AI Developer

Channel Fusion

India

On-site

INR 1,200,000 - 2,000,000

Full time

5 days ago
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Job summary

Channel Fusion is seeking a hands-on AI Platform Engineer to build and ship AI agents and automations across programs. You’ll implement agent capabilities, RAG components, and secure API integrations following established patterns and collaboration with the AI team.

The role emphasizes cross-team delivery, rapid iteration, and quality testing to prevent production issues, contributing to reusable components and tooling within Channel Fusion's AI Factory.

Qualifications

  • 2+ years of professional software engineering experience.
  • Hands-on experience building or shipping at least one production AI-enabled application or agent.
  • Strong Python development skills.
  • Experience building and consuming REST APIs.
  • Working SQL skills and comfort with data integration across systems.
  • Experience with Git and collaborative development workflows.
  • Comfort moving across multiple codebases/programs rather than owning a single one.

Responsibilities

  • Build agents against specs handed down from the Lead AI Platform Engineer and FPMs.
  • Implement retrieval-augmented generation components against enterprise knowledge sources.
  • Wire agents into internal and external business systems via secure APIs.
  • Reuse and extend existing agent frameworks/libraries.

Skills

2+ years software engineering
Python
REST APIs
SQL
Git
CI/CD
Azure Functions
Docker
GitHub Copilot

Tools

Azure Functions
Docker
CI/CD pipelines
GitHub Copilot

Job description

Job Description:

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 Fusions teams and client solutions — wherever the Lead AI Platform Engineer and Field Product Managers identify agent opportunities. Youll work day-to-day alongside Suraj (AI Engineer) and under the direction of the Lead/Senior AI Platform Engineer, picking up implementation work as its 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
  • Implementation. Build, test, and ship individual agents and automations to the architecture and standards set by the Lead AI Platform Engineer.
  • 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.
  • Peer Collaboration. Work directly with Suraj and other AI engineers to share patterns, reusable components, and avoid duplicated effort across parallel implementations.
  • Quality & Testing. Write and maintain evals/tests for the agents you build so regressions are caught before they reach production.
  • 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
  • Agent architecture, orchestration standards, and platform-wide design decisions. This is owned by the Lead AI Platform Engineer.
  • What a given agent needs to accomplish. This is owned by the relevant Field Product Manager.
  • 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).
  • The ADLC framework and AI governance policy. This is owned by the Technology Director and this role builds within it.
Key Responsibilities
Agent Implementation
  • Build agents against specs handed down from the Lead AI Platform Engineer and FPMs — covering planning, tool use, and task execution.
  • Implement retrieval-augmented generation (RAG) components against enterprise knowledge sources.
  • Wire agents into internal and external business systems via secure APIs and data access patterns already established by the platform team.
  • Reuse and extend existing agent frameworks/libraries rather than building one-offs.
Cross-Program Delivery
  • Move across Channel Fusion client programs and internal workflows as implementation priorities shift.
  • Ramp quickly on a new programs data model and requirements with support from the assigned FPM.
  • Keep implementation consistent with patterns used elsewhere in the AI Factory, flagging when a programs needs dont fit existing patterns.
Quality, Testing & Operations
  • Write evaluation/test cases for agents before they ship.
  • Monitor and troubleshoot agents in production; elevate architecture-level issues to the Lead.
  • Track and report token/cost usage for agents you own.
Qualifications
Require
  • 2+ years of professional software engineering experience.
  • Hands-on experience building or shipping at least one production AI-enabled application or agent.
  • Strong Python development skills.
  • Experience building and consuming REST APIs.
  • Working SQL skills and comfort with data integration across systems.
  • Experience with Git and collaborative development workflows.
  • Comfort moving across multiple codebases/programs rather than owning a single one.
Preferred
  • AI & Agentic Frameworks: LangGraph, CrewAI, Microsoft Semantic Kernls, AutoGen, OpenAI Agents Framework, Anthropic APIs, or Azure OpenAI Services.
  • Domain: Exposure to channel marketing, co-op advertising, dealer/distributor platforms, or document/PDF-heavy workflows.
  • Cloud & Tooling: Azure (Functions, AI Services, AKS), Docker, CI/CD pipelines, GitHub Copilot or other AI-assisted development tools.
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