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Salary: USD 182,900 - 310,500 / annual
Calix is a cloud-first platform serving Communication Service Providers (CSPs) of all sizes. The company delivers real-time data, automation, and actionable insights through Calix One, an AI-powered platform designed to simplify operations, reduce costs, and accelerate innovation for telecom operators.
You will join as a Principal Engineer focused on AI Agent Development, leading the design, development, and deployment of intelligent autonomous agents that transform workflows and customer experiences. This is a hands-on technical role with significant scope: you will architect and build agents capable of perception, reasoning, and autonomous action, then integrate them with enterprise systems at scale.
Key responsibilities include:
- Designing and building AI agents using modern frameworks and orchestration patterns
- Integrating agents with external systems via REST APIs, microservices, and cloud platforms
- Implementing best practices for performance, scalability, and security in multi-agent environments
- Collaborating with product managers and data scientists to align agent capabilities with business objectives
- Exploring and adopting emerging technologies in Generative AI, LLM orchestration, and multi-agent frameworks
- Optimizing LLM inference and implementing advanced fine-tuning techniques (LoRA, QLoRA)
- Building and managing agent lifecycle systems and AI profiles for model selection and orchestration
You will work on projects impacting millions of users in the telecom and broadband space, contributing to a once-in-a-generation transformation of the industry.
REQUIREMENTS:
- 10+ years of software development experience with exposure to AI/ML projects
- Bachelor's or Master's degree in Computer Science, AI/ML, or related field
- Hands-on experience developing AI agents using frameworks such as Google ADK, LangChain, CrewAI, AutoGen, or similar
- Strong programming skills in Go, Rust, or Python (PL/SQL or Java experience is a plus)
- Familiarity with LLM integration, prompt engineering, and orchestration of multi-agent workflows
- Knowledge of vector databases, embeddings, and retrieval-augmented generation (RAG)
- Understanding of Generative AI, NLP, and reinforcement learning concepts
- Experience with LLM inference optimization and fine-tuning techniques (LoRA, QLoRA)
PREFERRED:
- Experience building custom AI agents for enterprise workflows (e.g., service request triage, summarization, proactive support)
- Working with agent lifecycle management and AI profiles for model selection and orchestration
- Exposure to multi-agent collaboration and autonomous decision-making systems
