Junior/Intermediate Applied AI Specialist (Voice AI)

• 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.

• Voice AI agents and conversational automation.

• Audio recording, transcription, and conversation analytics features.

• Customer-facing AI deployments, integrations, and automation initiatives.

Requirements

• 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.

• 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, integration, regression, end-to-end, and exploratory testing.

• Proficiency in feature testing: test case design, structured execution, defect reporting, and verification.

• Awareness of Voice AI technologies and platforms, such as ElevenLabs, Twilio, and Amazon Connect, and of core concepts like speech-to-text (ASR), text-to-speech (TTS), and voice agents.

• Good understanding of model evaluation, including classification metrics such as accuracy, precision, recall, and F1, and the ability to reason about trade-offs between quality, latency, and cost.

• Familiarity with project management and issue-tracking tools such as Jira and Linear.

• Familiarity with at least one programming or scripting language (e.g., Python or JavaScript/TypeScript).

• Able to work effectively with AI-assisted development tools such as Claude Code and Codex.

• Strong analytical and problem-solving skills, with high attention to detail.

Benefits

• Competitive salary and benefits.

• Hands-on experience with real-world Voice AI products and customer deployments.

• Mentorship and a clear growth path toward a full Forward Deployed / Applied AI Engineer role.

• A collaborative and supportive work culture.