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greenhouse

AI Experience Engineer (Conversational AI)

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Remote, CAN
Mid · 3–5 years experience
Remote
Discovered 1 weeks ago
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Full Job Posting

What We Look For:

  • 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

Nice To Have:

  • 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
  • What We Offer You:
  • Competitive salary ($140K-$180K CAN) and stock option plan
  • Paid coverage of medical, dental and vision insurance
  • Flexible PTO
  • Opportunities for professional growth and development • Paid parental leave
  • Health & wellness initiatives
  • Opportunities for professional growth and development
  • Paid parental leave

Responsibilities

  • 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
  • Sierra relationship: Be the technical owner on our side, escalate platform issues and shape roadmap asks
  • 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

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