Software Engineering Manager - Artificial Intelligence/Machine Learning

<p><p>We are seeking an Engineering Manager for an AI Enabled Enterprise Solutions Platform.<br/><br/><b>Job Profile : </b><br/><br/>- Lead the design and implementation of complex, scalable, and high-performance systems and architectures.<br/><br/>- Tackle challenging engineering problems, such as distributed systems, real-time data processing, and high-concurrency platforms.<br/><br/>- Drive research and development of new technologies, frameworks, and methodologies, especially in the domain of Large Language Models (LLMs) and Agentic architectures.<br/><br/>- Collaborate cross-functionally with product, data science, and infrastructure teams to deliver robust solutions.<br/><br/>- Mentor and guide fellow engineers, setting high standards for engineering excellence and best practices.<br/><br/>- Proactively identify architectural bottlenecks and propose innovative solutions.<br/><br/>- Stay abreast of the latest trends in AI, machine learning, and agentic systems, and drive their adoption where relevant.<br/><br/><b>Requirements : </b><br/><br/>- 8+ years of professional experience in software engineering, with a proven track record of solving complex architectural challenges.<br/><br/>- Deep expertise in designing and building scalable, distributed systems.<br/><br/>- Hands-on experience with LLMs, agentic systems, and advanced AI/ML architectures.<br/><br/>- Strong research skills; ability to independently evaluate and implement new technologies.<br/><br/>- Proficiency in one or more programming languages such as Python, NodeJS or Go.<br/><br/>- Experience with cloud platforms (AWS, GCP, Azure) and modern DevOps practices.<br/><br/>- Excellent problem-solving, communication, and leadership skills.<br/><br/>- Experience mentoring teams and driving engineering culture.<br/><br/><b>Preferred Qualifications : </b><br/><br/>- Published research or contributions to open-source projects in AI/ML or agentic frameworks.<br/><br/>- Experience with MLOps, model deployment, and scaling AI solutions in production.<br/><br/>- Prior work in high-growth startups or complex product environments.<br/></p><br/></p> (ref:hirist.tech)