Senior Software Engineer - AI Agentic Product Dev
Location: Santa Clara, CA
Department: Engineering
Work Location: hybrid
- Build and ship AI-powered product features using LLMs, NLP, and agent-based workflows
- Develop backend services and APIs that support model inference, orchestration, and tool execution
- Implement LLM workflows, including pipelines, retrieval (RAG) systems, and goal-oriented agent behaviors
- Work closely with Product Managers and Designers to turn AI-driven ideas into working features
- Collaborate with ML engineers to integrate, evaluate, and productionize models
- Write clean, maintainable, and well-tested code
- Participate in code reviews and contribute to technical discussion
- Help improve system performance, reliability, and scalability
- 3–5 years of professional software engineering experience
- Strong experience building backend or full-stack applications
- Proficiency in Python and at least one other language (Java, Go, or TypeScript)
- Hands-on experience integrating LLMs, NLP, or ML-powered features
- Familiarity with APIs, distributed systems, and backend services
- Understanding of prompting, embeddings, and model inference
- Solid software engineering fundamentals (testing, debugging, system design)
- Product mindset with a focus on real-world impact and usability
- Experience with agentic systems, workflows, or orchestration frameworks
- Exposure to RAG Architecture Design & Evaluation
- Familiarity with cloud platforms (AWS, GCP, or Azure)
- Experience working in AI-first or fast-moving product teams
- Experience with agentic systems, workflows, or orchestration frameworks
- Exposure to RAG architecture Design & Evaluation
- Familiarity with cloud platforms (AWS, GCP, or Azure)
- Experience working in AI-first or fast-moving product teams
- Languages & Frameworks: Python, Flask, React, Typescript, Webpack, NextJS.
- Data & Infrastructure: MySQL, Solr, Apache Airflow, Apache Spark, Docker.
- Cloud Services: Major AWS services like Aurora, S3, Redshift, Cloudformation, SNS, SQS.
- AI & ML: Extensive use of ML models and LLMs.
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