AI Data Solutions Engineer

Work Schedule

Environmental Conditions

Job Description

Position Summary
As part of the Thermo Fisher Scientific Corporate Digital team youll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life every day by enabling customers to make the world healthier cleaner and safer. The Corporate Digital team is seeking an innovative technically skilled and solutions-oriented AI Solutions Engineer to accelerate the adoption of generative AI across Sales and Marketing. This role combines applied data science AI engineering and advanced analytics to evaluate AI solutions assess enterprise data readiness and develop AI-enabled data products that improve business outcomes. Working closely with business stakeholders product managers and technical teams you will evaluate large language model (LLM) applications OpenAI agents to ensure they deliver accurate relevant and measurable business value. You will assess and prepare enterprise Sales and Marketing data for AI consumption by improving data quality governance structure and accessibility while delivering insights that support strategic decision-making.

Primary Responsibilities
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.
Minimum Qualifications
Bachelors degree in Computer Science Data Science Statistics Mathematics Engineering Information Systems or related quantitative field with 4 years of relevant experience or Masters 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.
Preferred Qualifications
Experience evaluating LLMs and AI agents.
Experience developing AI evaluation frameworks and performance metrics.
Experience with Sales Marketing CRM customer engagement or digital analytics data.
Experience with Power BI or Tableau.
Knowledge of prompt engineering semantic search vector databases or knowledge management.
Experience with Git or other version control systems.
Exposure to relational and graph database design.
Familiarity with graph databases such as Neo4j or Amazon Neptune.
Understanding of graph theory concepts including centrality metrics and semantic clustering.
Why This Role Matters
The AI Solutions Engineer plays a key role in advancing Thermo Fisher Scientifics enterprise AI strategy by ensuring AI applications are trustworthy measurable and supported by high-quality enterprise data. This role bridges business data and AI by evaluating AI solutions improving AI data readiness and delivering actionable insights that accelerate innovation across Sales and Marketing.