A dedicated startup is being formed at the company to industrialize and scale a secure, AI-enabled, multi-source decision-support software offering. The platform is a multi-sensor fusion and agentic AI solution that connects to diverse data sources such as geospatial layers, imagery, video, and other operational signals. This role will support the delivery of a scalable product and contribute to establishing the processes, standards, and collaboration practices required for sustainable growth.
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You will own the technical architecture of a fast-scaling software platform that combines geospatial workflows with AI capabilities, including LLM-enabled and agentic components. Your responsibilities will include setting architectural direction, ensuring engineering consistency and quality, and helping teams deliver secure, scalable, and maintainable systems in a startup-paced environment.
Job Responsibilities:
- Define target architecture and reference patterns across platform, data, GIS services, LLM/agentic layer, and user applications.
- Translate product and operational requirements into end-to-end technical designs (APIs, services, data flows, model interfaces).
- Lead architectural reviews and decision-making, including trade-offs, architectural decision records (ADRs), standards, and technical debt roadmap.
- Design integration approaches for data sources, sensors, SDKs/APIs, and third-party systems.
- Establish non-functional requirements and quality gates: performance, latency, reliability, observability, security, and cost.
- Guide engineering on scalable data and GIS patterns, as well as LLM/agentic patterns.
- Partner with DevOps/MLOps to define deployment architectures, CI/CD, environment strategy, and release readiness.
- Support incident reviews and root-cause analysis while driving structural fixes and resilience improvements.
- Contribute to recruiting efforts, including role definition input, technical interviews, onboarding plans, and mentoring.
Qualifications and Experience:
- Typically 5+ years in software engineering, with 4+ years in architecture.
- Track record of delivering platform architectures that scaled in users, data volume, and features.
- Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
- Experience with tools such as GitHub/GitLab, CI/CD pipelines, IaC (Terraform or equivalent), Jira/Linear, Confluence/Notion, cloud services (AWS/Azure/GCP), and container platforms (Kubernetes).
Success Measures:
- Architecture adoption and consistency across teams (reduced rework, fewer integration surprises).
- Platform reliability and performance improvements (SLO/SLA attainment, reduced incident recurrence).
- Delivery velocity with controlled technical debt (predictable releases, clear trade-offs).
- Security and compliance readiness (design-time controls, auditability, least-privilege patterns).
