Staff Software Engineer, Agentic SDLC Foundations

Apigee; San Jose (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Apigee seeks a senior software engineer with extensive ML design experience to lead end-to-end product development, including model deployment, evaluation, data processing, and debugging. The role involves integrating generative AI tools into workflows and driving production-ready AI systems.

The candidate should have strong leadership in shaping technical roadmaps and guiding cross-functional engineering efforts, with a track record of moving AI solutions from prototype to high-reliability

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• Experience integrating generative AI tools or LLM interfaces into workflows.

Skills

Software development

ML design

Model deployment

Data processing

Debugging

Fine tuning

Generative AI integration

Education

Bachelor’s degree or equivalent

Master’s degree or PhD in Engineering/CS

Job description

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 8 years of experience in software development.
  
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• Experience integrating generative AI tools or LLM interfaces into workflows.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 3 years of experience in a technical leadership capacity (e.g., leading technical roadmaps, designing multi-system architectures, and guiding cross-functional engineering efforts).
• Experience designing and implementing AI/ML evaluations, LLM benchmarking frameworks, or agentic quality measurement pipelines.
• Experience in prompt optimization, LLM fine-tuning, automated dataset generation, and trajectory-based evaluation methodologies.
• Experience taking generative AI solutions or autonomous agent loops from prototype to high-reliability production systems.