Senior Developer

**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 Developer, Data & AI** to join their team in developing a groundbreaking, modular platform built from the ground up. Our client 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 ideal for a creative problem-solver who thrives at the intersection of **data engineering, distributed systems, and applied AI**.
**Key Responsibilities**
**Platform Design & Development**
- Architect, develop, and deploy **core modules** (Data, Access, & Agent's) for end-to-end data ingestion, contextualization, and visualization.
- Design and code **sensor collection agents** across heterogeneous systems (Windows, Linux, macOS, mobile, IoT).
- Implement **real-time ingestion pipelines** using technologies like **Apache Kafka, Apache NiFi, Redis Streams, or AWS Kinesis**.
- Persist and query multi-modal data across **time-series (MongoDB, InfluxDB, TimescaleDB), graph (Neo4j), and vector databases (Qdrant, FAISS, Pinecone, or Weaviate)**.
**API & Data Access Layer**
- Build secure, scalable **RESTful and GraphQL APIs** for exposing platform data models, sensor configuration, and reporting.
- Implement a **unified Database Access Layer (DBAL)** to abstract query logic across multiple databases.
- Experiment with or extend **Model Context Protocol (MCP)** or a similar standardized data interchange for multi-DB, multi-agent interoperability.
**System Integration & Data Streaming**
- Develop **low-latency data pipelines** for transporting and transforming event streams (syslog, telemetry, keystrokes, IoT feeds, cloud service logs).
- Collaborate with frontend engineers to connect **Access (visual mapping UI)** with back-end pipelines.
**Optimization & Scalability**
- Optimize **database query performance** using down-sampling, partitioning, and caching techniques.
- Design solutions for **horizontal scaling and containerized deployment (Docker, Kubernetes, OpenShift)**.
**Collaboration & Mentoring**
- Work directly with **compliance officers, security analysts, and business process owners** to refine data models for regulatory and operational needs.
- Conduct code reviews, mentor junior developers, and promote best practices across the team.
**Required Skills & Experience**
- ** Programming**: Strong proficiency in **Node.js and Python** (C++ a plus).
- ** Streaming**: Hands-on experience with **Kafka, NiFi, Redis Streams, or AWS Kinesis**.
- ** Databases**:
- Time-series: MongoDB, InfluxDB, TimescaleDB, or AWS Timestream
- Graph: Neo4j (Cypher, APOC, graph schema design)
- 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 interest in defining standardized APIs for cross-database access.
- ** Cloud/Infra**: AWS, Azure, or GCP with containerization (Docker, Kubernetes).
- ** Software Engineering**: Strong grasp of **algorithms, distributed systems, microservice design, and API security**.
- ** Problem Solving**: Strong debugging skills, creative mindset, and ability to balance speed with scalability.
**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.
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