Machine Learning Engineer - Agentic AI
First seen by Alion on Nov 13, 2026.
Job Overview :
We are looking for an experienced Machine Learning Engineer specializing in Agentic AI, multi-agent architectures, distributed systems, and orchestration platforms. The ideal candidate will have strong programming expertise in Python, extensive experience designing complex AI-driven systems, and the ability to lead technical architecture and engineering initiatives across cloud environments.
The role involves architecting and implementing scalable agentic AI solutions, designing multi-agent systems, establishing engineering standards, and driving the adoption of emerging AI technologies. The candidate will work closely with engineering, architecture, DevOps, security, and business teams to deliver reliable, secure, and scalable AI solutions.
Key Responsibilities :
- Design, architect, and implement advanced Agentic AI solutions and multi-agent systems for enterprise applications.
- Lead the development of distributed and event-driven architectures to support scalable AI applications and orchestration platforms.
- Design and implement agent-to-agent (A2A) communication protocols, runtime environments, and orchestration frameworks. Develop scalable AI applications and backend services using Python and other modern programming languages such as Java, Go, or C++.
- Architect and deploy cloud-native AI solutions across AWS, Google Cloud Platform (GCP), and Microsoft Azure.
- Establish technical architecture standards, engineering guidelines, and best practices for agentic AI development.
- Drive the adoption of emerging AI technologies, frameworks, and orchestration solutions across engineering teams.
- Implement cloud-native DevOps practices to support deployment, scalability, performance, and reliability of AI systems.
- Ensure enterprise security requirements are addressed through appropriate IAM, RBAC, access controls, and sandboxing mechanisms.
- Establish technical governance and compliance standards across AI development and deployment initiatives.
- Monitor system performance, identify architectural challenges, and drive continuous improvements.
- Lead incident response activities, troubleshoot complex system issues, and ensure timely resolution.
- Collaborate with cross-functional teams to align technical architecture with business and enterprise requirements.
- Mentor senior engineers and technical teams, providing guidance on system architecture, distributed computing, and agentic AI development.
- Evaluate new technologies and recommend solutions to improve system scalability, security, and operational efficiency.
Required Skills and Qualifications :
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 1214 years of progressive experience in software engineering, distributed systems, AI engineering, or orchestration platforms.
- Strong proficiency in Python programming and familiarity with at least one additional programming language, such as Java, Go, or C++. Deep understanding of Agentic AI, multi-agent architectures, and AI orchestration systems.
- Proven experience designing and implementing complex agentic or event-driven systems.
- Strong knowledge of A2A protocols, agent runtime environments, and distributed system architecture.
- Experience working with cloud platforms such as AWS, Google Cloud Platform, or Microsoft Azure.
- Expertise in cloud-native DevOps practices and modern deployment environments.
- Understanding of enterprise security, IAM, RBAC, and sandboxing in cloud environments.
- Experience establishing technical standards, architecture guidelines, and compliance practices.
- Proven ability to lead technical initiatives, mentor engineering teams, and manage complex technical challenges.
- Excellent analytical, problem-solving, communication, and cross-functional collaboration skills.
Skills
Artificial Intelligence, Agentic AI, Distributed Systems, Python, AWS, Google Cloud Platform, Azure, Security