systems through APIs. Write and debug scripts, configure workflows, and enable agents to take actions with the right permissions, validation, and escalation paths. Test the complete customer journey, including what happens when an integration fails or an exception needs a human.Evaluations and self-learningDefine what a correct resolution looks like for each customer. Build and maintain golden sets—curated conversations and expected outcomes, and regression tests that reflect real customer scenarios. Use Fini’s self-learning tooling to improve agent performance, measure the impact of each change, and catch regressions before they reach customers.Production performance and debuggingInvestigate why an agent gave the wrong answer, missed a step, or failed to complete an action. Work through conversation traces, knowledge retrieval, instructions, tool calls, and API responses to isolate the root cause. Verify fixes and track their impact on resolution, accuracy, escalation, and customer satisfaction.Making every deployment betterTurn recurring customer problems into reusable tooling, better defaults, and clear product requirements. Work with engineering to address issues at their source. Document what works so the next deployment is faster and the Solutions team can operate at greater scale.What we're looking for: Hands-on technical ability. You can work with Python, APIs, structured data, and logs to investigate problems and build practical solutions. You use AI to move faster while understanding, testing, and taking responsibility for what you ship.Practical LLM experience. You’ve built or meaningfully improved something with LLMs. You understand how context, retrieval, instructions, tool use, and evaluations shape an agent’s behavior.Structured problem-solving. You can turn an ambiguous issue into a testable hypothesis, isolate the root cause, and demonstrate that your fix works.Customer-facing confidence. You ask good questions, explain technical trade-offs clearly, and can work with both a Head of Support and an engineering team.Ownership and attention to detail. You follow problems through to a working outcome, communicate blockers early, and care about the edge cases that determine whether a customer trusts the system.Bonus pointsExperience in solutions engineering, forward-deployed engineering, or enterprise implementations. Familiarity with customer-support platforms such as Zendesk, Intercom, or Salesforce, SQL and analytics, or operating AI systems in production.What success looks like: Enterprise customers go live with reliable integrations, clear success criteria, and agents they trust.Your work produces measurable improvements in agent performance and customer outcomes.Evaluations catch regressions before release, and production failures lead to fixes that prevent repeat issues.Each deployment contributes reusable tooling, stronger workflows, or product improvements that help the wider team.You develop a deep understanding of how Fini behaves in production—and can explain to a customer what happened, why it happened, and what you’re doing about it.Why join Fini:You’ll work on AI handling millions of real customer conversations, with direct visibility into the impact of what you build. You’ll get hands-on experience with self-learning systems and meaningful ownership of enterprise deployments.You’ll work directly with a founding team from Uber, backed by Y Combinator and Matrix. The problems you solve with customers will help shape what we build next.LocationAmsterdam · RemoteHow to applySend your LinkedIn, résumé, and a short note about a technical problem you’ve solved to careers@usefini.com, with the subject line “[AI Solutions Engineer] at Fini.”Sourced from LinkedIn. Relocantly aggregates public job postings; apply on the original site.