Overview

Company Description

Responsibilities

• Attain Solutions provides software development, implementation, quality assurance and support services for international clients. We are seeking a hands-on senior engineer to assess and deliver a voice-based practice capability for a US training business serving insurance agencies.
• In the proposed experience, the AI plays a customer throughout a short conversation. The learner speaks naturally, while the customer raises a relevant concern, responds to questions and keeps its facts and character consistent. After the session, a separate assessment produces scores and a coaching PDF. The first scope is a personal-lines and commercial-lines pair, using client-approved content.
• Assess existing LMS capabilities, reusable prototypes and focused extensions before recommending a configured or custom solution. Document feasibility, dependencies, delivery effort and operating costs.
• Build a working two-way voice prototype, including responsive audio, turn-taking, interruption handling, session state and recovery from common failures.
• Implement the customer role with approved facts, a persona, objections and an objective. Support varied learner responses and natural endings without feeding the learner the expected answers.
• Convert approved training material into configurable, versioned scenarios and rubrics. Keep the customer simulation separate from post-session assessment.
• Investigate launch from Absorb LMS, browser microphone access and learner identity. Validate an embedded experience and a separate-tab fallback; implement the agreed access and completion approach.
• Produce evidence-based scores and balanced coaching. Apply approved weights, exclusions and serious-error rules; calculate totals in code and keep the PDF consistent with the underlying results.
• Store learner, agency, scenario, rubric and attempt records. Generate branded PDFs and an agreed basic export; preserve structured data for later reporting integrations.
• Implement agency and learner usage allowances, reset rules, alerts and limits as agreed. Handle simultaneous requests, retries and failed attempts without duplicate charging or results.
• Protect agency data boundaries, credentials and recordings. Apply agreed access, retention and deletion rules, with useful logs that do not expose unnecessary personal data.
• Deploy and maintain the application, manage environments and secrets, monitor latency and usage, resolve defects and hand over source code, configuration and operating documentation.

Qualifications

• Proven ownership of at least one working two-way voice application or conversational product with spoken interaction. Be ready to explain your contribution, architecture, latency, interruption handling, failure recovery and usage costs.
• Strong frontend development with TypeScript and React or a comparable framework; browser audio capture and playback, asynchronous UI behaviour, microphone permissions and session error states.
• Backend development in Python, for example FastAPI, or Node.js with TypeScript; REST APIs, WebSockets and/or WebRTC integration, authentication, background work and relational data modelling.
• Practical integration of LLM and speech services, using either real-time speech-to-speech or speech recognition, a language model and speech synthesis. Strength in one coherent stack is sufficient.
• Prompt and context design, structured model outputs, scenario grounding and evaluation. Ability to test responses against approved facts and recognise when the system should acknowledge missing information.
• Third-party API integration, secure session handling, SQL databases such as PostgreSQL, PDF generation and reliable export workflows.
• Automated testing and debugging across the browser, backend and AI services; Git, code review, deployment pipelines, Docker or equivalent packaging, and one cloud environment.
• Clear written English and the ability to translate a business requirement into a small, testable release, explaining assumptions and trade-offs to a non-technical project lead.
• The AI sustains the approved customer role across different learner approaches, raises the required practice opportunity and keeps scenario facts consistent.
• Representative strong, mixed and weak attempts are reviewed with the content specialists. Scores and feedback reflect demonstrated behaviour, with omissions and technical failures treated appropriately.
• Agreed browsers and LMS launch paths work. Access boundaries, usage limits, retries and common audio failures have been tested with Attain QA.
• Coaching PDFs match stored results. Actual audio measures are distinguished from text-derived estimates; optional speaking metrics are included only when agreed and validated.
• Source code, scenario and rubric configuration, deployment instructions, monitoring, cost assumptions and a support runbook are handed over.
• Standard work timing: 3:00 PM to 12:00 AM IST, to ensure sufficient overlap with Tango Analytics US-based teams and clients.
• Flexibility may be required during critical project milestones, deployment activities, go-live events, and production support periods.
• Location: Remote. Overlap with US morning and/or evening hours required.