Agentic Ai OS Implementation Engineer
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Key skills for this role
About the Role
Nexo is seeking a visionary Principal Agentic AI Engineer to architect and deploy production-grade autonomous AI systems. The role involves designing multi-agent systems, integrating with legacy RPA/BPM platforms, and implementing context/memory management.
Key Skills for This Role
Responsibilities
- Design and develop multi agent systems and coordinators using frameworks like LangGraph and CrewAI.
- Integrate AI agents securely with existing infrastructure, internal databases, and third party SaaS using legacy RPA/BPM platforms.
- Implement short term and long term memory systems, state graphs, and advanced RAG pipelines.
- Enable agents to operate across various software by linking them via standard APIs and protocols.
- Design testing, monitoring, and observability pipelines to ensure autonomous workflows are reliable, secure, and compliant.
Requirements
- 10+ years in IT with hands on technical architecture and implementation experience spanning multiple enterprise RPA and BPM platforms
- Deep understanding of modern foundation models (OpenAI, Claude, Gemini, Llama) and prompt engineering techniques
- Strong programming background in Python and experience with asynchronous processing, REST APIs, and microservices
- Familiarity with vector databases (e.g., Pinecone, Weaviate) and building RAG pipelines
- Proven ability to map business processes, evaluate process constraints, and design reusable intelligent automation frameworks
Full Job Posting
Role Overview
- We are seeking a visionary Principal Agentic AI Engineer to architect, build, and deploy production grade autonomous AI systems and operating ecosystems.
- This role requires a seasoned expert who can bridge the gap between classic RPA, BPM workflows, and dynamic, LLM driven AI agents.
Key Responsibilities
- Design and develop multi agent systems and coordinators using frameworks like LangGraph and CrewAI.
- Leverage your extensive background in platforms like UiPath, Blue Prism, and enterprise BPM suites to integrate AI agents securely with existing infrastructure.
- Implement short term and long term memory systems, state graphs, and advanced RAG pipelines.
- Enable agents to operate across various software by linking them via standard APIs and protocols.
- Design testing, monitoring, and observability pipelines to ensure autonomous workflows are reliable, secure, and compliant.
Qualifications & Technical Competencies
- 10+ years in IT, with hands on technical architecture and implementation experience spanning multiple enterprise RPA and BPM platforms.
- Deep understanding of modern foundation models (OpenAI, Claude, Gemini, Llama) and prompt engineering techniques.
- Strong programming background in Python and experience with asynchronous processing, REST APIs, and microservices.
- Familiarity with vector databases (e.g., Pinecone, Weaviate) and building RAG pipelines.
- Proven ability to map business processes, evaluate process constraints, and design reusable intelligent automation frameworks.
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