Description
You’re a full-stack product engineer who wants ownership, not tickets. In this role, you will run an AI product end-to-end: meeting customers weekly, choosing what to build, and shipping to prod. Your two missions: make Kayako One resolve support tickets without humans and build an AI sales pipeline that takes prospects from first touch to close. You control the stack, the roadmap, the releases, and the outcomes.
Most of the industry walls engineers off from users and calls it “process.” We don’t. There’s no chain of PM → designer → “customer success” between you and reality. You’ll run weekly discovery calls, translate pain into product, ship fast, and measure real outcomes. You’ll also pioneer the AI sales automation stack that can become the template for how Trilogy sells across the portfolio. This is the place where adoption, resolution rate, CSAT, and pipeline velocity are the scorecard.
This job is owning the whole thing: new AI features in Kayako One that raise ticket resolution rates; integrations with CRMs and ticketing platforms; outreach workflows and targeting logic; pipeline connectors; reporting that proves what’s working; and the deployments, monitoring, and incident response to keep it all up. It is not a backend-only seat cranking tickets someone else specced, and it’s not a comfy lane with handoffs. You’ll write code as needed, wire up AWS like a pro, pick up tools like Voiceflow or Cursor without drama, and make LLMs behave in production instead of just demoing well.
You’ll sit at the pointy end of our help desk product and an AI sales automation strike effort, with portfolio-level visibility. Success looks like customers using what you ship, faster resolutions, happier end users, and a cleaner, faster-moving pipeline. If you want to own outcomes, talk to customers weekly, say no to the noise, and ship the thing that moves the number, this is your opportunity.
What you will be doing
- Build and ship Kayako One features—AI that boosts ticket resolution, CRM/ticketing integrations, scalable/reliable infrastructure, and performance/bug fixes.
- Run weekly customer discovery to translate real pain points into requirements and validate product direction with users.
- Build the AI sales automation stack—outreach workflows, pipeline/tool integrations, automated sales stages, and performance reporting.
- Own deployments and operations—full-stack releases, monitoring/alerting/incident response, and AWS/database infrastructure.
What you will NOT be doing
- It isn’t just writing code to a spec handed to you — you’re shaping what gets built through customer input.
- It isn’t work that stays in staging — everything you build goes to production and real customers.
- It isn’t narrow specialization — you own the full stack, infrastructure, and customer experience.
Key responsibilities
- Build and maintain an AI-powered customer support that resolves tickets without human agents
- Build and maintain a full AI sales pipeline that takes deals from first touch to close
Candidate requirements
- At least 5 years of professional software development experience
- Experience owning entire products or major systems, not just features
- Experience shipping AI/LLM-powered products to production (not just prototypes or demos)
- Deep AWS experience, including Lambda, S3, OpenSearch, RDS, CloudWatch, EventBridge, EC2, Route 53, CloudFront
- LLM/AI integration experience, including Claude/ChatGPT prompt engineering, API integration
- Experience coding in Python, Java, and JavaScript
- Experience using MySQL database
- Experience using Docker, deployment pipelines, and GitHub workflows
- Experience with OpenAI and JWT API development
- Experience with DNS management and web infrastructure
- Customer-facing experience
Applying for a role? Here’s what to expect.
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Interview with the hiring manager.
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