Junior/Intermediate Applied AI Specialist (Voice AI)

**Role Overview** We are looking for a motivated Applied AI Specialist to join our growing Voice AI team. This role suits candidates who combine a solid grounding in software engineering fundamentals with strong testing discipline and a customer-focused mindset. You will initially own feature testing and quality assurance for our Voice AI products, which are built with platforms such as ElevenLabs, Twilio, and Amazon Connect, and grow into a Forward Deployed Engineer (FDE) role, configuring, deploying, and iterating on AI solutions directly with customers. Clear, confident communication is central to this role, as you will regularly engage with customers and be expected to articulate technical concepts in a simple and professional manner. You will work under the guidance of senior team members and gain hands-on experience across the full lifecycle of applied AI products, from development through to production **Key Responsibilities** • Own feature testing for Voice AI products: design test cases, execute test plans, log defects, verify fixes, and run regression testing ahead of releases. • Apply established testing practices such as test-driven development (TDD), property-based testing, and unit, integration, end-to-end, and user acceptance testing. • Validate features across deployment environments (development, staging, and production) and support the controlled promotion of releases from one environment to the next. • Act as a Forward Deployed Engineer: configure, deploy, and support Voice AI solutions in customer environments, including pilots and production roll-outs. • Communicate and articulate clearly with customers: explain technical concepts, findings, and progress in a simple, confident, and professional manner. • Reproduce, triage, and clearly document issues, and collaborate with engineers to resolve them. • Track and manage work using project management tools such as Jira and Linear, including tickets, sprints, backlogs, and bug tracking. • Gather feedback from customers and internal stakeholders and translate it into clear, actionable tickets and requirements. • Evaluate the quality of AI models using appropriate evals, and make sound judgements on trade-offs between latency, classification metrics (accuracy, precision, recall, and F1), and cost. • Stay current with developments in AI and Voice AI, and proactively bring new tools, techniques, and ideas to the team. • Document test results, workflows, configurations, and findings clearly and comprehensively. **Projects** **​** • Voice AI agents and conversational automation. • Audio recording, transcription, and conversation analytics features. • Customer-facing AI deployments, integrations, and automation initiatives. ### Requirements **Experience:** • Hands-on experience building or configuring solutions with Voice AI platforms such as ElevenLabs, Twilio, or Amazon Connect, or familiarity with telephony concepts (e.g., SIP, WebRTC, IVR flows). • Familiarity with cloud platforms such as AWS, Google Cloud, or Azure. • Experience with API testing tools (e.g., Postman) or automated testing frameworks (e.g., pytest, Jest, Playwright). • Understanding of CI/CD pipelines and release management processes. • Prior experience in a customer-facing, QA, support, or implementation role. • Awareness of prompt engineering and the evaluation of LLM outputs. **Skills & Competencies:** • Qualification in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related field (or equivalent practical experience). • A strong understanding of version control with Git, including branching, merging, and pull request workflows. • Solid understanding of core software engineering principles, including the purpose of separate deployment environments (development, staging, production) and how changes are promoted between them. • Working knowledge of software testing methodologies, including TDD, property-based testing, and common approaches such as unit, integra…