Verified Job
Engineering - Architecture
Principal Agentic AI Engineer (Located, Spain, Portugal, or Mexico)
Engineering - Architecture
#7421
Remote / WFH
BMC Software
Job Description
Description and Requirements
"At BMC trust is not just a word - it's a way of life!"
Description And Requirements
CareerArc Code
CA-PF
Remote
BMC empowers nearly 80% of the Forbes Global 100 to accelerate business value, faster than humanly possible. Our industry-leading portfolio unlocks human and machine potential to drive business growth, innovation, and sustainable success. BMC does this in a simple and optimized way by connecting people, systems, and data that power the world’s largest organizations so they can seize a competitive advantage.
Locations:
Canada, Spain, Portugal, or Mexico
We are evolving from foundational LLM applications to fully autonomous, agent driven systems. As a Senior Agentic AI Engineer, you will architect and deploy intelligent agents capable of multi-step reasoning, tool use, and independent execution across complex internal workflows. This role offers the chance to work on advanced agent orchestration, real-world integrations, and production-scale AI systems that deliver tangible business impact.
Here is how, through this exciting role, YOU will contribute to BMC's and your own success:
• Design & develop autonomous agents: Architect and build advanced agentic AI workflows that go beyond FAQ chatbots, enabling agents to plan multi-step tasks, make decisions, and act autonomously in customer success use-cases.
• Includes developing agents capable of handling complex sequences (e.g. analyzing customer data, initiating follow-ups, updating records) with minimal human intervention.
• Implement and refine multi-agent systems: Enable agents to communicate and delegate tasks to each other (multi-agent orchestration) for complex, cross-functional processes involving multiple enterprise systems.
• Partner with IT and R&D to embed agents: Integrate with platforms such as Microsoft Power Platform and Salesforce Agentforce to execute business processes and interact with CRM databases, internal APIs, and third-party services.
• Lead deployment of agents into production: Orchestrate for scalability and reliability, implementing robust monitoring, logging, and leading AI operations practices (e.g. using tools for tracing agent reasoning and performance) to ensure uptime and quick debugging of issues.
• Develop and optimize RAG pipelines: Incorporate vector databases and embeddings to give agents access to customer data, knowledge base articles, historical interactions and other relevant context during conversations and decision-making.
• Ensure all autonomous agents adhere to AI safety & guardrails: Manage ethical guidelines, safety constraints, and data privacy requirements.
• Serve as the technical expert for AI within the Customer Success organization: Collaborate with product managers and subject-matter experts to translate business processes into AI workflows and agent behaviors.
• Innovation & Strategy: Stay abreast of the latest advancements in AI agent development, including emerging frameworks and tools for autonomous agents. Provide recommendations on new technologies or methodologies that could accelerate agent development. Drive the technical roadmap for incorporating these innovations, ensuring our AI stack remains at the leading edge.
To ensure you’re set up for success, you will bring the following skillset & experience:
• 5+ years of professional experience in software engineering or machine learning, including substantial experience (1+ years) building and deploying LLM-powered applications or autonomous agent systems in production.
• Strong programming skills in Python (experience with relevant libraries and frameworks) and software engineering best practices (code review, testing, version control, CI/CD).
• Experience creating and consuming RESTful APIs or microservices for AI-driven applications. Familiarity with devops/MLOps for deploying and maintaining AI models and agents at scale.
• Hands-on experience working with Large Language Models and natural language processing techniques. Direct experience with LLM APIs (e.g., OpenAI GPT-4, Azure OpenAI Service, Anthropic Claude, etc.) and fine-tuning or training custom models is required. Strong grasp of prompt engineering and techniques to guide LLM behavior, as well as understanding of transformer-based model capabilities and limitations (e.g. context window management, tokenization).
• Practical experience building autonomous agents or multi-agent systems using LangChain, Microsoft Semantic Kernel (SK), Salesforce Agentforce, AutoGen, LlamaIndex, ReAct or similar agent development frameworks. Knowledge of how to enable agents to use tools, call APIs, maintain state or memory, and interact with each other (or with humans) to achieve goal
"At BMC trust is not just a word - it's a way of life!"
Description And Requirements
CareerArc Code
CA-PF
Remote
BMC empowers nearly 80% of the Forbes Global 100 to accelerate business value, faster than humanly possible. Our industry-leading portfolio unlocks human and machine potential to drive business growth, innovation, and sustainable success. BMC does this in a simple and optimized way by connecting people, systems, and data that power the world’s largest organizations so they can seize a competitive advantage.
Locations:
Canada, Spain, Portugal, or Mexico
We are evolving from foundational LLM applications to fully autonomous, agent driven systems. As a Senior Agentic AI Engineer, you will architect and deploy intelligent agents capable of multi-step reasoning, tool use, and independent execution across complex internal workflows. This role offers the chance to work on advanced agent orchestration, real-world integrations, and production-scale AI systems that deliver tangible business impact.
Here is how, through this exciting role, YOU will contribute to BMC's and your own success:
• Design & develop autonomous agents: Architect and build advanced agentic AI workflows that go beyond FAQ chatbots, enabling agents to plan multi-step tasks, make decisions, and act autonomously in customer success use-cases.
• Includes developing agents capable of handling complex sequences (e.g. analyzing customer data, initiating follow-ups, updating records) with minimal human intervention.
• Implement and refine multi-agent systems: Enable agents to communicate and delegate tasks to each other (multi-agent orchestration) for complex, cross-functional processes involving multiple enterprise systems.
• Partner with IT and R&D to embed agents: Integrate with platforms such as Microsoft Power Platform and Salesforce Agentforce to execute business processes and interact with CRM databases, internal APIs, and third-party services.
• Lead deployment of agents into production: Orchestrate for scalability and reliability, implementing robust monitoring, logging, and leading AI operations practices (e.g. using tools for tracing agent reasoning and performance) to ensure uptime and quick debugging of issues.
• Develop and optimize RAG pipelines: Incorporate vector databases and embeddings to give agents access to customer data, knowledge base articles, historical interactions and other relevant context during conversations and decision-making.
• Ensure all autonomous agents adhere to AI safety & guardrails: Manage ethical guidelines, safety constraints, and data privacy requirements.
• Serve as the technical expert for AI within the Customer Success organization: Collaborate with product managers and subject-matter experts to translate business processes into AI workflows and agent behaviors.
• Innovation & Strategy: Stay abreast of the latest advancements in AI agent development, including emerging frameworks and tools for autonomous agents. Provide recommendations on new technologies or methodologies that could accelerate agent development. Drive the technical roadmap for incorporating these innovations, ensuring our AI stack remains at the leading edge.
To ensure you’re set up for success, you will bring the following skillset & experience:
• 5+ years of professional experience in software engineering or machine learning, including substantial experience (1+ years) building and deploying LLM-powered applications or autonomous agent systems in production.
• Strong programming skills in Python (experience with relevant libraries and frameworks) and software engineering best practices (code review, testing, version control, CI/CD).
• Experience creating and consuming RESTful APIs or microservices for AI-driven applications. Familiarity with devops/MLOps for deploying and maintaining AI models and agents at scale.
• Hands-on experience working with Large Language Models and natural language processing techniques. Direct experience with LLM APIs (e.g., OpenAI GPT-4, Azure OpenAI Service, Anthropic Claude, etc.) and fine-tuning or training custom models is required. Strong grasp of prompt engineering and techniques to guide LLM behavior, as well as understanding of transformer-based model capabilities and limitations (e.g. context window management, tokenization).
• Practical experience building autonomous agents or multi-agent systems using LangChain, Microsoft Semantic Kernel (SK), Salesforce Agentforce, AutoGen, LlamaIndex, ReAct or similar agent development frameworks. Knowledge of how to enable agents to use tools, call APIs, maintain state or memory, and interact with each other (or with humans) to achieve goal
