Senior Full Stack Engineer

Company Description

For over decade, we've been building the agentic call center that powers real customer conversations and automates operations across many different industries. Our proprietary AI Telco platform is a white labeled system that enables CRMs, Sales enablement platforms, and enterprise customers to carry out conversations and tasks using AI Voice, AI Text and AI Email. Known as the best Voice AI company in Home Services across the United States, Structurely is growing fast and looking for engineers who take real ownership, are independent and love building world-class products. We want ambitious engineers who love to code.

The Opportunity

Senior Fullstack/Backend engineer with high agency to own and evolve our backend services. You’ll build reliable, scalable systems that support real-time, high-throughput workloads (telephony + AI inference + integrations). Python is the primary language today, but we want someone excited to work in TypeScript as well, especially where it’s the right tool for the job.

You’ll help us scale on our current AWS container stack (ECS + Docker) while contributing to our migration toward Kubernetes.

Role Description

What You’ll Do - Own backend services end-to-end

Take primary ownership of key backend domains/services (design, implementation, deployment, uptime, iteration).

Write clear technical plans, make pragmatic tradeoffs, and drive work to completion without needing heavy process.

Establish and improve service-level standards: reliability, performance, observability, and maintainability.

Develop APIs and services that orchestrate agent workflows across LLM/TTS/STT vendors.

Design resilient patterns for retries, timeouts, fallbacks, rate limits, and circuit breaking across external providers.

Build capabilities that support real-time and near-real-time workloads; telephony latency constraints, event-driven processing.

Build and maintain integrations with multiple CRMs; bi-directional sync, webhooks, workflow triggers, identity mapping.

Support telecom integrations; events, call state, messaging, routing, configuration, ensuring reliability and traceability.

Create internal abstractions/adapters so integrations are consistent, testable, and extensible.

Model and operate systems using MongoDB as the primary datastore.

Use Aurora (RDS) where relational guarantees are required.

Use RabbitMQ for asynchronous workflows and background processing.

Use Redis for caching, ephemeral state, rate limiting, and coordination where appropriate.

Ship on Docker + ECS today; contribute materially to migration planning/execution toward Kubernetes.

Improve CI/CD, environment parity, and deployment safety; rollbacks, progressive delivery, migration strategies.

Partner with security/compliance needs; secrets management, auditability, least privilege, data retention.

Our Tech Stack (you don’t need all of this)

Languages: Python (primary), TypeScript (growing footprint)

Containers/Runtime: Docker, AWS ECS (current), Kubernetes (evolution)

Datastores: MongoDB (primary), AWS Aurora (RDS)

Messaging/Cache: RabbitMQ, Redis

Cloud: AWS networking, IAM, logs/metrics, container registry, etc.

Domain: Agentic orchestration, LLM/TTS/STT vendor integrations, CRM integrations, telecom integrations

Qualifications

Experience with telecom/telco systems (call routing, SIP/telephony infrastructure, messaging, carrier integrations).

7–10+ years of backend engineering experience with demonstrated end-to-end ownership of production services.

Strong proficiency in Python and solid engineering fundamentals APIs, data modeling, distributed systems basics.

Willingness and interest in contributing in TypeScript or strong desire to learn quickly.

Experience shipping and operating containerized services with Docker and a production orchestrator (ECS and/or Kubernetes).

Practical experience with MongoDB and/or relational databases Aurora/Postgres, including schema design and performance tuning.

Experience with messaging systems RabbitMQ or similar and caching Redis, including failure modes and operational concerns.

Strong debugging skills and an operator mindset: observability, incident response, and continuous reliability improvements.

High agency: you take ambiguous problems, turn them into plans, align stakeholders, and deliver.