AI Experience Engineer (Conversational AI)

Remote · USD 140,000-180,000 · 3-5 years experience · Remote · Posted Oct 13, 2026

At a glance

An AI Experience Engineer owns the full lifecycle of the journeys our customers have with Upgrade's AI agent on chat, voice and email: creation, optimization, edge case handling and containment growth.
You will sit between engineering, product and customer operations to turn servicing workflows into production journeys and keep improving them after launch.
Within your first year, you will own a portfolio of journeys across products and help set the standards for how Upgrade builds, tests and ships AI experiences.

Journey creation: Design and build Sierra journeys in Agent Studio for chat, voice and email, from discovery with operations through production rollout
Optimization: Review transcripts, recordings and analytics every week, find where conversations fail or transfer, and ship fixes to journey logic, instructions and knowledge
Edge case handling: Map the unhappy paths (failed payments, mismatched identity, delinquent accounts, unsupported requests) and make sure each ends in a correct answer or a clean handoff
Containment: Own containment and CSAT targets per journey, run staged rollouts (1% → 100%), and prioritize the work that moves those numbers most
Product partnership: Work with product groups (Personal Loans, Card, BNPL, Deposits) to scope new journeys, keep journeys current as products change, and define the APIs the agent needs
Safety and compliance: Apply tiered authentication and step-up verification, verbatim compliance language and guardrails against hallucination and off-policy answers
Handoffs: Design transfers to human agents in Genesys with accurate summaries and auth context
Testing: Build simulation and regression suites so every journey change ships with evidence it did not break existing behavior
Monitoring: Watch latency, errors and drop-offs in SumoLogic and Grafana, and own the alerts
Voice tuning: Latency, filler phrases, interruptions, personality and tone

3–5 years of Frontend Software Engineering experience, or equivalent experience in Solutions Engineering, Conversational AI or Technical Product roles
Working knowledge of how LLM agents behave: instructions, tool calls, knowledge retrieval, and where each one fails
Experience building evaluations for non-deterministic systems: test sets, simulations, LLM-as-judge, regression gates
Enough technical depth to read API specs, work with backend engineers on REST and GraphQL integrations, and reason about authorization and permission scopes
Working knowledge of JavaScript/TypeScript, with the ability to build and maintain coded journeys and integrate APIs within conversational AI platforms
Product and customer mindset: you understand ops procedures, you read transcripts, care about tone, and measure success by whether the customer's problem got solved
Ownership in production: rollouts, monitoring, log analysis and incident response
Clear writing and the ability to work with non-engineers in operations, compliance and legal

Hands-on experience with Sierra Agent Studio, or a comparable no-code agent platform (Decagon, Ada, Kore.ai, Google CCAI, Amazon Lex/Connect)
Voice AI experience: speech-to-text, text-to-speech, latency tuning, barge-in handling
Contact center systems such as Genesys, and agent handoff design
Background in fintech or another regulated industry (UDAAP, FDCPA, TCPA, PCI, SOC 2)
Conversation design or UX writing experience