Staff Agentic AI Engineer

Accountabilities:
In this role, you will design and develop advanced AI agent platforms that support enterprise automation and intelligent customer experiences. You will contribute to the architecture, implementation, evaluation, and continuous improvement of agentic AI systems used in complex production environments. Design, build, and optimize production-grade AI agent systems that power enterprise automation workflows. Architect agent workflows incorporating reasoning, tool usage, retrieval, guardrails, escalation mechanisms, and performance monitoring. Evaluate and implement emerging agent orchestration frameworks and patterns to support new AI capabilities. Develop and maintain AI evaluation frameworks, including LLM-as-judge workflows, regression testing, quality measurement, and production behavior analysis. Diagnose and improve agent performance by analyzing prompts, retrieval quality, tool selection, latency, cost, and completion rates. Build RAG and embedding-based solutions that enable intelligent access to enterprise knowledge. Develop scalable Python services and AI platform components deployed in cloud environments. Design systems that transform complex and unstructured information into structured, reliable knowledge models. Collaborate with product, engineering, and platform teams to translate AI innovations into practical platform features. Establish engineering standards and best practices for optimizing agentic AI systems. Stay informed on advances in LLMs, AI agents, retrieval systems, evaluation methodologies, and enterprise AI solutions. Requirements: The ideal candidate is a senior AI engineer with strong experience building production machine learning systems, LLM applications, and scalable software platforms. You should be comfortable solving ambiguous technical challenges and independently driving complex AI initiatives. Bachelor’s degree or higher in Computer Science, Engineering, Mathematics, Statistics, or another quantitative discipline. 5–7+ years of experience in AI/ML engineering, applied machine learning, NLP, or AI systems development. 2+ years of hands-on experience building production LLM applications or AI agent systems. Proven experience developing AI agents used by customers, enterprises, or business users. Experience with agent orchestration frameworks such as LangGraph, LangChain, or similar technologies. Strong Python engineering skills with experience building scalable production software. Experience designing AI architectures involving reasoning flows, tool use, memory, retrieval, guardrails, and workflow orchestration. Strong understanding of RAG architectures, embeddings, retrieval optimization, and knowledge-grounded generation. Experience creating AI evaluation systems, including quality metrics, automated testing, and production monitoring. Experience deploying and operating AI systems in AWS cloud environments. Familiarity with AI-assisted development tools such as Codex, Claude Code, Cursor, or similar platforms. Ability to work independently, demonstrate strong technical judgment, and lead complex engineering initiatives. Preferred experience with knowledge graphs, enterprise knowledge modeling, automation platforms, customer experience systems, or AI governance practices. Benefits: Opportunity to work on cutting-edge agentic AI technology transforming enterprise workflows. High-impact role with ownership over foundational AI systems and platform capabilities. Remote-friendly work environment with flexibility. Opportunity to collaborate with talented engineers, product leaders, and AI specialists. Exposure to large-scale enterprise AI applications and complex real-world challenges. Continuous learning opportunities in rapidly evolving AI technologies. Competitive compensation package and employee benefits. Inclusive workplace culture focused on innovation, collaboration, and professional growth.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
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