Channel Fusion powers channel marketing programs for enterprise brands—managing billions of dollars in marketing investments through dealer and distributor networks. Our platform handles high-volume transaction processing, complex business rules, and financial accountability across programs ranging from co-op advertising to dealer incentives to rewards and rebates.
We're executing a dual transformation. Transformation A: stabilize and strengthen the core platform that drives today's revenue. Transformation B: architect the next generation of our platform for scale, observability, and modern integration patterns. We need a senior engineer who can work across both—bringing immediate value to stabilization while laying the architectural foundation for where we're headed.
This role reports to the Director of TSL (Tech Solutions Lab) and works as a peer to our Principal Engineer who leads database architecture. Where the Principal brings deep SQL Server and database expertise, you'll bring modern event-driven architecture, stream processing, and data pipeline design. Together, you'll define the technical direction for a platform processing hundreds of millions of transactions annually.
What You'll OwnArchitecture Evolution
- Design and lead implementation of event-driven architecture patterns to replace batch-oriented processing with real-time, observable data flows
- Architect stream processing and data pipeline infrastructure—queues with proper visibility, retry semantics, ordering guarantees, and dead letter handling
- Partner with the Principal Engineer (Database) to design integration patterns between evolved architecture and existing database layer
- Establish architectural patterns that enable incremental migration—strangler fig, anti-corruption layers, event sourcing where appropriate
Testing Rigor & Quality Engineering
- Bring modern behavior-driven development (BDD) practices to the organization—establishing specification-first development as the norm
- Build test infrastructure: golden dataset validation for financial calculations, contract testing for integrations, property-based testing for edge cases
- Establish regression testing practices that give confidence to modify legacy code—the platform has significant untested surface area that creates risk
- Create observability infrastructure: distributed tracing, meaningful alerting, and dashboards that surface problems before clients do
Agentic Development & AI-Assisted Engineering
- Lead adoption of agentic development practices—leveraging AI coding assistants, automated test generation, and specification-driven development
- Explore and implement MCP (Model Context Protocol) servers for client integrations—enabling intelligent connectivity between Channel Fusion and client systems
- Stay current with rapidly evolving AI tooling and bring practical applications to the team—you should be genuinely excited about how AI is changing software development
- Help the team level up: pairing sessions, architectural reviews, knowledge transfer that raises everyone's capabilities
Dual Transformation Execution
- Transformation A (Core): Specification extraction from legacy systems, dependency mapping, identifying and remediating architectural risks in the current platform
- Transformation B (Future): Design target-state architecture, build proof-of-concept implementations, create migration paths that don't require big-bang rewrites
- Navigate the tension between these priorities—knowing when to stabilize vs. when to evolve, and how to make progress on both simultaneously
What You BringRequired Experience
- 8+ years of software engineering with progression to staff/principal level—demonstrated technical leadership and architectural ownership
- Event-driven architecture expertise —you've designed and built systems using message queues, event streaming (Kafka, Azure Event Hubs, etc.), and asynchronous processing patterns
- Data pipeline and stream processing —experience with real-time data flows, ETL/ELT modernization, and high-volume transaction processing
- Fintech or marketing technology background —you've built systems where accuracy matters: financial calculations, compliance tracking, or investment accountability
- Legacy system modernization —you've successfully evolved production systems incrementally, not just greenfield builds
- Both startup and enterprise experience —you know how to move fast AND how to operate systems that can't go down
Technical Depth
- .NET ecosystem proficiency —our platform runs on .NET; you should be comfortable in this stack even if it's not your only expertise
- SQL competency —you won't own database architecture, but you need to read and understand complex queries and collaborate on data layer design
- Testing and quality engineering —deep experience with BDD frameworks (SpecFlow, Cucumber, etc.), test automation, and building quality into the development process
- Observability and operations —you've built systems you also had to support; you understand what makes software operable at scale
- Agentic development fluency —active experience with AI coding assistants, interest in MCP and emerging integration patterns, enthusiasm for how AI is reshaping engineering practice
Working Style
- Hands-on contributor —this is not an architecture-on-paper role; you'll write code, review code, and build the things you design
- Collaborative technical leadership —you'll work closely with the Principal Engineer (Database), engineering leads, and the Director of Product; no solo heroes
- Comfortable with ambiguity —legacy systems mean incomplete documentation, tribal knowledge, and surprises; you navigate this without getting stuck
- Continuous learner —AI tooling is evolving weekly; you stay current and bring practical applications back to the team
First 90 Days
- Deep dive on current architecture: Understand the platform's data flows, processing patterns, integration points, and where the architectural pain lives
- Build the partnership with your peer: Establish working rhythm with the Principal Engineer (Database)—define how you'll collaborate on cross-cutting architectural decisions
- Quick win on testing: Identify one critical path and establish BDD coverage as a proof point for the practices you'll bring
- Architectural assessment: Document current-state patterns (batch processing, parallel EXE instances, queue-less orchestration) and propose target-state direction
- Introduce agentic practices: Start demonstrating how AI-assisted development accelerates the work—specification extraction, test generation, code understanding
The Environment
The platform today: .NET backend, SQL Server with complex stored procedures, batch processing patterns, SSIS-based ETL, and client integrations. High-volume transaction processing (billions of records) with tight SLAs. The architecture works, but there is opportunity to evolve with the industry.
The challenge: Batch-oriented patterns that should be event-driven. Parallel processing without proper queue semantics. Limited observability. Minimal automated testing. A codebase shaped by years of client customization without aggressive refactoring.
The opportunity: Genuine greenfield architecture work within an established, revenue-generating platform. A peer in database architecture who complements your skills. Leadership committed to investing in the transformation. And a problem domain—marketing investment accountability—that's actually interesting.
Benefits:
- 401(k)
- AD&D insurance
- Dental insurance
- Disability insurance
- Flexible spending account
- Health insurance
- Life insurance
- Vision insurance
- Work from home
Work Location: Remote
