Marcos Medina
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Telecommunication Engineer — AI Development & Automation

I engineer intelligent systems that listen, decide and act, from the phone line to the model and back.

Selected work LinkedIn(opens in a new tab)

01 — Profile

Every system I build starts with a signal. A voice on a phone line, the heartbeat of a router, the rhythm of a body in motion, a discharge hidden inside high-voltage equipment. My work is to capture it, understand it and engineer what happens next.

Now
AI Development & Automation at Ausarta
Trained as
Telecommunication Engineer, MSc UPV/EHU
Focus
Voice AI, automation, systems integration

02 — Selected Work

Four systems, four signals.

Voice, infrastructure, the body and the electromagnetic field. Each project starts from a different signal and ends in something that works.

  1. 01 AI Voice Agents Conversational AI × Telephony
  2. 02 Network Operations Platform Monitoring × Infrastructure
  3. 03 MarcosHealth Personal project × Health data & AI
  4. 04 Partial Discharge Localization in 3D Master’s thesis × Research
01/04 Conversational AI × Telephony

AI Voice Agents

Voice agents that pick up real phone lines, understand the request, validate it and get it done.

A conversational voice-agent system integrated with real telephony. ElevenLabs provides the voice components and agent platform, a custom orchestration proxy routes language-model calls to Cerebras with Groq as fallback, and a validation layer enforces required fields and business rules before anything is automated.

  • ElevenLabs
  • Cerebras
  • Groq
  • Orchestration proxy
  • Yeastar P-Series
  • Rule validation
View case study
  1. 01

    Ring

    The call arrives through the Yeastar P-Series PBX and is handed to the voice agent.

  2. 02

    Understand

    ElevenLabs handles voice in and out. Each turn passes through a custom orchestration proxy: Cerebras first, Groq as fallback.

  3. 03

    Validate

    Required fields and business rules are checked before anything happens. If something is missing, the agent asks instead of guessing.

  4. 04

    Act

    Validated requests become actions: messages taken, people notified, workflows set in motion.

02/04 Monitoring × Infrastructure

Network Operations Platform

One operational picture of routers, IP telephony and PBXs, honest about how fresh every value is.

An operations and monitoring platform for telecommunications infrastructure. A Node.js/Express backend integrates with Zabbix to bring routers, IP telephony and PBXs into a single operational view, and every panel declares the state of its data: live, snapshot, stale, refreshing or degraded.

  • Node.js
  • Express
  • Zabbix
  • Routers
  • IP telephony
  • PBX
View case study

Honest data, by design.

Fig. 02 Conceptual interface — not production screenshots

Model-written summary · sample data

“Training load this week sits above your four-week average, while sleep duration has stayed below it for three nights.”

03/04 Personal project × Health data & AI

MarcosHealth

A personal analytics lab for wearable data: trends, context and AI-written readings of recovery and activity.

MarcosHealth gathers health and activity data from wearable devices and turns it into something readable: long-term trends, context around recovery and training, and summaries written by AI models. It describes; it never diagnoses.

  • Wearable data
  • Data visualisation
  • Trend analysis
  • AI models
View case study

Fig. 03 Sample data — no medical interpretation

04/04 Master’s thesis × Research

Partial Discharge Localization in 3D

Locating electrical faults inside high-voltage equipment in three dimensions, with convolutional neural networks and optimization methods.

Partial discharges are tiny electrical breakdowns inside high-voltage insulation and an early sign of failure. They radiate electromagnetic pulses, so their position can be inferred from how those pulses reach a set of sensors. The thesis simulates that propagation with CST Studio, applies convolutional neural networks and optimization methods to estimate the source in 3D, and studies robustness against noise and multipath.

  • CST Studio Suite
  • Convolutional neural networks
  • Optimization methods
  • Signal processing
View case study

03 — Expertise

A working spectrum.

Six bands I operate across, from the physical layer to the product. Hover a band to tune in.

  1. 01

    Voice AI & conversational agents

    Voice agents that hold natural conversations on real phone lines, designed around latency, turn-taking and reliable outcomes.

    • ElevenLabs
    • LLM orchestration
    • Cerebras
    • Groq
    • Prompt & tool design
  2. 02

    Automation & systems integration

    Connecting models, telephony and business systems so a conversation or an event ends in a validated, automated action.

    • APIs & webhooks
    • Business-rule validation
    • Workflow automation
  3. 03

    IP telephony & PBX

    Voice infrastructure from the inside: PBX platforms, IP telephony and the call flows that tie them together.

    • Yeastar P-Series
    • IP PBX
    • VoIP
    • Call flows
  4. 04

    Networks & infrastructure

    Routers, devices and the monitoring that keeps them observable, with an operator’s eye for what actually matters.

    • Routing
    • Zabbix
    • Device monitoring
  5. 05

    Product & platform development

    Backends and interfaces that make complex systems usable: monitoring platforms, data-state design, product thinking.

    • Node.js
    • Express
    • Frontend
    • Data visualisation
  6. 06

    Signal processing & machine learning

    From electromagnetic simulation to neural networks: research-grade work on extracting position and meaning from signals.

    • CNNs
    • Optimization
    • CST Studio
    • Signal analysis

04 — About

Telecommunication engineer by training, builder by habit.

I’m Marcos Medina, a telecommunication engineer specialising in AI and automation, and I work where infrastructure and intelligence overlap. My background runs through IP telephony, PBX systems, networks and infrastructure; today I design and ship AI systems (conversational voice agents, automations and integrations) together with the product layers that make them usable and observable.

I like problems that span layers: a millisecond budget on a phone line, a data state on a monitoring screen, a wavefront inside a metal enclosure. Understanding the whole path is usually where the best solution is.

Experience

  1. AI Development & Automation

    Current

    Ausarta

    Conversational voice agents, automation and systems integration, from telephony to product.

  2. Telecommunications & infrastructure

    Hands-on experience with IP telephony, PBX, networks, infrastructure and monitoring platforms.

Education

  1. MSc in Telecommunication Engineering

    University of the Basque Country (UPV/EHU)

    Qualifying master’s degree for the regulated profession of Telecommunication Engineer. Thesis on 3D localization of partial discharges.

  2. Telecommunication Engineering

    Undergraduate studies in telecommunication engineering.

Areas of specialisation

  • Voice AI
  • Conversational agents
  • Automation
  • Systems integration
  • IP telephony
  • PBX
  • Networks
  • Monitoring
  • Product development
  • Signal processing
  • Machine learning

05 — Contact

Open a channel.

For engineering roles, collaborations or a good technical conversation.