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Urgent! Python Developer — Data Engineering Job Opening In Colombia, Colombia – Now Hiring R. Phants & Associates LLC

Python Developer — Data Engineering



Job description

Python Developer — Data Engineering & AI Automation

(GCP, VoIP/Telephony, LLMs & MLOps)

TL;DR
: Build production-grade data pipelines and real‑time voice automation.

You'll ship Python services on
GCP
(BigQuery, Dataflow, Pub/Sub, Cloud Functions/Composer/Vertex), integrate
Twilio/Asterisk/Vicidial
, and operationalize
LLM + TTS/STT
workflows with strong data/infra reliability.

Why this role matters

Our products power AI-driven communications (including ringless voicemail automation) at scale.

Your work will turn messy call events, transcripts, and analytics into reliable, low‑latency systems that drive customer outcomes and revenue.

What you'll do (Outcomes)

  • Ship reliable data pipelines
    in GCP (BigQuery, Dataflow, Pub/Sub, Cloud Functions, Composer) with
    SLOs
    for latency, throughput, and cost per GB processed.

  • Build Python backends/APIs
    (FastAPI/Flask), codify contracts with
    Pydantic
    , manage persistence via
    SQLAlchemy + Alembic
    , and keep schemas & migrations healthy across environments.

  • Own VoIP integrations
    : call routing, voicemail drops, campaign automations with
    Twilio (Voice, Messaging, Studio, Conversations, TaskRouter)
    ; customize/scale
    Asterisk/Vicidial
    for outbound dialing.

  • Operationalize voice AI
    : integrate
    TTS/STT
    (Cartesia, ElevenLabs, Google, AWS Polly), wire
    real‑time STT → intent → TTS
    loops, and measure WER/latency.

  • Enable LLM workflows
    : build dataset prep, evaluation, and inference pipelines; support
    Vertex AI
    jobs, registries, CI/CD, monitoring, and rollbacks.

  • Make systems observable
    : metrics, traces, and logs (e.g., OpenTelemetry, Cloud Monitoring) with dashboards and actionable alerts.

  • Collaborate
    with data/ML/DevOps/product on architecture, reviews, and production readiness.

Tech you'll touch

Python, FastAPI/Flask, Pydantic, SQLAlchemy, Alembic, PostgreSQL/MySQL

GCP
: BigQuery, Dataflow, Pub/Sub, Cloud Functions, Cloud Run, Composer (Airflow), Vertex AI, Cloud Storage

VoIP
: Twilio (Voice/Messaging/Conversations/Studio/TaskRouter),
Asterisk/Vicidial
, SIP/RTP

Voice/LLM
: Cartesia, ElevenLabs, Google TTS/STT, AWS Polly, Whisper (as applicable)

Platform/Tooling
: Docker, Terraform, GitHub Actions, pytest, Ruff/mypy, OpenTelemetry, Prometheus/Grafana/Cloud Monitoring

Must‑have skills

  • Python
    expertise for APIs, services, and data pipelines.

  • GCP
    experience (BigQuery, Dataflow, Pub/Sub, Storage, Composer, Vertex AI).

  • Pydantic
    for validation;
    SQLAlchemy
    for ORM;
    Alembic
    for migrations.

  • Strong
    SQL
    and relational schema design.

  • Practical
    VoIP/telephony
    knowledge (SIP/RTP, call flows) and
    Twilio
    APIs.

Nice‑to‑have skills

  • Cartesia/ElevenLabs
    and other TTS/STT providers.

  • Asterisk/Vicidial
    customization & scaling (e.g., AMI/ARI).

  • LLM integration (GPT/PaLM/OSS), prompt/latency optimization in real‑time paths.

  • MLOps
    (Vertex pipelines, model registry, evaluation/monitoring).

  • Event streaming
    (Kafka, Pub/Sub).

  • Security/Compliance awareness
    for voice/data (e.g., PII redaction, call recording governance; STIR/SHAKEN/TCPA considerations where relevant).

How we work

  • Remote/hybrid flexibility; async‑first with clear ownership and fast feedback loops.

  • Production‑minded: testing, canaries, rollbacks, and on‑call rotation shared across the team.

  • Ship small, measure impact, iterate.

Success looks like (30/60/90)

  • 30 days
    : Production access + dashboards; ship a small service or pipeline; add unit/integration tests around a Twilio webhook or Pub/Sub consumer.

  • 60 days
    : Replace a fragile ETL with
    Dataflow
    ; cut pipeline cost/latency by ≥25%; harden Alembic migrations with blue/green strategy.

  • 90 days
    : Launch a real‑time
    STT → LLM → TTS
    microservice with SLOs (

Compensation & benefits

  • Competitive
    salary + performance incentives
    .

  • Remote/hybrid, learning budget (GCP certs, ML/telephony), modern tooling, and clear growth paths.

Hiring process (what to expect)

  1. Intro call
    (role fit, past systems you've owned).

  2. Technical deep‑dive
    (data pipeline & telephony scenarios).

  3. Practical exercise
    (see below) or code walkthrough.

  4. Panel
    with ML/DevOps/product on cross‑functional design.

  5. Offer.

Practical exercise (2–4 hours, take‑home or live)

  • Build a small
    FastAPI
    service that:
  • Validates an inbound
    Twilio Voice
    webhook with
    Pydantic
    ,
  • Publishes events to
    Pub/Sub
    ,
  • Streams to
    BigQuery
    via
    Dataflow
    (template or Python SDK),
  • Manages tables/migrations with
    Alembic
    ,
  • Includes
    pytest
    tests and basic
    OpenTelemetry
    traces.

  • Bonus: integrate a
    TTS/STT
    provider and measure E2E latency.

Equal opportunity

We welcome applicants of all backgrounds and identities.

If you're excited by the role but don't meet 100% of the bullets, please apply—
skills grow quickly in our environment
.


Required Skill Profession

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