Job Opportunities API

About Tekion: Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe. Roles & Responsibilities   Generative AI & LLM Evaluation   Build automated testing suites to detect hallucinations, bias, toxicity, and prompt injection vulnerabilities across LLM-powered products   Implement automated evaluations for RAG systems measuring context relevance, groundedness, and answer faithfulness using frameworks like RAGAS or DeepEval   Design test beds to validate multi-agent workflows — tool-calling accuracy, multi-step reasoning, memory, and autonomous decision loops   Build and run automated conversation simulations — scripted and synthetic user journeys — to stress-test agent behaviour across intents, edge cases, and multi-turn dialog flows   Create prompt regression frameworks to assess how changes in system prompts, temperature, and sampling parameters impact output consistency   Data Quality Assurance   Statistically validate AI data outputs — distributions, precision/recall, error pattern analysis — to catch silent data quality failures before production   Programmatically audit data ingestion, transformation, and feature store pipelines for schema drift and data corruption   Validate vector DB indexing, embedding semantic similarity accuracy, and retrieval latency   Verify quality, diversity, and privacy compliance of synthetic datasets used for model training and evaluation   Classical ML & Deep Learning Validation   Maintain automated suites tracking ML metrics — Precision, Recall, F1, ROC-AUC — and deep learning loss curves across model versions   Implement continuous monitoring scripts to detect data and concept drift on live inference endpoints   Automation Engineering & CI/CD   Build and maintain scalable test automation frameworks for APIs, backend services, and model endpoints   Embed AI evaluation and data QA suites into MLOps and CI/CD pipelines so quality failures block releases automatically   Define and track AI quality KPIs and communicate release readiness to engineering and product teams   Experience of 5+ years SDET role  Technical Skills & Frameworks   Core Programming   Python  — expert level; test automation, eval pipelines, data analysis (Pandas, NumPy, Pytest)   SQL  — data output validation, ground truth querying, pipeline data quality checks   GenAI & Evaluation   RAGAS / TruLens / DeepEval / Promptflow  etc — LLM evaluation frameworks for measuring faithfulness, hallucination rate, and task success   LangChain / LangSmith / LlamaIndex  — agent workflow testing, prompt tracing, and LLM response debugging