Manager, Quality Engineering

About the position

As a Sr. Quality Engineer specializing in artificial intelligence (AI) and Machine Learning (ML) technologies, you will actively engage in your AI/ML craft, taking a hands-on approach to multiple high-visibility projects. Your expertise will be pivotal in delivering solutions that delight customers and users while also driving tangible value for Deloitte's business investments. You will leverage your extensive AI/ML engineering craftsmanship and advanced proficiency across multiple quality assurance disciplines and modern frameworks, consistently demonstrating your exemplary track record in delivering high-quality, outcome-focused solutions.

Responsibilities

• Embrace and drive a culture of accountability for customer and business outcomes.
• Develop engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality, lean designs and implementations.
• Serve as the technical advocate for products, ensuring code integrity, feasibility, and alignment with business and customer goals.
• Lead requirement analysis, contributing to low-level architecture and component design, development, unit testing, integrations, and support.
• Maintain accountability for the integrity of code design, implementation, quality, data, and ongoing maintenance and operations.
• Stay hands-on, self-driven, and continuously learn new approaches, languages, and frameworks with significant focus on infusing AI/ML/GenAI where possible/appropriate.
• Create technical specifications, and write high-quality, supportable, scalable code and review code of other engineers, mentoring them, to ensure all quality KPIs are met or exceeded.
• Develop lean engineering solutions through rapid, inexpensive experimentation to solve customer needs.
• Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time.
• Adopt a mindset that favors action and evidence over extensive planning.
• Utilize a leaning-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions.
• Work collaboratively with empowered, cross-functional teams including product management, experience, and delivery.
• Integrate diverse perspectives to make well-informed decisions that balance feasibility, viability, usability, and value.
• Possess deep expertise in modern software engineering practices and principles, including AI/ML/GenAI, Agile methodologies and DevSecOps.
• Strive to be a role model, leveraging these techniques to optimize solutioning and product delivery.
• Quickly acquire domain-specific knowledge relevant to the business or product.
• Translate business/user needs, architectures, and UX/UI designs into technical specifications and code.
• Articulate complex technical concepts clearly and compellingly.
• Inspire and influence teammates and product teams through well-structured arguments and trade-offs supported by evidence.
• Engage and collaborate with product engineering teams at all organizational levels, including customers as needed.

Requirements

• Bachelor's degree in computer science, software engineering, or related field.
• 6+ years of engineering experience focused in AI/ML.
• 2+ years of recent experience in GenAI utilizing technologies such as: OpenAI, Claude, Gemini, LangChain, Agents, Vector databases and approaches like Prompt Engineering, fine-tuning, etc.

Nice-to-haves

• 8+ years of engineering experience focused in AI/ML.
• Prior experience in quality assurance and automation-first techniques such as BDD, as well as test automation tools like, TOSCA, Selenium, Gherkin, Functionize, Testim, and AccelQ.
• Prior experience in Python, R, TensorFlow, PyTorch, Keras, Julia, ML libraries, NLP, etc.
• Prior experience in working with various forms of big data to generate synthetic data for testing purposes.
• Prior experience with cloud hyper-scalers like Azure, AWS, and GCP.
• Advanced degree (e.g., MS) in computer science, software engineering, or related field.

Benefits

• Discretionary annual incentive program based on individual and organizational performance.
• Broad range of employee benefits including professional development opportunities.