- Company Name
- MISTI AI
- Job Title
- Cloud & Edge AI Systems Engineer
- Job Description
-
**Job title**
Cloud & Edge AI Systems Engineer
**Role Summary**
Design, build, and maintain the distributed infrastructure that delivers real‑time computer vision models from AWS to NVIDIA Jetson edge devices. Own end‑to‑end reliability, scalability, security, and performance of the Vision Agentic Platform, ensuring safety‑critical insights are produced under harsh industrial conditions.
**Expectations**
- 4+ years of systems or infrastructure engineering, preferably in high‑scale cloud environments.
- Deep expertise with AWS services (EKS/ECS, networking, IAM, KMS, autoscaling, SageMaker).
- Experience deploying AI/ML models to edge hardware, ideally Jetson.
- Proficient in IaC (Terraform or CloudFormation) and CI/CD automation.
- Strong Linux, Python, and/or Go/Node background.
**Key Responsibilities**
1. **Cloud Architecture** – Design and scale AWS backbone (EKS/ECS, networking, autoscaling, serverless) for AI agents.
2. **Data Pipelines** – Build real‑time ingestion of video/event streams from mining sites; manage model registries in SageMaker.
3. **Edge Deployment** – Package CV models with ONNX/TensorRT, implement OTA updates, and maintain telemetry/logging for heterogeneous Jetson fleets.
4. **CI/CD & Observability** – Automate pipelines (GitHub Actions), implement metrics, logs, traces, alerts, and incident response across cloud and edge.
5. **Model Ops** – Deploy and monitor models, detect drift, latency, and failure; coordinate with ML team on deployment strategy.
6. **Security & Compliance** – Enforce encryption, IAM least‑privilege, KMS, Security Hub, CloudTrail, GuardDuty; manage GDPR/PII data protection and edge‑to‑cloud integrity.
7. **Documentation & Communication** – Produce architecture, deployment, and security documentation; communicate decisions clearly.
**Required Skills**
- AWS (EKS/ECS, networking, IAM, KMS, autoscaling, serverless).
- Distributed systems or large‑scale backend infrastructure.
- Edge AI deployment on Jetson (ONNX, TensorRT preferred).
- CI/CD automation (GitHub Actions or equivalent).
- IaC (Terraform or CloudFormation).
- Python/Go/Node; strong Linux aptitude.
**Nice to Have**
- Experience with AWS IoT Greengrass or similar.
- GPU‑aware systems engineering.
- Safety‑critical or robotics/embedded real‑time experience.
- Prior work with regulated or PII environments (GDPR).
**Required Education & Certifications**
- Bachelor’s degree in Computer Science, Electrical Engineering, or related field (or equivalent experience).
- AWS certifications (e.g., Solutions Architect, DevOps Engineer) preferred but not mandatory.