
Senior AI Engineer
- Mexicali, B.C.
- Permanente
- Tiempo completo
Our Business Segment: Architecture, Engineering, Construction and Owner Segment (AECO)
Our Department: Construction Management Solutions (CMS)Are you passionate about architecting and leading the development of autonomous AI agents, eager to drive innovative AI solutions, and mentor a talented team in a dynamic environment?What You Will DoThis role offers a pivotal opportunity to lead and innovate in Agentic AI engineering, working within a high-performing team that fosters expertise and impactful contributions. The successful candidate will independently drive and oversee the full lifecycle of agentic AI projects, from conceptualization and design to advanced implementation, deployment, and ongoing optimization. This position requires a strong technical leader who can solve complex problems, make architectural decisions, and guide junior engineers in developing sophisticated AI agents that deliver significant business value.
- Design, develop, and implement complex AI agent architectures, including advanced reasoning, planning, memory, and sophisticated tool integration, independently driving significant components of the agentic system.
- Lead the design and optimization of environments and large-scale datasets for training and testing AI agents, ensuring high data quality and developing advanced metrics for agent behavior, performance, and robustness.
- Architect and implement comprehensive testing, debugging, and monitoring frameworks for agent code and systems, ensuring high reliability, scalability, and performance in production environments.
- Lead the integration of AI agents into complex existing applications and new systems, defining deployment strategies, ensuring seamless operation, and establishing robust monitoring and maintenance protocols for autonomous systems.
- Collaborate extensively with cross-functional teams, including product managers, researchers, and other engineering disciplines, to translate ambiguous business needs into clear technical requirements and innovative AI solutions. Drive technical discussions and influence strategic direction.
- Mentor junior engineers, provide technical guidance, conduct code reviews, and foster a culture of best practices in agentic AI development, including principles of responsible AI and ethical considerations.
- Bachelor's degree in Computer Science, Math, Engineering, Statistics, or a closely related quantitative field, with 4+ years of professional experience in software development, including a significant focus on AI/ML. Master's or Ph.D. preferred for P4.
- Demonstrated expertise and in-depth practical experience with AI agent theories, practices, and procedures, including advanced concepts in autonomous decision-making, planning, and multi-agent systems.
- Advanced proficiency in multiple relevant programming languages (e.g., Python, C++, Java) with a strong focus on building scalable, high-performance systems and integrating complex libraries and APIs.
- Strong understanding and practical experience with advanced data structures, algorithms, and complex system design principles, with a proven track record of designing and implementing efficient and robust AI systems.
- Proven ability to independently analyze, diagnose, and solve complex technical problems with broad scope, often involving novel solutions and requiring deep analytical skills.
- Experience leading technical projects or significant features, demonstrating ownership and driving initiatives to completion.
- Extensive experience with leading frameworks for building AI agents (e.g., LangChain, AutoGen, CrewAI) and deep understanding of their underlying mechanisms.
- Proficiency in cloud computing platforms (e.g., Azure, AWS, GCP) including designing and deploying intelligent applications at scale, leveraging serverless functions, containerization, and managed AI services.
- Significant practical experience with generative AI, large language models (LLMs), and/or reinforcement learning in real-world applications.
- Strong experience with MLOps practices for deploying, monitoring, and managing AI models in production.
- Experience with advanced version control strategies, continuous integration/continuous deployment (CI/CD) pipelines, and collaborative development tools.
- Familiarity with distributed systems and microservices architectures as they relate to AI agent deployments.
- A strong portfolio of relevant projects, open-source contributions, or publications demonstrating advanced expertise in Agentic AI.