Engineering Manager

Responsibilities:

• Lead and mentor a team of software engineers, fostering a culture of ownership, collaboration, and continuous learning.
• Drive end-to-end product development, from architecture and design to deployment and maintenance.
• Collaborate with product managers and AI teams to translate business requirements into scalable technical solutions.
• Define engineering roadmaps, delivery milestones, and execution strategies.
• Ensure timely delivery while maintaining high standards for quality, security, scalability, and performance.
• Conduct architecture reviews, code reviews, and technical design discussions.
• Build and improve engineering processes, including Agile execution, CI/CD, testing, and release management.
• Manage technical risks, dependencies, and resource planning across multiple projects.
• Recruit, coach, and retain top engineering talent.
• Work closely with customers and stakeholders to understand product requirements and translate feedback into product improvements.
• Champion engineering best practices, automation, observability, and operational excellence.

Requirements:

• Bachelor's or master's degree in computer science, electronics, or a related engineering discipline.
• 10-14 years of software engineering experience with at least 3 years in engineering leadership.
• Proven experience building and shipping B2B or enterprise software products.
• Strong expertise in system design, distributed systems, cloud-native architectures, and microservices.
• Hands-on experience with Python, Go (Golang), Java, or C++.
• Experience with AWS, Azure, or Google Cloud Platform.
• Strong understanding of DevOps, CI/CD pipelines, Docker, Kubernetes, and containerized deployments.
• Experience leading Agile engineering teams.
• Excellent stakeholder management and communication skills.

Preferred Qualifications:

• Experience building AI, machine learning, LLM, speech AI, NLP, or generative AI products.
• Experience with Conversational AI, Voice Assistants, or Speech Technologies (ASR/TTS).
• Exposure to MLOps and AI product deployment.
• Experience working in high-growth startups or product companies.
• Knowledge of automotive software, embedded systems, or Software-Defined Vehicles (SDV) is a plus.

Skills

aws, azure, c++, ci/cd, devops, docker, gcp, golang, google cloud platform, java, kubernetes, microservices, python