Principal Software Architect

InnovaccerHealthcare AI

Workable workplace: remote; Workable locations: United StatesFull-TimePrincipal

Salary not disclosed

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Job Details

Bring 8+ years of backend engineering experience, including technical ownership of a complex, multi-service system.
Have strong Python proficiency, including async programming with asyncio, and production experience with FastAPI or Django.
Have experience designing distributed, multi-service architectures, including event-driven systems such as Kafka, service-to-service authentication, webhook integrations, and idempotency and retry design.
Have experience with MongoDB or another NoSQL database and working knowledge of PostgreSQL.
Have direct production experience building or operating conversational AI or voice-agent systems, including telephony, IVR, or conversational voice platforms.
Have experience with latency-sensitive real-time pipelines such as speech-to-text, speaker separation, and text-to-speech.
Have experience designing real-time decisions from streaming context, including intent detection, recommendations, or next-best-action logic with confidence thresholds and human escalation.
Have experience with LLM or agent frameworks and a working understanding of agent evaluation and reliability practices.
Have a track record of driving architecture decisions across teams, writing and reviewing technical design documents, and mentoring engineers.
Be comfortable with Docker or containerized deployments, CI/CD, and observability tooling for production diagnosis across a service mesh.
Be proficient with Git and collaborative workflows.

Own architecture for the AI voice agent platform, next-best-action assistant guidance, or standalone AI agents across voice, chat, and SMS.
Design real-time, low-latency systems for in-call intent detection and next-best-action suggestions.
Design an orchestration layer that exposes reusable AI agent workflows, with output contracts and versioning.
Define patient and customer identification, context retrieval, and escalation contracts, including safe failure, human handoff, and audit trails.
Drive the AI agent evaluation and reliability framework and set SLOs for agent-facing services.
Lead technical design reviews across backend services and drive architectural consistency.
Design and build backend services in Python, model data in MongoDB and PostgreSQL, and build Kafka-based event streams.
Work hands-on with LLM and AI agent tooling for scheduling agents, in-call recommendations, and automated documentation.
Set testing, observability, and production triage practices, and mentor engineers on distributed systems and AI agent design.
Partner with product on scoping initiatives and apply healthcare data security and compliance practices.

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