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Jonathan R.

Jonathan R.

AI & Machine Learning Engineer · Senior

United States · Rate on request

Professional Overview

Senior Software & Data Engineer with 8+ years of experience specializing in Generative AI, LLMs, Prompt Engineering, RAG, AI evaluation, model testing, and data engineering. Strong expertise in Python, SQL, cloud platforms, distributed systems, Kubernetes, Kafka, and full-stack development.

Experience

Company
Palantir
Feb 2023 – Aug 2026
Role title
Senior Software Engineer

AI Expertise

AI & Machine Learning Engineers NLP & Prompt Engineering

Skills

Python AI Agents RAG Prompt Engineering Scikit-Learn Reinforcement Learning Azure Kafka

Employment Type

Full-time

Description of Responsibilities

  • Developed Generative AI and LLM solutions using Python and RAG.
  • Designed effective prompts for LLM testing and response quality.
  • Evaluated AI models for accuracy, consistency, and instruction following.
  • Built data pipelines using Python, SQL, Spark, and Kafka.
  • Integrated AI capabilities into scalable production applications.

Key Achievements / KPIs

  • Improved LLM response quality through optimized prompt engineering.
  • Reduced AI evaluation time through automated testing pipelines.
  • Built scalable RAG workflows for accurate, context-aware AI responses.
  • Improved data processing efficiency using Python, Spark, and Kafka.
Company
Palantir
Feb 2023 – Aug 2026
Role title
Senior Software Engineer

AI Expertise

AI & Machine Learning Engineers NLP & Prompt Engineering

Skills

Python AI Agents RAG Prompt Engineering Scikit-Learn Reinforcement Learning Azure Kafka

Employment Type

Full-time

Description of Responsibilities

  • Developed Generative AI and LLM solutions using Python and RAG.
  • Designed effective prompts for LLM testing and response quality.
  • Evaluated AI models for accuracy, consistency, and instruction following.
  • Built data pipelines using Python, SQL, Spark, and Kafka.
  • Integrated AI capabilities into scalable production applications.

Key Achievements / KPIs

  • Improved LLM response quality through optimized prompt engineering.
  • Reduced AI evaluation time through automated testing pipelines.
  • Built scalable RAG workflows for accurate, context-aware AI responses.
  • Improved data processing efficiency using Python, Spark, and Kafka.

Education

School
MacMurray College
Sep 2012 – May 2016
Degree / Program
Bachelor of Science in Computer Engineering

Field of Study: Computer Engineering

Areas of Expertise

AI & Machine Learning Engineers

Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.

NLP & Prompt Engineering

Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.

Data Science & Analytics

Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.

Automation & AI Workflows

Build intelligent automation pipelines, integrate AI APIs into existing tools, and replace manual workflows with agentic AI systems.

Open to

Full-time

Skills

Python PyTorch NumPy Scikit-Learn Reinforcement Learning Snowflake ai agents Prompt Engineering RAG llm fine-tuning

Experience Level

Senior

Current location

United States

Time Zone

Anchorage UTC-9

Primary Work Language

English

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