Senior DevOps Engineer

DeepNeuronic is a fast-growing AI startup building real-time computer vision systems for transportation, retail, industrial automation, and smart city applications. Our platform turns live video into actionable analytics at scale, across edge and cloud deployments, helping organizations improve safety, efficiency, and operations. As we expand deployments across multiple countries and environments, we are strengthening our platform and delivery capabilities to enable fast, repeatable rollouts.

DeepNeuronic delivers AI systems that operate in demanding real-world conditions, different camera networks, infrastructures, and operational constraints. To support scalable growth, we invest in strong deployment foundations: standardized architectures, reliable release processes, and operational excellence across cloud and on-prem deployments.

This role sits at the center of that mission. You’ll help ensure that deploying and operating DeepNeuronic solutions is fast, predictable, observable, and resilient, across multiple products and customer contexts.

As a Senior DevOps Engineer, you’ll own key parts of DeepNeuronic’s deployment and reliability stack: packaging, environment readiness, configuration, upgrades, health checks, monitoring, alerting, and rollback strategies. You’ll work closely with Product, Support/Sales, MLOps, and Engineering teams to improve operational maturity and create a consistent deployment experience across customers.

• Design and maintain standard deployment architectures for cloud and on-prem environments (edge + central services).

• Build and evolve deployment automation for install, upgrade, validation, and rollback (scripts, templates, CI/CD hooks).

• Define and document recommended configurations for typical customer scenarios (network, storage, GPU, streaming inputs).

• Implement observability (logs, metrics, alerts, dashboards) to detect issues early and reduce downtime.

• Create and maintain deployment runbooks, checklists, and troubleshooting guides to support reliable operations.

• Improve release engineering: versioning, reproducibility, environment parity, and safe rollout practices.

• Standardize system requirements (GPU drivers, Docker versions, permissions, ports) and reduce configuration drift.

• Collaborate with engineering teams to ensure services are deployable, testable, and operable in production.

• Support critical deployments and incidents when needed, focusing on root-cause fixes and prevention.

• 5+ years experience in DevOps / Platform Engineering / Reliability Engineering with production deployments.

• Strong Linux + networking fundamentals (VPN/VLAN/firewall, ports, bandwidth, RTSP basics).

• Solid experience with Docker (Kubernetes is a plus).

• Experience building reliable systems with monitoring/alerting, incident response practices, and root-cause analysis.

• Ability to write clean automation (Bash/Python) and produce clear documentation/runbooks.

• Strong ownership and ability to drive cross-team standardization.

• Experience with GPU workloads (NVIDIA drivers/CUDA), real-time video pipelines, or edge deployments.

• Familiarity with CI/CD (GitHub Actions/GitLab CI), Infrastructure-as-Code (Terraform/Ansible), and secrets management.

• Experience with cloud providers (GCP/AWS/Azure) and hybrid architectures.

• Understanding of MLOps practices: model packaging, versioning, and reproducible inference environments.

• Familiarity with computer vision pipelines in production (e.g., RTSP ingest, decoding, pre/post-processing, detection/tracking stages, latency/throughput constraints).

• A high-impact role improving how real-world AI systems are deployed and operated at scale.

• Direct access to leadership and the teams building the platform end-to-end.

• A flat and agile environment where you can drive meaningful operational improvements quickly.

• Flexible hybrid work model and autonomy with clear outcomes.

• Competitive compensation aligned with experience and performance, with rapid adjustments for strong impact.

• Growth path into Platform Lead / Head of Deployment & Reliability as the company scales.

• 1st take-home general skills assignment;

• 2nd take-home specific skills assignment (to be delivered within 1 week);

• 1h general & specific skills and working principles interview;

• 1h mindset and cultural fit interview.

Note: Please note that this position does not offer relocation assistance. Candidates must possess a valid EU visa and be based in Portugal.

Our job titles may span more than one career level. Actual pay is determined by skills, qualifications, experience, location, market demand, and other factors. Compensation details listed in this posting reflect the base salary and any potential variable, bonus or sales incentives, and the Company’s estimation of the value of private company stock options, if applicable. The pay range is subject to change, future value of company stock options is not guaranteed, and compensation may be modified in the future.