Company Description ARC Ventures builds AI-powered systems for leading financial and commercial real estate organizations, including investment firms, insurers, and corporate development teams. The company designs custom AI workflows that align with each client’s existing processes, standards, and technology stack, with a focus on professional-grade outputs. ARC Ventures is model-agnostic and integrates multiple frontier AI models in a single pipeline to ensure each step is handled by the best-suited technology. Data privacy and security are core principles, with all systems operating inside the client’s established controls and policies. The firm’s solutions support deal and investment work, research and intelligence, client deliverables, operations, compliance, and web and application development.
Role Description The Systems Engineer is a full-time, on-site role based in San Diego, CA, responsible for designing, implementing, and maintaining AI-driven systems and infrastructure that power client workflows. In this position, the Systems Engineer collaborates with product, engineering, and client delivery teams to build secure, scalable pipelines that connect multiple AI models and data sources. Day-to-day work includes configuring cloud and on-prem environments, integrating APIs, optimizing system performance, and ensuring uptime, reliability, and compliance with client security policies. The role also involves troubleshooting production issues, monitoring system health, documenting architecture and processes, and supporting deployment of new features and workflows. The Systems Engineer contributes to continuous improvement by evaluating new tools, refining automation, and helping standardize best practices across engagements.
Qualifications
- Strong systems engineering skills, including experience with system design, integration, and performance optimization.
- Proficiency with cloud platforms (e.g., AWS, GCP, Azure) and infrastructure-as-code tools (e.g., Terraform, CloudFormation, Ansible).
- Experience implementing secure, compliant systems within enterprise environments, including identity and access management and data protection controls.
- Working knowledge of API integration, microservices architectures, and containerization (e.g., Docker, Kubernetes).
- Practical experience with monitoring and logging tools (e.g., Prometheus, Grafana, Datadog, ELK stack) to ensure reliability and observability.
- Proficiency in at least one programming or scripting language commonly used for systems work (e.g., Python, Go, Bash).
- Familiarity with AI/ML workflows or data pipelines is beneficial, especially integrating third-party AI models into production systems.
- Strong problem-solving skills, attention to detail, and the ability to work collaboratively with cross-functional technical and non-technical stakeholders.
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
