Applied AI Engineer

Sourced from careerium.unaux.com

Appsilon is hiring an Applied AI Engineer to build and deploy AI agents and generative AI solutions in production. The role involves designing agentic workflows, integrating with client systems, and optimizing performance using LLMOps best practices. Ideal candidates have proven experience with LLM orchestration frameworks, Python, and deploying AI in production environments.

• Build AI Agents with domain context for specialized tasks, including multi-step reasoning, tool use, and autonomous decision-making. Design and implement agentic workflows — orchestrating LLMs, retrieval systems, and external tools into reliable, production-grade pipelines. Integrate agents with client applications, APIs, and enterprise systems. Evaluate, iterate on, and optimize agent performance using structured testing, tracing, and observability. Deploy and maintain generative AI solutions in production environments (APIs, microservices, cloud architecture). Document your work, follow best practices for LLMOps, and help shape AI development standards at Appsilon. Work closely with Data Engineers, Developers, and Analysts to integrate GenAI solutions into full-scale applications.

• Proven experience building and deploying AI agents or agentic systems in production (not just prototypes). Deep familiarity with LLM orchestration frameworks (e.g., LangChain, LangGraph, CrewAI, Autogen, Claude Agent SDK, or similar). Strong understanding of prompt engineering, retrieval-augmented generation (RAG), tool use, and function calling patterns. Hands-on experience with LLM APIs (OpenAI, Anthropic, Google, open-source models) and managing their lifecycle in real-world applications. Strong programming skills in Python with experience building robust, maintainable backend services. Ability to evaluate and debug agent behavior - including tracing, logging, and structured evaluation of multi-step workflows. Excellent communication skills and a collaborative approach to teamwork.