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Gramian Consulting Group

via Workable

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Founding Engineer for Industrial AI Platform (Data Infrastructure)

Anywhere
Full-time
Posted 2/25/2026
Direct Apply
Key Skills:
Data Pipeline Architecture
Edge Ingestion
ETL
Streaming Infrastructure

Compensation

Salary Range

$Not specified

Responsibilities

Design and build end-to-end data layers and scalable data pipelines with infrastructure and security ownership.

Requirements

Strong engineering background with experience in production-scale data pipelines, industrial data sources, and DevOps/security engineering.

Full Description

About Us Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. Role overview We are partnering with an innovative deep-tech company currently emerging from stealth and building an industrial data platform focused on real-time sensor connectivity, scalable data pipelines, and AI-driven analytics for manufacturing, energy, and critical infrastructure environments. They are hiring their first Backend & Data Infrastructure Engineer — a foundational, high-ownership role responsible for designing and building the company’s data layer end-to-end, from edge ingestion through transformation, fusion, and delivery into analytics and AI systems. This is a foundational engineering role with founder-level responsibility, working alongside senior engineers and leaders from globally recognized industrial, autonomous systems, and research organizations. Model: Contracting, Remote Duration: 6+ months Location: strong preference for Texas, US, alternatively LATAM Key Responsibilities Design and implement end-to-end data pipeline architecture spanning edge devices, ingestion, processing, storage, and delivery into analytics/AI workloads Build scalable ETL and data processing frameworks with orchestration, schema management, versioning, and automated data quality controls Develop real-time and streaming infrastructure supporting event-driven systems, edge-to-cloud synchronization, buffering strategies, and strict latency requirements Own DevOps and infrastructure engineering, including CI/CD pipelines, infrastructure-as-code, container orchestration, and production deployment workflows Implement and maintain security architecture across the stack, including access controls, secrets management, network segmentation, vulnerability scanning, and compliance practices Establish strong observability, monitoring, and operational tooling for distributed systems running across cloud, edge, and enterprise integrations Support onboarding of complex multimodal data sources including telemetry, time-series, video, audio, LiDAR, and geospatial datasets Strong engineering background from leading technology companies or large-scale production environments (for example globally recognized tech firms, large enterprise platforms, or similarly demanding engineering organizations) Proven experience building production-scale data pipelines or ETL systems handling large-scale streaming and batch datasets Hands-on work with real-world industrial or multimodal data sources, such as sensor telemetry, time-series, geospatial, video, audio, or point-cloud data Strong experience owning infrastructure and DevOps in production environments, including CI/CD, containers, orchestration, and operational reliability Practical experience implementing security engineering practices such as threat modeling, secrets management, system hardening, and secure architecture design Experience as an early engineer or key technical owner building systems from scratch through production deployment

This job posting was last updated on 2/26/2026

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