About Channel Fusion
Founded more than 20 years ago, Channel Fusion provides brands and their channel partners with an ecosystem of channel marketing technologies, solutions and services. By coupling innovative technologies, industry expertise and a relentless customer-focused support team, we provide a unique combination of platforms, products and people.
Our purpose is simple: inspire our clients to achieve their desired outcomes by transforming channel marketing into impactful business results. We do this by ensuring an understanding of your desired outcomes first and then deploying tailored solutions using a disciplined process to achieve those outcomes.
Once a program is operational, our support team of Fusers becomes an extension of your brand to ensure your channel partners have an optimal customer experience while maximizing their marketing investment in your brand. Our account leadership teams stay involved every step of the way to ensure programs continue to exceed expectations and drive your desired outcomes.
About the role
Channel Fusion is building an AI Factory focused on accelerating software delivery, automating business operations, modernizing legacy platforms, and creating intelligent customer-facing solutions through Agentic AI.
This is a hands-on implementation role. Rather than owning a single client program, this person builds and ships AI agents and automation across Channel Fusion's teams and client solutions — wherever the Lead AI Platform Engineer and Field Product Managers identify agent opportunities. You'll work day-to-day alongside Suraj (AI Engineer) and under the direction of the Lead/Senior AI Platform Engineer, picking up implementation work as it's scoped and prioritized across programs.
This role does not set agent architecture standards or product requirements — those come from the Lead AI Platform Engineer (how) and the relevant FPM (what). This role is the execution capacity that turns those specs into working, production-quality agents.
What You Own
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Implementation. Build, test, and ship individual agents and automations to the architecture and standards set by the Lead AI Platform Engineer.
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Cross-Team Delivery. Pick up agent-building work across whichever Channel Fusion team or client solution has current priority, rather than owning one fixed program.
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Peer Collaboration. Work directly with Suraj and other AI engineers to share patterns, reusable components, and avoid duplicated effort across parallel implementations.
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Quality & Testing. Write and maintain evals/tests for the agents you build so regressions are caught before they reach production.
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Feedback Loop. Flag gaps, edge cases, or ambiguity in a spec back to the Lead/FPM rather than guessing silently.
What You Do NOT Own
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Agent architecture, orchestration standards, and platform-wide design decisions. This is owned by the Lead AI Platform Engineer.
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What a given agent needs to accomplish. This is owned by the relevant Field Product Manager.
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Requirements for agents touching a specific engineering workstream. Owned by the relevant Lead Developer for engineering-embedded agents (e.g., CI/CD or code-review agents).
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The ADLC framework and AI governance policy. This is owned by the Technology Director and this role builds within it.
Key Responsibilities
Agent Implementation
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Build agents against specs handed down from the Lead AI Platform Engineer and FPMs — covering planning, tool use, and task execution.
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Implement retrieval-augmented generation (RAG) components against enterprise knowledge sources.
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Wire agents into internal and external business systems via secure APIs and data access patterns already established by the platform team.
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Reuse and extend existing agent frameworks/libraries rather than building one-offs.
Cross-Program Delivery
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Move across Channel Fusion client programs and internal workflows as implementation priorities shift.
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Ramp quickly on a new program's data model and requirements with support from the assigned FPM.
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Keep implementation consistent with patterns used elsewhere in the AI Factory, flagging when a program's needs don't fit existing patterns.
Quality, Testing & Operations
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Write evaluation/test cases for agents before they ship.
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Monitor and troubleshoot agents in production; escalate architecture-level issues to the Lead.
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Track and report token/cost usage for agents you own.
Qualifications
Require
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2+ years of professional software engineering experience.
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Hands-on experience building or shipping at least one production AI-enabled application or agent.
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Strong Python development skills.
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Experience building and consuming REST APIs.
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Working SQL skills and comfort with data integration across systems.
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Experience with Git and collaborative development workflows.
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Comfort moving across multiple codebases/programs rather than owning a single one.
Preferred
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AI & Agentic Frameworks: LangGraph, CrewAI, Microsoft Semantic Kernls, AutoGen, OpenAI Agents Framework, Anthropic APIs, or Azure OpenAI Services.
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Domain: Exposure to channel marketing, co-op advertising, dealer/distributor platforms, or document/PDF-heavy workflows.
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Cloud & Tooling: Azure (Functions, AI Services, AKS), Docker, CI/CD pipelines, GitHub Copilot or other AI-assisted development tools.
