AI Data Solutions Engineer

Thermo Fisher Scientific — Bangalore, India

• Evaluate generative AI agents, copilots, and LLM-based applications for accuracy, relevance, consistency, and business value. • Develop AI evaluation methodologies, benchmarks, scorecards, and success metrics. • Perform qualitative and quantitative assessments of AI-generated responses and recommend improvements. • Partner with AI developers to improve prompts, retrieval quality, and overall AI performance. • Assess enterprise Sales and Marketing data for AI readiness, including quality, governance, metadata, and usability. • Prepare structured and unstructured data to support AI, analytics, and intelligent search. • Design scalable datasets and data models that improve AI retrieval and business insights. • Analyze Sales and Marketing data to identify trends and actionable recommendations. • Develop dashboards, reporting, and analytical models using Python, SQL, Databricks, and Power BI. • Collaborate with business and technical stakeholders to translate requirements into AI-enabled solutions. • Document evaluation methodologies, data standards, and best practices. • Evaluate emerging AI technologies and recommend improvements to enterprise AI capabilities. • Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Information Systems, or related quantitative field with 4+ years of relevant experience, or Master's degree with 2+ years of experience. • Strong proficiency in Python, SQL, Databricks, and PySpark. • Experience evaluating AI, machine learning, or advanced analytics solutions. • Experience preparing enterprise data for AI and analytics use cases. • Experience with Azure, AWS, or similar cloud platforms. • Strong analytical, statistical, and problem-solving skills. • Excellent communication skills and experience working in cross-functional environments. • Experience evaluating LLMs and AI agents. • Experience developing AI evaluation frameworks and performance metrics. • Experience with Sales, Marketing, CRM, customer en

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