Arganteal accepts applications from direct candidates only. We do not work with third-party recruiters or staffing agencies.

Required Country Location

Costa Rica, Peru, Argentina, Brazil, Columbia, South Africa, Mexico, or Panama. This is full time work at 40 hours per week Overview: Our client seeks a motivated

Senior DevOps Engineer, Data & AI to join their team in building a groundbreaking, modular platform from the ground up. This platform digitizes and contextualizes multi-modal sensor data from both digital and physical environments into specialized time-series, graph, and vector databases—powering real-time analytics, compliance, and AI-driven context mapping. This role is adecuado for a DevOps leader with strong expertise in data engineering, distributed systems, and applied AI, who thrives on automation, scalability, and production-grade deployments across hybrid and cloud environments.

Key Responsibilities: Platform Automation & Infrastructure

Architect, automate, and manage infrastructure for data ingestion, contextualization, and visualization modules

(Data, Access, & Agents). Build CI/CD pipelines for sensor collection agents across heterogeneous systems (Windows, Linux, macOS, mobile, IoT). Implement and automate real-time ingestion pipelines using

Apache Kafka, Apache NiFi, Redis Streams, or AWS Kinesis . Database & Data Layer Engineering

Deploy, scale, and optimize multi-modal databases:

Time-series:

MongoDB, InfluxDB, TimescaleDB, or AWS Timestream Graph:

Neo4j (Cypher, APOC, graph schema design) Vector:

Qdrant, FAISS, Pinecone, or Weaviate

Automate deployment and monitoring of a

Database Access Layer (DBAL)





to unify queries across multiple database engines. Experiment with or extend

Model Context Protocol (MCP)

or similar standards for cross-database and multi-agent interoperability. Data Streaming & Integration

Engineer low-latency pipelines for event streams (syslog, telemetry, keystrokes, IoT feeds, cloud service logs). Collaborate with frontend engineers to integrate visual mapping UIs with scalable back-end pipelines. Optimization, Reliability & Scalability

Optimize system and database performance using down-sampling, partitioning, and caching techniques . Design solutions for horizontal scaling and containerized deployment

(Docker, Kubernetes, OpenShift). Apply infrastructure-as-code practices to achieve resilience, reproducibility, and rapid iteration under real-world constraints. Collaboration & Leadership

Partner with compliance, security, and business stakeholders to ensure systems meet regulatory and operational requirements. Conduct architecture reviews, lead DevOps best practices, and mentor junior engineers on automation, scalability, and observability.

Required Skills & Experience:

Programming

Strong proficiency in Python and Node.js (C++ a plus). Streaming:

Proven hands-on experience with

Kafka, NiFi, Redis Streams,



or AWS Kinesis . Databases:

Time-series: MongoDB, InfluxDB, TimescaleDB, or AWS Timestream Graph: Neo4j (Cypher, APOC) Vector: Qdrant, FAISS, Pinecone, or Weaviate

AI & Agents:

Experience with—or strong interest in— Agentic AI frameworks, multi-agent orchestration, and context-aware data processing . Data Interchange:

Familiarity with

MCP-like protocols or standardized APIs for multi-database access. Cloud & Infrastructure:

Hands-on with

AWS, Azure, or GCP , plus containerization and orchestration ( Docker, Kubernetes, OpenShift ). DevOps Expertise:

Deep understanding of

CI/CD pipelines, IaC (Terraform/Ansible), monitoring/observability, distributed systems, and microservices security . Problem Solving:

Strong debugging skills, automation mindset, and ability to balance speed, scalability, and compliance in production systems.

Preferred Skills

Machine Learning/NLP integration into multi-modal pipelines. CI/CD automation and DevOps practices. Knowledge of enterprise integration patterns, event-driven systems, and zero-trust security models . Experience with compliance frameworks (NERC CIP, FedRAMP, GDPR, SOX).

Qualifications

Bachelor's degree in Computer Science, Engineering, or related field (or equivalent hands-on experience). 5+ years professional software development with data-intensive or AI-driven systems. Proven experience designing, deploying, and scaling modular platforms in production.

Arganteal accepts applications from direct candidates only. We do not work with third-party recruiters or staffing agencies.

📌 Senior Devops Engineer (Monterrey)
🏢 Arganteal
📍 Monterrey