Engineering project manager

2 days ago

Bangalore, India Avo Automation Full time

Avo Automation is a Saa S business focused on automation of the software delivery process. We offer a holistic, enterprise-grade platform that unifies test automation and test data management. Our mission is to help businesses assure digital perfection. We are backed by SLK Group, a leading technology provider, with offices in USA, Europe and India. The automation testing market is growing at 18% annually is already valued at over USD 20 Billion, that’s just the product industry. Testing services market is over USD 200 Billion. Testing takes 20-30 % of entire software delivery effort. Avo Automation counts marquee organizations like Sony, Mizuho, CNA, Emerson, Voya etc. Avo Assure- A Test Automation platform that supports over 100 technologies. # Avo i TDM(Intelligent Test Data Management)-A market leading data masking and synthetic data generation engine to expedite testing further. Top analysts and peer reviewers like Gartner and G2 recognize Avo as a representative vendor for test automation. The latest G2 Enterprise Grid Report for Test Automation ranks Avo as a ‘Leader’ in this space. Job Description – Engineering Manager / Director Employment Type: Full-time Experience: 10–15+ years We are seeking an experienced Engineering Manager/Director to lead and scale our engineering organization. This role requires deep expertise in Saa S architectures, AI/ML integration, and agile practices, along with strong people leadership and business alignment skills. You will guide teams to deliver high-quality, AI-enabled software at speed while fostering a culture of ownership, experimentation, and continuous improvement. Drive cloud-native Saa S architecture and distributed systems design. Guide teams on AI/ML workflows: data pipelines → model training → deployment → monitoring. Agile & Lean Practices Scale agile practices across teams while balancing autonomy and alignment. People & Talent Management Mentor technical leads in both software engineering and AI/ML best practices. Build a culture of safe, frequent deployments and responsible AI adoption. Ensure release reliability through monitoring, observability, and automated rollback. Embed MLOps and continuous retraining for AI-powered Saa S. Define metrics for deployment frequency, lead time, change failure rate, and AI model performance . Align engineering throughput with product roadmaps and business outcomes. Balance speed of delivery with long-term maintainability and compliance (esp. Translate complex engineering and AI concepts into business value for executives and customers. Lead cultural change toward “always deployable” software and responsible AI integration. Bachelor’s/Master’s degree in Computer Science or related field. ~10–15+ years in software engineering, with 5+ years in leadership roles. ~ Proven track record of leading teams in Saa S, cloud-native, and AI/ML-powered products . ~ Strong knowledge of CI/CD, distributed systems, MLOps, and agile scaling . ~ Excellent people leadership, coaching, and communication skills. ~ Ability to align engineering strategy with business goals.

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