AI/ML Engineering Manager

Arbisoft


Date: 17 hours ago
City: Lahore
Contract type: Full time

Role Overview:

We are looking for a seasoned Engineering Manager to lead two fast-moving products. This role combines technical leadership with people management. You will guide, mentor, and measure the output and performance of engineers across Machine Learning, Full-Stack Development, and QA. While the role is not primarily hands-on, you must possess deep technical competence across modern SaaS stacks, AI/ML, and infrastructure to set direction, maintain best practices, and ensure architectural excellence.


You will also act as the primary owner of architecture, infrastructure, release pipelines, and risk/health tracking, ensuring our products achieve industry-best standards for scalability, reliability, and innovation.


This role requires strong technical leadership, deep expertise in modern deployment pipelines, and Python and AI/ML, contributing directly to the company's product and technology strategy.


Key Responsibilities:

  • Lead, coach, and mentor engineers (ML, full-stack, and QA) across two squads, driving delivery and technical excellence.
  • Champion best practices in engineering, including code quality, testing, observability, and security.
  • Own the overall software architecture for both platforms, ensuring scalability, security, and high availability.
  • Oversee application and infrastructure design, cloud environments, and release/production pipelines.
  • Ensure adherence to best practices in SaaS product engineering, CI/CD, observability, and DevOps/MLOps.
  • Build a culture of ownership, accountability, and continuous improvement.
  • Guide teams working with LLMs, transcription pipelines, embeddings, and ML-driven workflows.
  • Ensure models, services, and APIs are production-ready, performant, and compliant.
  • Cross-functional alignment with Product and Design.
  • Manage technical debt, prioritize effectively, and de-risk engineering roadmaps.
  • Track platform reliability, uptime, latency, and cost efficiency.
  • Define and monitor engineering metrics (e.g., DORA, QA pass rates, SLA adherence).
  • Identify and mitigate risks across infrastructure, data, and compliance.


Requirements:

  • 10 years of professional experience in software engineering, with increasing leadership responsibilities.
  • Prior hands-on background in backend or full-stack development, plus strong understanding of ML/AI systems and LLM integration.
  • Hands-on experience working with ML models, data pipelines, and inference systems.
  • Proven track record of leading AI/ML-focused engineering teams and shipping production SaaS products.
  • Strong command of system design, distributed systems, and SaaS architecture.
  • Proficiency with cloud platforms (AWS, GCP, or Azure), CI/CD pipelines, observability tools, and DevOps practices.
  • Understanding of AI/ML workflows (training, inference, evaluation, deployment) and experience with LLMs, NLP, and transcription models.
  • Familiarity with modern frontend/backend frameworks (React, Node.js, Python).
  • Excellent ability to guide, train, and measure engineering performance.
  • Strong communication and collaboration skills with the ability to operate autonomously in cross-functional squads.
  • Domain expertise in AI SaaS products, with the ability to challenge and set technical direction confidently.
  • Strategic mindset: able to balance short-term delivery with long-term scalability and reliability.
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

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