About AptEdge
We build AI agents for B2B technical support. The agent pulls from everything a support org already has (tickets, docs, CRM, chat, bugs, codebase) and works a case the way a good senior engineer would, from investigation to resolution. We live inside the tools support teams already use: Zendesk, Salesforce, ServiceNow, Slack, Jira, Confluence. Backed by top VCs and Founders.

The Role
Every customer we sign has to go from contract to a working, trusted AI agent workflow, and you're the person who gets them there. You'll set up their integrations, tune what the agent can see and say, write the runbooks that tell it how that customer resolves a given class of ticket, and stay close enough afterward to know when something has drifted. Most of that is configuration. Some of it is code, and when it is, you'll write it yourself rather than filing a ticket and waiting.
You'll be part of our Customer Success org, because the role is evaluated on whether customers adopt, expand, and renew. You'll also spend time working with the R&D team. When you find something in a deployment that's a product problem and not a config problem, you should be able to walk over and fix it, or at least get it fixed fast.

What You'll Work On
Getting customers live
Setting up integrations, SSO and SAML, IT and systems administration, and checking that what we’re integrated with is actually what they meant to give us. Co-ordinate with customers and admin/IT teams over calls and async to run enablement.
Customizing the product
Overall setup, prompt engineering, search filters, ranking, how answers get formatted, branding, embeds. Whatever it takes to make AptEdge feel native to that customer.
Data understanding and engineering
Sometimes it's the source data. Sometimes it's indexing, a filter, or a prompt. You'll trace it through pipelines, logs, and the database and fix the layer that's actually broken.
Technical Prompt Engineering
Work on a live LLM powered platform that empowers very technical engineers and agents to deliver business value. Understand data in depth to understand build agentic workflows and pipelines.
Writing some code
Building and fixing connectors, self-service features, ingestion for the odd knowledge sources customers throw at us, and internal tooling so the third time we do a customization it's a setting instead of a project.
Monitoring and optimizing customer health
Reporting on usage and resolution per account, alongside CS. You'll see a stalled deployment before the customer does and know how to unstick it.
Growing accounts
You'll own the technical half of expansion: scoping new use cases, discovering value, empowering business partners, and coordinating with internal go-to-market and engineering teams.

You Need

• 5+ years in solutions, implementation, and backend engineering at a B2B SaaS company
• To have supported an LLM or RAG product that real customers used in production
• Solid Python and TypeScript, and comfort working in a large codebase in collaboration with engineering teams
• Hands-on experience with enterprise identity (SAML, OAuth2, SSO) and third-party APIs, including the ugly parts: rate limits, webhooks, eventual consistency, prompt engineering & testing
• Clear written and spoken English to communicate with customers and IT/engineering teams.
• Availability for customer calls through US working hours. The rest of your day is yours to arrange.
• Experience with cloud and debugging tools such as GCP/AWS, Sentry, PagerDuty, etc.

It Helps If You Have

• Admin or config experience in Zendesk, Salesforce Service Cloud, or ServiceNow
• Direct experience supporting live, production-grade retrieval-augmented generation systems
• Background with Kubernetes or React web applications
• A feel for the commercial side. You know adoption is what drives renewal, and you can tell a customer who's stuck from one who's just not using it
• A habit of owning problems from beginning to end, including identifying opportunities to be proactive in support of customer or internal goals.
• Previous working experience as a Support Engineer

How We Work

• Small team, high ownership. Small PRs, and we pair when a problem is hard
• Customer-facing engineers ship code here. Your work goes in the main repo and gets reviewed as per engineering contribution process
• CS and R&D look at the same customer data. You'll be in both rooms and carry context between them