Engineering Manager / Director

Avo Automation is a SaaS business focused on automation of the software delivery process. Our Platform is recognized as leader by market leading analyst like Gartner and G2. We are a young and fast-moving business that looks for hungry and driven people to join our team. We offer a holistic, enterprise-grade platform that unifies test automation and test data management. Avo Automation works with clients across the globe. 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. To put in another way let’s assume an application you use every day, took 1 year to build testing alone took 3 month of entire build time.

Avo Automation counts marquee organizations like Sony, Mizuho, CNA, Emerson, Voya etc. as our major clients.

We bring a set of amazing products to the table:

1. Avo Assure- A Test Automation

   platform that supports over 100 technologies.

2. Avo iTDM(Intelligent Test Data Management)-A market leading data masking and synthetic data generation engine to

   expedite testing further.

Top Analysts Recommend Avo

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. With a growing market presence and higher customer satisfaction score, we are delighted to be modernizing how organizations test applications.

https://avoautomation.ai/

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About the Role

Engineering Manager/Director

Key Responsibilities

Technical Leadership

• Drive cloud-native SaaS architecture and distributed systems design.
• Champion

  CI/CD pipelines

  for safe, automated, and rapid delivery.
• Guide teams on AI/ML workflows: data pipelines → model training → deployment → monitoring.

Agile & Lean Practices

• Promote

  story slicing

  into small, testable increments to maximize flow.
• Scale agile practices across teams while balancing autonomy and alignment.
• Foster iterative delivery and tight feedback loops.

People & Talent Management

• Coach engineers to own delivery, experiment, and continuously improve.
• Mentor technical leads in both software engineering and AI/ML best practices.
• Build a culture of safe, frequent deployments and responsible AI adoption.

Operational Excellence

• Ensure release reliability through monitoring, observability, and automated rollback.
• Embed

  MLOps

  and continuous retraining for AI-powered SaaS.
• Define metrics for

  deployment frequency, lead time, change failure rate, and AI model performance

  .

Strategic Thinking & Business Alignment

• Align engineering throughput with product roadmaps and business outcomes.
• Balance speed of delivery with long-term maintainability and compliance (esp. in AI systems).
• Drive innovation while managing technical debt responsibly.

Communication & Change Leadership

• Translate complex engineering and AI concepts into business value for executives and customers.
• Lead cultural change toward

  “always deployable” software

  and responsible AI integration.
• Influence stakeholders with clarity on trade-offs (speed vs. reliability vs. cost).

Qualifications

• 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

  SaaS, 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.