About the Role:
We are looking for an AI-First Software Engineer to help us build faster, smarter, and more scalable software for the agriculture industry.
This role is for a hands-on engineer who is excited about using modern AI tools across the software development lifecycle — from discovery and prototyping to implementation, testing, documentation, and code review. You should be comfortable moving quickly, learning new tools, and turning ambiguous product problems into high-quality software.
You do not need to be a machine learning researcher. This is a product engineering role. We are looking for someone who can use AI to dramatically increase engineering velocity while still maintaining strong judgment around correctness, maintainability, security, and user experience.
You will work closely with Product, Design, Engineering, and business stakeholders to ship customer-facing features, internal platform improvements, and AI-enabled product capabilities that help Seso serve farms and agricultural workers at scale.
Responsibilities:
Product Engineering
- Build, test, ship, and maintain high-quality software across Seso’s platform
- Work with Product and Design to turn customer and business problems into simple, reliable product experiences
- Contribute across the stack, including frontend, backend, APIs, databases, integrations, and cloud infrastructure
- Write clean, maintainable code and participate in thoughtful code reviews
- Improve existing systems by reducing complexity, improving performance, and increasing reliability
AI-First Development
- Use modern AI tools to improve your own engineering speed and quality across coding, debugging, testing, documentation, refactoring, and technical exploration
- Experiment with tools such as Cursor, Claude, ChatGPT, GitHub Copilot, Codex-style agents, or other AI development environments
- Create effective prompts, workflows, and review practices that help you produce better software faster
- Use AI responsibly — validating outputs, checking edge cases, writing tests, and ensuring generated code meets Seso’s standards
- Help the engineering team learn practical ways to use AI tools without compromising quality, security, or maintainability
AI-Enabled Product Capabilities
- Help design and build product features that use LLMs, agents, structured data extraction, summarization, recommendations, search, classification, document understanding, or other AI-enabled capabilities
- Integrate with AI APIs and platforms such as OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, or similar tools
- Evaluate AI-generated outputs for accuracy, reliability, cost, latency, safety, and user impact
- Collaborate with Product and Engineering to decide when AI is the right solution — and when traditional software is better
Technical Quality
- Write tests and evaluation workflows that help ensure software and AI-enabled features behave reliably
- Contribute to CI/CD, observability, logging, monitoring, and incident prevention
- Think carefully about privacy, security, permissions, and data handling
- Document technical decisions clearly so future teammates can understand and maintain your work
Collaboration
- Work closely with teammates across Engineering, Product, Design, Customer Experience, and other business functions
- Communicate clearly in both English and Spanish
- Bring high agency, curiosity, and a bias toward action
- Ask good questions, challenge assumptions respectfully, and help the team move faster without cutting corners
Skillset:
- 3+ years of professional software engineering experience, or equivalent experience building and shipping production software
- Strong experience with at least one backend or full-stack programming language such as Python, TypeScript, JavaScript, C#, Java, Go, or Ruby
- Experience building web applications, APIs, data models, integrations, and production services
- Hands-on experience using AI development tools such as Cursor, GitHub Copilot, Claude, ChatGPT, Codex-style agents, or similar tools
- Strong understanding of how to review, test, and validate AI-generated code
- Comfort working with cloud platforms such as AWS, Azure, or GCP
- Familiarity with modern software engineering practices, including version control, CI/CD, testing, observability, and code review
- Interest in LLMs, agents, RAG, prompt engineering, tool/function calling, AI evals, or AI-assisted product development
- Strong product judgment and ability to translate ambiguous requirements into practical technical solutions
- High attention to detail and strong ownership of outcomes
- Excellent written and verbal communication skills