
QA & Application Testing & Automation Engineer
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DeepLight AI is a specialist AI and data consultancy with extensive experience implementing intelligent enterprise systems across multiple industries, with particular depth in financial services and banking. Our team combines deep expertise in data science, statistical modeling, AI/ML technologies, workflow automation, and systems integration with a practical understanding of complex business operations.
The QA & Application Testing & Automation Engineer is responsible for the quality, resilience, and performance of the Bankās digital and core operational platforms. This role goes beyond traditional testing, focusing on the end-to-end validation of next-generation AI systems, mobile applications, and enterprise services. By building sophisticated automated frameworks and continuous testing pipelines, you will ensure that every releaseāfrom Conversational AI agents to core banking microservicesāmeets the highest standards of security, scalability, and reliability. You will act as a quality gatekeeper, collaborating across engineering and cybersecurity teams to accelerate deployment without compromising the Bank's integrity.
Your responsibilities within this role include:
⢠Validate next-gen AI platforms (voice and chat) for accuracy, stability, latency, and safety; ensure AI-driven enterprise search avoids hallucinations.
⢠Build and maintain reusable automation frameworks for web, mobile, and API integrations using Python, Selenium, or Playwright.
⢠Validate RAG (Retrieval-Augmented Generation) pipelines, vector search quality, and grounding accuracy to ensure data retrieval performance.
⢠Implement automated quality checks for MLOps, including drift detection, retraining validation, and model registry integrity.
⢠Conduct scenario-based testing for operational AI agents (KYC, Risk, Compliance) and validate high availability and disaster recovery protocols.
⢠Integrate automated quality gates into CI/CD pipelines to ensure continuous validation within containerized (Docker/Kubernetes) environments.
⢠Verify that all AI engineering aligns with guardrails for fairness, security, explainability, and regulatory requirements.As an AI consultancy, our greatest asset is the expertise of our people.
While technical mastery is the foundation of what we do, the ability to bridge the gap between complex data science and actionable business value is what defines your success with Deeplight.
We're looking for individuals who are not only world-class in their fields of specialism, but also compelling communicators and persuasive advocates for their own skills.
You will be the face of our firm, tasked with building trust, articulating the "why" behind your technical decisions, and effectively "selling" your vision to high-level stakeholders.
If you thrive on the challenge of presenting cutting-edge solutions as much as you do on building them, you will fit right in.
Requirements
We need you to have:
⢠A Bachelorās degree in Computer Science, AI, Software Engineering, or a related quantitative field. A Masterās degree in AI/ML is highly preferred.
⢠A minimum 5+ years in QA and Automation, preferably within a large-scale digital bank or a major digital transformation project.
⢠Proven experience deploying AI/ML QA solutions at an enterprise scale, specifically in banking or financial services.
⢠Deep knowledge of software testing methodologies (Functional, Regression, Security, and Non-functional).
⢠Proficiency in Python for test automation and expertise with tools like PyTest, Selenium, Playwright, and Postman.
⢠Hands-on experience testing LLM response quality, prompt stability, and agentic orchestration workflows.
⢠Strong experience validating pipelines and storage services across Azure (AI Foundry) and AWS (SageMaker).
⢠Proficiency in load and stress testing using tools like JMeter or Locust.
⢠Expertise in SQL and NoSQL test validation (Postgres, MongoDB, Cassandra) and data platform integrity.It would be beneficial if you also have:
⢠The ability to evaluate and integrate emerging AI testing tools such as LangChain, CrewAI, or Bedrock.
⢠Experience at acting as an "analytics translator" between technical teams and business stakeholders regarding quality risks.
⢠An understanding of cybersecurity principles in the context of AI safety and prompt injection prevention.
⢠A proven ability to work within fast-paced squads to remove blockers and manage dependencies.Benefits
Benefits & Growth Opportunities:
⢠Competitive salary.
⢠Visa Sponsorship for the successful individual.
⢠Comprehensive health insurance for the successful individual.
⢠Professional development and certification support.
⢠Opportunity to work on cutting-edge AI projects.
⢠Career advancement opportunities in a rapidly growing AI company.This position offers a unique opportunity to shape the future of AI implementation while working with a talented team of professionals at the forefront of technological innovation. The successful candidate will play a crucial role in driving our company's success in delivering transformative AI solutions to our clients.
At DeepLight AI, we recognise that diversity drives innovation. We are committed to fostering an inclusive environment where individuals with different thinking styles can thrive and contribute their unique strengths to our specialised AI and data solutions.
Our goal is to ensure our application and interview process is accessible, predictable, and fair for all candidates.
If you require any specific adjustments to the application process, or if you require any reasonable adjustments should you be successful in being processed to the interview stage, please do let us know. This information will be kept strictly confidential and will not impact hiring decisions.
Requirements
- ā¢Bachelorās degree in Computer Science, AI, Software Engineering, or a related field
- ā¢Experience building and maintaining reusable automation frameworks
- ā¢Proficiency in Python, Selenium, or Playwright
- ā¢Experience with MLOps, including drift detection and retraining validation
- ā¢Experience with CI/CD pipelines
- ā¢Experience with Docker/Kubernetes
- ā¢Understanding of AI guardrails (fairness, security, explainability)
- ā¢Strong communication and presentation skills
Nice to Have
- ā¢Expertise in data science, statistical modeling, AI/ML technologies
- ā¢Experience in financial services and banking
- ā¢Ability to articulate technical decisions and sell a vision to stakeholders
Responsibilities
- ā¢Validate next-gen AI platforms (voice and chat) for accuracy, stability, latency, and safety
- ā¢Build and maintain reusable automation frameworks for web, mobile, and API integrations
- ā¢Validate RAG pipelines, vector search quality, and grounding accuracy
- ā¢Implement automated quality checks for MLOps
- ā¢Conduct scenario-based testing for operational AI agents (KYC, Risk, Compliance)
- ā¢Validate high availability and disaster recovery protocols
- ā¢Integrate automated quality gates into CI/CD pipelines
- ā¢Verify AI engineering aligns with guardrails for fairness, security, explainability, and regulatory requirements
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