Software Development Engineer - Test

Responsibilities :

- Design and implement end-to-end quality strategies for agentic AI systems, balancing manual exploratory testing with automation frameworks.

- Develop and maintain validation frameworks for multi-agent orchestration logic, ensuring correctness in planning, decision-making, and adaptive behaviours.

- Develop and run manual and automated test pipelines to validate end-to-end functionality, data flow, and system reliability across AI services.

- Perform exploratory testing of AI reasoning, tool usage, and agent collaboration workflows to uncover edge cases and emergent behaviours.

- Automate test coverage for APIs, microservices, and orchestration components using modern testing tools and frameworks.

- Create observability and monitoring solutions to assess agent accuracy, latency, and behavioural consistency.

- Collaborate with AI and backend developers to embed quality gates and automated checks into CI/CD pipelines.

- Evaluate and integrate testing tools for AI-specific workflows (prompt validation, response benchmarking, output scoring).

- Champion best practices for reproducibility, versioning, and manual/automated validation of AI model behaviours.

- Contribute to cross-team initiatives, R& D demos, hackathons, and innovation sprints.

Requirements :

- 5+ years of experience in Quality Engineering, SDET, or Software Testing (manual and automated) in distributed or AI-driven systems.

- Strong experience designing and executing both manual exploratory tests and automated test frameworks.

- Proficient in Python, Java, or Go for developing test automation scripts and frameworks.

- Have worked on distributed systems and microservices architecture (preferred).

- Hands-on experience with API testing, microservices validation, and CI/CD integration (GitHub Actions, Jenkins, etc.).

- Experience with AI technologies and frameworks that enable intelligent agents, automation, and contextual reasoning.

- Familiarity with cloud-native testing (AWS, GCP, or Azure) and containerized environments (Docker, Kubernetes).

- Experience with observability tools (Grafana, Prometheus) to validate performance and system health.

- Strong analytical, debugging, and communication skills; able to translate complex AI behaviours into clear, testable criteria.

- Passionate about ensuring quality and trustworthiness in intelligent, autonomous systems.