Posted over 30 days ago. Roles like this often stay open for a while, so it's still worth applying.
GenAI Engineer – Test Agent & CI at Turing
posted 5 months agoGenAI Engineer – Test Agent / CI Integration | Full-Time | Gurugram, India (Hybrid)
Join a forward-thinking team building intelligent, AI-powered testing systems for next-generation applications. This is a specialized role focused on automated test-agent frameworks, LLM evaluation, synthetic data generation, and CI/CD-integrated AI testing pipelines — not a general GenAI developer position.
Key Responsibilities
AI Test Agent Development
- Design and develop autonomous AI-driven test agents for validating GenAI and LLM-powered applications
- Build systems for synthetic data generation, test-case synthesis, scenario generation, and adversarial/edge-case testing
- Develop reusable evaluation harnesses for benchmarking model quality, accuracy, safety, and reliability
Context-Aware Test Generation
- Integrate test agents with knowledge/context graphs for retrieval-grounded testing
- Enable contextual test generation using RAG pipelines and graph-based retrieval systems
- Ensure generated tests align with enterprise knowledge sources and real-world workflows
CI/CD & Automation
- Integrate AI test agents into CI/CD pipelines as first-class pipeline jobs
- Automate regression testing, evaluation runs, and quality scoring during deployments
- Build scalable validation workflows for continuous model monitoring and release gating
Evaluation Frameworks & Quality Engineering
- Work with LLM evaluation frameworks including DeepEval, Ragas, and custom evaluators
- Develop automated scoring for hallucination detection, faithfulness, relevance, toxicity, and response quality
- Integrate with pytest and existing QA ecosystems
Backend & Infrastructure
- Build and maintain Python backend services powering evaluation workflows
- Optimize distributed evaluation execution for scalability and performance
- Collaborate with platform, MLOps, and DevOps teams for production deployment
Required Skills & Qualifications
- 4–8 years of experience in relevant engineering roles
- Strong proficiency in Python, pytest, REST APIs, and backend development
- Hands-on experience with CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI, etc.)
- Experience with LLM evaluation frameworks (DeepEval, Ragas, LangSmith, or custom evaluators)
- Solid understanding of RAG systems, retrieval pipelines, and synthetic dataset generation
- Familiarity with vector databases, embeddings, and knowledge graphs
- Experience integrating AI workflows into CI/CD environments with automated quality gates
Preferred Qualifications
- Experience with knowledge graphs or graph databases
- Exposure to LangChain, LlamaIndex, or similar orchestration frameworks
- Familiarity with Kubernetes, Docker, and cloud platforms (AWS/GCP/Azure)
- Background in enterprise-scale AI platform engineering
This is a niche, high-impact role. Ideal candidates bring a unique blend of AI validation, QE automation, Python backend development, and LLM evaluation expertise.