QA Lead, IT​/Tech, IT QA Tester ​/ Automation

QA Lead for Swamy

Contract to Hire

Must be Local to Hartford

Position Summary

We are looking for an exceptionally skilled and driven Conversational AI QA Engineering Leader. The ideal candidate will have a robust background in building and guiding high-performing QA teams focused on conversational AI solutions. This role involves coaching and mentoring QA engineers to ensure the delivery of high-quality voice and chatbot products and services through rigorous testing and validation strategies.

If you are passionate about quality assurance in conversational AI and have a proven track record of leading successful QA teams in a fast-paced environment, we would love to hear from you.

Responsibilities

• Provide strategic and technical QA leadership across multiple conversational AI delivery teams, ensuring alignment with business goals and customer needs.
• Lead the development and execution of comprehensive QA strategies for conversational AI solutions, including voice and chatbots.
• Ensure timely execution of QA cycles, quality outcomes, and measurable impact through test automation and manual validation.
• Build, mentor, and inspire high-performing teams of QA engineers and test managers. Foster a culture of quality, collaboration, and continuous improvement.
• Continuously evaluate and drive adoption of emerging QA tools and technologies to enhance testing capabilities and maintain competitive advantage.
• Collaborate with engineering and product leadership to identify quality risks and communicate QA progress and metrics.
• Champion best practices in QA methodologies, agile testing, and AI model validation.
• Establish KPIs, governance models, and QA frameworks to ensure scalability, compliance, and performance of conversational AI solutions.
• Identify opportunities for improving customer experience through robust QA processes and ROI-driven quality initiatives.

Success Criteria

• Thrive in a fast-paced, high-energy environment where innovation and agility are paramount.
• Demonstrate exceptional leadership and interpersonal skills, with the ability to motivate and inspire QA teams.
• Exhibit strong technical acumen in QA engineering, with hands-on experience in testing AI and machine learning solutions.
• Possess a strategic mindset, capable of translating business objectives into actionable QA plans.
• Show a commitment to excellence, with a keen eye for detail and a passion for delivering high-quality products.
• Embrace a culture of collaboration, working seamlessly with diverse teams to achieve common goals.
• Be a visionary thinker, always looking for ways to push the envelope and drive quality standards forward.

Required Qualifications

• 10+ years of experience in QA leadership roles, with at least 5 years focused on cloud-native environments (IBM & Azure highly preferred) testing conversational AI solutions, including voice and chatbots.
• 10+ years of experience translating complex QA strategies into strategic business outcomes.
• 10+ years of experience with QA automation and scripting using languages such as Java, Python, or Node.js.
• 7+ years of experience as a QA lead for large-scale AI or digital transformation programs working in a high-performance Agile environment.
• 7+ years of experience testing applications deployed to the cloud, integrated with cloud technologies.
• 7+ years of experience with open-source automation servers such as Jenkins, Octopus, or Git Hub Actions.
• 7+ years of experience with API testing tools such as Postman, Swagger, or similar tools.
• Strong understanding of conversational AI technologies (e.g., chatbots, voice assistants, LLMs, STT/TTS, NLU/NLP engines) and QA techniques for validating these technologies, including model testing, regression, and performance validation.

Preferred Qualifications

• Executive-level communication skills, capable of effectively articulating QA and strategic concepts to multiple stakeholders.
• Experience with IBM WatsonX and its suite of AI tools and services.
• Advanced degree (Master’s or PhD) in Computer Science, Engineering, AI, or a related field.
• Hands-on experience with Large Language Models (LLM) and their practical applications in conversational AI QA.
• Familiarity with SAFE agile methodologies and experience in leading agile QA teams.