Channel Fusion is looking For Lead AI Platform Engineer

Channel Fusion; Chandigarh; Hybrid; INR 600,000 - 1,200,000; Full time

Job summary

Channel Fusion is building an AI Factory to accelerate software delivery and automate operations, delivering intelligent agents across engineering workflows. You will lead a small team to architect and deliver autonomous agents, translating product features into scalable architectures and reusable frameworks.

You will design multi-agent solutions, oversee the implementation, and ensure reliability, security, and cost efficiency of deployed agents within CI/CD pipelines and enterprise

Qualifications

• 5+ years of professional software engineering experience.
• 2+ years building production AI-enabled applications.
• Experience designing cloud-native distributed systems.
• Prior experience leading a small team or serving as a technical lead on a delivery team.
• Experience building and consuming REST APIs.
• Expert-level Python development.
• Strong understanding of software architecture and design patterns.
• Experience with modern cloud platforms (Azure strongly preferred).
• Experience with containerization technologies such as Docker.
• Experience with CI/CD pipelines and DevOps practices.
• Strong SQL and data integration capabilities.
• Experience with Git and collaborative software development workflows.

Responsibilities

• Translate FPM-defined product features into agent architecture, orchestration design and delivery plans.
• Design multi-agent systems, tool-calling patterns, memory/orchestration approaches, and reusable agent frameworks.
• Lead and mentor the small team of engineers implementing agents; review designs and set standards.
• Coordinate with Engineering Leads to ensure agents meet domain requirements; align with standards.
• Build monitoring, logging, evaluation frameworks; own token/cost efficiency and reliability of shipped agents.
• Build monitoring, logging, evaluation, and performance frameworks for AI systems.
• Optimize model utilization, token consumption, and overall platform costs.
• Implement CI/CD pipelines for AI applications and agent deployments.
• Ensure security, compliance, reliability, and maintainability of AI services.
• Run architecture reviews and technical design sessions.

Skills

Python

Distributed systems

REST APIs

AI/Agent architectures

Team leadership

Cloud-native

Tools

Docker

Azure Functions

Azure OpenAI Services

AKS

CI/CD pipelines

Git

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 role leads a small team responsible for architecting and delivering autonomous agents. Field Product Managers (FPMs) define the product features and capabilities the agents need to support what the agent needs to accomplish and for which client/program. This team owns how that gets architected and delivered: orchestration design, tooling, agent standards, evaluation, and production reliability.

Because AI agents will also show up inside engineering workflows owned by other Lead Developers (e.g., code generation, testing, delivery automation), this role coordinates closely with those Leads so agent implementations inside engineering are built to the standards and requirements those Leads set for their own domains this role is not overriding other Leads' engineering requirements, it's the shared agent-implementation capability they draw on.

What You Own

• Agent Architecture & Delivery Translate FPM-defined product features/capabilities into agent architecture, orchestration design, and delivery plans.


• Technical Design — Design multi-agent systems, tool-calling patterns, memory/orchestration approaches, and reusable agent frameworks used across teams.


• Team Leadership — Lead and mentor the small team of engineers implementing agents; review designs, unblock technical decisions, set coding/agent-eval standards for the team.


• Coordination with Engineering Leads — Ensure agents built for engineering workflows (e.g., CI/CD automation, code review agents) meet the requirements set by the relevant Lead Developer for that domain — this role builds it, the domain Lead sets the bar.


• Operational Quality — Build monitoring, logging, and evaluation frameworks; own token/cost efficiency and reliability of shipped agents.

Key Responsibilities

Agentic Workflow Development

• Build intelligent agents that automate engineering, product, support, and operational workflows against FPM-defined requirements.


• Develop multi-agent systems capable of planning, reasoning, and task execution.


• Create reusable agent frameworks and libraries that accelerate development across teams.


• Build workflow automation using tool calling, memory, and orchestration patterns.

Enterprise AI Integration

• Integrate AI solutions with internal and external business systems.


• Develop secure API and data access frameworks.


• Create retrieval-augmented generation (RAG) systems leveraging enterprise knowledge.


• Design scalable architectures supporting both internal and customer-facing AI capabilities.

Team Leadership

• Lead and mentor a small team of AI engineers delivering against the FPM-defined roadmap.


• Set coding standards, design patterns, and agent-engineering best practices for the team.


• Run architecture reviews and technical design sessions.


• Coordinate with other Lead Developers to align on standards for any agents touching shared engineering systems.

DevOps & Operations

• Build monitoring, logging, evaluation, and performance frameworks for AI systems.


• Optimize model utilization, token consumption, and overall platform costs.


• Implement CI/CD pipelines for AI applications and agent deployments.


• Ensure security, compliance, reliability, and maintainability of AI services.

Qualifications Required:-

• 5+ years of professional software engineering experience.


• 2+ years building production AI-enabled applications.


• Experience designing cloud-native distributed systems.


• Prior experience leading a small team or serving as a technical lead on a delivery team.


• Experience building and consuming REST APIs.


• Expert-level Python development.


• Strong understanding of software architecture and design patterns.


• Experience with modern cloud platforms (Azure strongly preferred).


• Experience with containerization technologies such as Docker.


• Experience with CI/CD pipelines and DevOps practices.


• Strong SQL and data integration capabilities.


• Experience with Git and collaborative software development workflows.

Preferred — AI & Agentic Frameworks

• LangGraph, CrewAI, Microsoft Semantic Kernel, AutoGen, OpenAI Agents Framework, Anthropic APIs, or Azure OpenAI Services.

Preferred — Agentic System Development

• Multi-agent orchestration systems, tool calling workflows, RAG, prompt management frameworks, knowledge retrieval systems, autonomous workflow automation, evaluation/benchmarking frameworks.

Preferred — Cloud & Infrastructure

• Azure Functions, Azure AI Services, Azure Kubernetes Service (AKS), Azure API Management, event-driven architectures, observability/monitoring platforms.

Preferred — Modern Engineering Practices

• GitHub Copilot, AI-assisted software development, test automation, Infrastructure as Code, secure SDLC practices, DevSecOps methodologies.