Senior Full Stack Engineer (Conversational AI and Voice Applications)
First seen by Alion on Oct 31, 2026.
- 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 experienceAbsorb 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 DetailsCompany & 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 assessmentDuration : 1-2 weeks
Expected outcome : Options and reuse assessment; architecture; integration risks; work estimate; operating-cost assumptions; recommendation.
Phase 2: Voice prototypeDuration : 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 releaseDuration: 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 handoverDuration : 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 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.
Working arrangements and ongoing supportProvide a weekly demonstration, maintain an agreed task tracker and flag blockers early. Be available for scheduled US-time-zone discussions, with the overlap agreed in advance. Part-time support may continue for 3-6 months after the initial engagement, with scope and hours agreed separately; a starting planning allowance is 10-20 hours per month.
What to include when applyingPlease share your CV or profile, earliest start date, weekly availability and expected hourly or monthly contract rate. Include a relevant voice-application demo or architecture walkthrough, your exact contribution, and one example of a difficult production issue you resolved. A degree in a relevant discipline or equivalent practical experience is suitable.
Selection will focus on a technical discussion and a walkthrough of relevant work. The selected engineer will begin with the paid assessment described above. Training content and grading standards will be supplied and approved by the client specialists; Attain will coordinate scope and QA support.
Terms- 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.
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.
Originally posted on Himalayas