Staff Software Engineer, AI
New
J
JobgetherSaaS software
Based in the United StatesFull-TimeStaff
SalaryAnnual salary range of $150,000–$190,000
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Job Details
- Experience
- 10+ years of professional software engineering experience
- Required Skills
- AWSPythonDevOpsSaaSLLM
Requirements
- 10+ years of professional software engineering experience, ideally in full-stack SaaS application development or backend engineering.
- A track record of building and deploying production-ready AI or machine learning services at scale.
- Hands-on experience with large language model frameworks, platforms, evaluation methods, and related AI tooling.
- Strong Python development skills or equivalent expertise in a modern programming stack.
- Familiarity with data manipulation and model evaluation workflows.
- Experience building scalable data infrastructure and integrating AI models into broader SaaS systems.
- Experience with AWS or an equivalent cloud environment and modern DevOps practices.
- Ability to use AI tools and technologies to improve workflows, enhance decision-making, or drive innovation.
- Ability to translate business requirements into maintainable, production-quality technical solutions.
- Ability to collaborate with engineering, product, data, and cloud operations teams.
Responsibilities
- Collaborate with product managers and business stakeholders to identify challenges and translate them into AI-driven solutions.
- Design, develop, and integrate AI features into existing SaaS products.
- Partner with data teams to collect, enrich, prepare, and provide data for AI applications.
- Build, test, and evaluate AI services from customer-facing prototypes through production-grade solutions.
- Write Python code to manipulate data, interact with large language models, and evaluate AI system performance and reliability.
- Develop tools, services, and infrastructure for secure, scalable, and dependable AI deployment.
- Work with cloud operations teams to deploy AI features, monitor performance and business impact, and optimize production systems.
- Apply AI technologies and engineering practices to improve workflows, decision-making, and product innovation.
- Provide technical leadership and engineering best practices across experimentation, evaluation, deployment, and ongoing improvement.
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