AI Core Software Engineer

DTN is a global data and technology company that empowers operational leaders in energy, agriculture, and weather-driven industries to make faster, smarter decisions. As an AI Core Software Engineer, you will design and build advanced AI systems that provide actionable insights and enhance decision support for customers across various sectors.

Responsibilities:

• Design, build, and maintain agentic AI pipelines and workflows that automate complex, multi-step reasoning and decision support tasks
• Integrate and fine-tune large language models (LLMs), including prompt engineering, model evaluation, and iterative improvement
• Develop and optimize Retrieval-Augmented Generation (RAG) systems that ground AI outputs in DTN's trusted data and domain knowledge
• Build and maintain AI platform infrastructure and observability tooling — including logging, monitoring, tracing, and evaluation frameworks for AI systems in production
• Leverage AWS services, including Amazon Bedrock AgentCore and Strands Agents, to architect scalable, reliable AI solutions
• Collaborate cross-functionally with product managers, domain experts, and fellow engineers to translate complex business needs into AI-powered solutions
• Contribute to a culture of engineering excellence through code reviews, documentation, and knowledge sharing

Requirements:

• 3+ years of software engineering experience with a solid grasp of software fundamentals: APIs, testing, version control, and CI/CD
• A solid foundation in Python and JavaScript, with developing skills in full-stack development using Node.js, Next.js, React, and TypeScript
• Hands-on experience with AI frameworks and tooling (e.g., LangChain, Claude SDK, OpenAI APIs, Amazon Bedrock AgentCore)
• Experience building or working with RAG pipelines, vector databases, or semantic search systems; as well as knowledge of prompt engineering and model evaluation techniques
• Working knowledge of AWS cloud services
• Excellent written and verbal communication skills — ability to explain complex AI concepts to non-technical stakeholders
• 4-year degree in Computer Science, Software Engineering, or a related field
• AI/ML certifications (e.g., AWS Certified Machine Learning, Google Professional ML Engineer, Coursera/DeepLearning.AI specializations)
• Experience or interest in agriculture, weather, or energy industry domains