Founding Engineer for Industrial AI Platform (Data Infrastructure)

Job 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

Requirements

• 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