Senior Full Stack Engineer (Conversational AI and Voice Applications)

What you will own

• 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.

Engineering responsibilities

• 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.

Essential experience and skills

• 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.

Preferred experience

Absorb or another LMS; LTI 1.3, OIDC/SSO or secure external-tool launches; multi-tenant SaaS; rubric-based AI evaluation; training/coaching products; insurance workflows; document retrieval; and integrations with Sheets, BigQuery, HubSpot or Zapier. Avatar integration is useful if later included in scope. These are advantages, not requirements to know every platform.

Role Details

Company & Location

Attain Solutions | Remote within India; Bengaluru preferred

Contract and capacity

Planned 8-12 weeks, full time at approximately 35-40 hours per week

Initial assessment

Paid 1-2 weeks; subsequent build work depends on the selected approach and project approval

Experience and start

Typically 5-8 years in software engineering; relevant delivery evidence takes priority. Near-term availability preferred.

Proposed duration and milestones

We recommend planning an initial 8-12-week engagement from kickoff. The paid assessment comes first. The remaining phases proceed against an agreed scope, estimate and project approval; their timing depends on the chosen route, content readiness and access.

Phase 1: Technical assessment

Duration

1-2 weeks

Expected outcome

Options and reuse assessment; architecture; integration risks; work estimate; operating-cost assumptions; recommendation.

Phase 2: Voice prototype

Duration

2 weeks

Expected outcome : A hosted two-way practice example and sample assessment on approved or clearly marked demonstration content; documented limitations.

Phase 3: First pilot release

Duration

4-6 weeks

Expected outcome: Agreed personal/commercial pair, learner access, usage controls, scoring, coaching PDF, structured results and required integration.

Phase 4 : Validation and handover

Duration

1-2 weeks

Expected outcome

User testing, scoring calibration with content specialists, defect fixes, deployment and documented handover.

This is a staffing allowance, not a committed production release date. A focused extension of an existing platform may need less time; additional integration or product scope must be estimated separately.

What successful delivery looks like

• 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 bou