Jobs at AgileEngine

Build and own the enterprise AI context and knowledge layer, including knowledge graphs, semantic retrieval, RAG, connectors, APIs, and agent integrations. Design and evaluate AI agents, skills, workflows, and prompts; improve retrieval quality, reliability, security, and cost efficiency. Administer Slack, Google Workspace, Glean, and AI assistants while implementing access controls, monitoring, incident response, documentation, and governance. Lead cross-functional stakeholders and create reusable tooling that enables teams to manage context and scope AI use cases independently.

Owns BI product management for Quote-to-Cash and Order-to-Cash processes. Partners with finance, sales, legal, product, and engineering teams to identify operational issues and translate them into BI, AI, and machine learning opportunities. Develops PRDs, roadmaps, business requirements, dashboards, and data products covering quoting, contracts, billing, revenue recognition, and financial systems.

Architect low-latency .NET APIs and backend services while building Angular interfaces for a financial services platform. Develop microservices and message-driven systems, maintain strong automated test coverage, conduct code reviews, manage CI/CD and production observability, and define API contracts using OpenAPI/Swagger. Collaborate in Agile/Scrum environments to deliver analytical investment tools.

Own the strategic vision and backlog for internal security tools and developer portals. Prioritize risk-reduction initiatives, drive adoption of security policies and tooling, reduce developer friction, and connect executive security mandates with Agile delivery teams. The role requires autonomy in product strategy, experience with vulnerability management, AppSec, cloud security, architecture, or development enablement, and strong cross-functional leadership.

Design and maintain scalable ELT/ETL pipelines, data models, and automation systems supporting cloud cost visibility, attribution, and performance insights. Use Python, SQL, dbt, Airflow, AWS services, and Snowflake to optimize data workflows for reliability, performance, and cost. Ensure data quality, validation, and auditability while partnering with Engineering and Finance stakeholders on cloud cost optimization and usage-based decisions.