Senior Software Engineer - Fulfillment Systems & Applied AI
Uses GenAI/LLM tools and AI/ML frameworks to build automation—directly aligns with AI-assisted "vibe" coding and automation workflows.
About the Role
Senior Software Engineer role focused on architecting, building, and maintaining scalable automation and fulfillment systems using AI/ML techniques to reduce operating costs and improve process reliability. Collaborate with stakeholders to analyze workflows, integrate automation with existing infrastructure, and continuously monitor and optimize solutions.
Job Description
Role
Senior Software Engineer responsible for designing, implementing, and maintaining scalable automation solutions for fulfillment systems using AI/ML techniques. The role focuses on reducing operational expense, improving process robustness, and ensuring seamless integration with existing infrastructure.
Key Responsibilities
- Analyze manual business workflows and identify automation opportunities with stakeholders.
- Architect, design, build, test, deploy, and maintain automation systems leveraging AI/ML.
- Integrate automation solutions with existing systems and APIs (e.g., ERP, e-commerce).
- Monitor performance, troubleshoot issues, and implement enhancements for efficiency and reliability.
- Deliver solutions that reduce OPEX and improve process robustness.
- Create and maintain clear technical documentation.
- Stay current with AI/ML and automation advancements and recommend new tools and best practices.
Requirements
Required
- 5+ years of professional software development experience, including senior-level responsibilities.
- Strong programming skills in Python; experience with Java, Go, C#, or JavaScript is a plus.
- Experience applying AI/ML fundamentals to process automation and proven experience designing and deploying automation solutions.
- Familiarity or experience with NetSuite ERP and Shopify APIs is a plus.
- Strong analytical skills, systems thinking, and troubleshooting ability.
- Bachelor’s or Master’s in Computer Science, Engineering, or related field (or equivalent experience).
- Excellent communication skills and ability to work independently and collaboratively in a small team.
Preferred
- Experience with ML/DL frameworks: TensorFlow, PyTorch.
- Experience with NLP libraries: NLTK, SpaCy.
- Experience with GenAI/LLM tooling: LangChain, LangGraph, CrewAI, RAG.
- Hands-on experience with AWS, Azure, or GCP and cloud-native AI/ML services; familiarity with serverless, containers, and managed databases.
- Experience with workflow orchestration (Airflow) or agentic workflow frameworks.
- Proficiency in SQL, NoSQL, and vector databases.
- Understanding of DevOps and CI/CD pipelines and tools (Jenkins, GitLab CI, GitHub Actions, Terraform).
- Experience working in Agile/Scrum environments.