AI Software Engineer
$115,000–$145,000 year
RemoteUnited States
Job Summary
Design, build, and maintain LLM-powered and agentic workflows using LangGraph, LangChain, and AWS Bedrock AgentCore, including tool use, retrieval, memory, and multi-step reasoning pipelines. Develop and productionize AI/ML services in Python with Mixture-of-Experts architectures, while building backend services, APIs in Django, and front-end features in TypeScript and Vue.js. Implement data processing pipelines to ingest, clean, and normalize large volumes of geospatial and agronomic data, then deploy and scale these services on AWS. Execute QA/QC processes for software and data to ensure model outputs meet accuracy and auditability standards, and partner with data scientists and product stakeholders to translate requirements into production systems.
Required Qualifications
- 2–5 years of professional software development experience building and shipping production systems
- Strong proficiency in Python, including experience with modern application frameworks, testing, and packaging practices
- Demonstrated experience building applications or services that use large language models or other machine learning models in production
- Working knowledge of relational databases and SQL, with practical experience designing schemas and writing performant queries
- Experience developing and consuming RESTful APIs
- Familiarity with cloud infrastructure (AWS preferred) and standard software delivery practices including version control, CI/CD, and automated testing
- Ability to work independently on ambiguous problems, and to communicate technical trade-offs clearly to both technical and non-technical colleagues
- Bachelor's degree in Computer Science, Software Engineering, a related technical field, or equivalent practical experience
- Only applicants currently eligible to work in the United States
Desired Qualifications
- AI frameworks — Building agentic and LLM applications with tools like Amazon Bedrock, LangGraph and LangChain
- Model architecture — Familiarity with Mixture-of-Experts (MoE) architectures, model routing, and ensemble or multi-model system design
- Backend — Production experience with Python and the Django framework
- Frontend — Proficiency with TypeScript, JavaScript, and Vue.js
- Data storage — Advanced PostgreSQL experience, including performance tuning and the PostGIS extension
- Geospatial — Experience with geospatial data formats, coordinate systems, raster and vector processing, satellite or remote sensing imagery, and libraries such as GDAL, rasterio, GeoPandas, or Shapely
- Data processing — Building large-scale ETL/ELT pipelines, batch and streaming workflows, and orchestration tooling
- AWS — Depth across services such as Lambda, S3, ECS/Fargate, RDS, Batch, SQS/SNS, Step Functions, and IAM
- Integrations — Designing and maintaining robust third-party and partner API integrations
- QA/QC — Establishing automated quality assurance and quality control processes for software, data, and model outputs
- Domain — Prior work in agriculture, agronomy, remote sensing, climate, energy, or environmental markets
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.