Senior Full Stack Engineer (Conversational AI and Voice Applications)

Attain; India; Remote; INR 1,515,000 - 2,755,000; Full time

Job summary

Attain Solutions in India seeks a software engineer to own a conversational voice product, build a robust frontend with TypeScript/React, and a Python/Node.js backend. You will integrate real-time speech services and LLMS, ensuring secure sessions and scalable data handling.

The role focuses on delivering a hosted voice prototype, maintaining data integrity, and coordinating with cross-functional teams. Remote work within India is offered for a 8–12 week contract at ~35–40 hours/week.

Qualifications

• Ownership of at least one working two-way voice app
• Strong frontend development with TypeScript and React; browser audio capture, playback and session handling
• Backend development in Python or Node.js with REST/WebSockets and data modelling
• Practical integration of LLM and speech services with a coherent stack
• Prompt and context design for testable outputs and grounded responses

Responsibilities

• Produce evidence-based scores and PDFs
• Store learner, agency, scenario, rubric and attempt data; export workflows
• Manage usage allowances, alerts and limits; handle concurrent requests
• Protect data boundaries, credentials and recordings with logs
• Deploy and maintain the app, monitor latency and environment secrets

Skills

Two-way voice app

TypeScript & React

Python/Node.js

Speech/LLM integration

Prompt design

Tools

REST APIs

WebSockets

PostgreSQL

Docker

Job description

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