Internal Automation Software Engineer
Enterprise AI platform for financial institutions, providing agentic research, analysis, workflow automation, and client-ready deliverables.
Funding history
About Rogo
Rogo builds bespoke, enterprise-grade AI systems for financial workflows, including research, analysis, modeling, reporting, and deal work. Its platform emphasizes financial-domain models, integrated firm and market data, auditability, governance, and security.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will turn operational problems into production services, integrate internal systems of record, and build reliable AI-agent workflows. You will automate customer lifecycle processes, protect company and customer data, instrument outcomes, and retire automations that do not deliver measurable value.
Requirements
- 2+ years of professional software engineering experience operating production backend systems
- Strong TypeScript for backend services and APIs
- Experience deploying production services on GCP or an equivalent cloud stack
- Strong relational database and SQL knowledge
- Experience building production LLM systems, including prompting, tool calling, retrieval, agent workflows, evaluation, and guardrails
- Experience integrating third-party APIs, REST, webhooks, authentication, rate limits, pagination, and data reconciliation
- Knowledge of queuing, background jobs, scheduling, retries, idempotency, and observability
- Experience translating non-technical workflows into requirements
- Interest in corporate finance and capital markets
Responsibilities
- Build production services for internal operational workflows
- Integrate systems of record into a reliable internal data layer
- Design AI-agent workflows for research, enrichment, drafting, summarization, and data entry
- Build evaluations, guardrails, and monitoring for production agents
- Automate provisioning, onboarding, and account setup
- Build secure, compliant company and customer-data integrations
- Measure automation impact using hours returned, error rates, and cycle time
- Retire automations that do not deliver value