AI Python Engineer
AI Delivery Engineer (Agent Tooling & Code Generation) 🤖⚡
ZentixSoft is looking for an AI Delivery Engineer! 🚀
Format: Full-Time Outstaffing, long-term remote project. You will build and ship production-grade AI agent tooling and code-generation solutions, embedding AI agents directly into the delivery lifecycle.
💡 Why ZentixSoft?
💸 Salary Review: A structured system of compensation reviews aligned with your engineering growth.
⚖️ Work-Life Balance: Sustainable workflows with no senseless overtime, helping you keep your resource fully charged.
🦾 Trust and Transparency: Zero micromanagement and no invasive time-trackers—we fully trust your professional autonomy.
🎁 Gifts & Culture: Corporate gifts for holidays, birthdays, and a true team atmosphere where your voice always matters.
🧩 Responsibilities:
- AI Tooling & Automation: Design, build, and maintain AI agent tooling that automates engineering and business workflows.
- Code Generation Pipelines: Develop and refine developer copilots and code-generation workflows.
- Agent Integration & RAG: Integrate LLM APIs, agent-orchestration frameworks, RAG pipelines, and vector databases into production systems.
- Production Reliability: Monitor, evaluate, and enhance agent performance, safety guardrails, and reliability from prototype to production rollout.
- Documentation & Adoption: Document tooling, establish prompt engineering standards, and support internal teams in adopting AI agents.
🎓 Requirements:
- Engineering Background: 4+ years of commercial software engineering experience, with a recent focus on applied AI/LLM systems.
- Agent Frameworks: Hands-on experience building LLM-based agents or agent-orchestration frameworks (LangChain, LangGraph, AutoGen, or custom pipelines).
- Code-Gen & Copilots: Proven experience with code-generation tooling and AI-assisted development workflows.
- Core Tech Stack: Strong Python skills (TypeScript/JavaScript is a plus) for agent tooling and integration.
- LLM & Vector Ecosystem: Experience working with LLM APIs (OpenAI, Anthropic, etc.), RAG architecture, vector stores, prompt engineering, and guardrails.
- Production Shipping: Demonstrated ability to take AI concepts and prototypes to production-grade deployment.
➕ Nice to Have:
- Experience deploying agentic frameworks in enterprise settings.
- Familiarity with MLOps / LLMOps practices.
- Contributions to open-source AI tooling.
📍 Project Details:
⏳ Duration: Long-term (Full-time).
📍 Location: Fully Remote.