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About This Role
For decades, DTN has been the silent force behind some of the world’s most critical industries—helping businesses navigate complexity, uncertainty, and risk with smarter, faster decisions. From agriculture to energy to weather intelligence, our proprietary Operational Decisioning Platform transforms raw data into decision\-grade insights—enabling companies to optimize supply chains, ensure market stability, and safeguard infrastructure against disruption. We don’t follow trends—we set the standard for precision, trust, and operational impact.
DTN is at an exciting inflection point. Building off a foundation of financial strength, profitability, and industry trust, we’re accelerating growth and expanding our global footprint. Our purpose\-built solutions—powered by AI and honed by decades of vertical expertise—are helping some of the world’s most significant enterprises thrive amid operational constraints and uncover new opportunities in a fast\-changing world.
J ob Description:
The DTN Information Hub (DIH) is a bold new initiative designed to transform how we deliver value to our customers across agriculture, weather, and energy. Our mission is to build advanced AI a gents that leverage DTN's trusted data and deep industry expertise to provide customers with actionable insights, informed recommendations, and enhanced decision support.
As a Software Engineer on the AI Core Team, you'll be at the heart of this mission — designing and building the agentic systems, LLM\-powered workflows, and intelligent infrastructure that power the next generation of DTN products.
What you’ll be responsible for :
- 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.
What you will bring to this role:
- 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.
- Bonus Skills: 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.
What you can expect from DTN:
- Competitive Salary
- Generous PTO
- Flexible work arrangements
- C ompetitive Medical, Dental and Vision Insurance Plans
- 6% 401K matching
- Unlimited access to 13k\+ courses via learning platform to support employee career advancement
- Employee Assistance Program (EAP)
Compensation
*The targeted hiring base pay range for this position is between* *$101,000 and $124,000* *. DTN is a pay for performance organization, which means there is the opportunity to advance your compensation with performance over time. The actual base pay offered for this position will be dependent upon many factors, including but not limited to: prior work experience, training/education, transferable skills, business needs, internal equity and applicable laws. The targeted hiring base pay range is subject to change and may be modified in the future. This role may also be eligible for market competitive variable pay and benefits.*
\#LI\-Engineering
\#LI\-AI
\#LI\-REMOTE
\#LI\-HYBRID
\#LI\-TH1
About DTN:
DTN is a global data and technology company helping operational leaders in energy, agriculture, and weather\-driven industries make faster, smarter decisions. Our Operational Decisioning Platform turns complex data into decision\-grade insights—empowering customers to expand their margins, accelerate growth, and outpace risk. With more than 1,200 employees globally, DTN serves the companies that feed, fuel, and protect the world.
At DTN, we value clarity, trust , and action . We’re a team of problem\-solvers, outcome\-drivers, and industry nerds who believe that precision matters – and that mission is at the core of what we do.
- Trust Built: We earn it. We keep it. We protect it. Our neutrality, precision, and integrity are non\-negotiable.
- Confidence\-Driven: We help customers move with clarity and conviction. We bring the data and operational knowledge leaders need to act.
- Built for Industry: We speak operations because we come from operations. Our expertise is forged in fuel terminals, fields, flight paths, and forecasts.
- Future\-Forward: We see what’s coming\- and we’re ready. We help customers lead through change with smarter decisioning.
Recruitment Fraud Notice:
DTN is aware of incidents where external parties have impersonated our organization, issuing fraudulent communications and/or job offers. Please be advised that all legitimate communication from DTN will come from an official @dtn.com email address or through our Paradox AI automated scheduling platform (Talent IQ). Any offers are extended directly by our Talent Acquisition team following a formal interview process.
If you receive a suspicious message or offer claiming to be from DTN, please do not engage. Contact our Talent Acquisition team at Careers@dtn.com to verify the legitimacy of any communication. Report any fraudulent messaging as phishing or spam.
DTN is an Equal Opportunity Employer. We welcome and encourage applicants of all backgrounds, including minorities, women, veterans, and individuals with disabilities.
Salary Context
This $101K-$124K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $189K across 518 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 26,159 AI roles we're tracking, AI Software Engineer positions make up 2% of the market. At DTN, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $235,100 based on 665 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300. This role's midpoint ($112K) sits 52% below the category median. Disclosed range: $101K to $124K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
DTN AI Hiring
DTN has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Austin, TX, US. Compensation range: $124K - $124K.
Location Context
AI roles in Austin pay a median of $212,800 across 317 tracked positions. That's 16% above the national median.
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (2,416) are outnumbered by mid-level (16,247) and senior (5,153) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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