Early Career Software Engineer – Applied AI
Early career software engineer builds and integrates AI agents and solutions using frameworks like LangChain and RAG pipelines to enhance childcare platform features. Requires bachelor's in CS/engineering, Python/JS proficiency, and AI/ML familiarity; hybrid onsite in SF office 3 days/week.
About the job
Key Responsibilities
- Design, develop, and maintain robust software solutions with a focus on integrating AI capabilities.
- Collaborate with product managers, designers, and engineers to define requirements and implement innovative features.
- Design and Development of AI Agents: Build modular, task-specific AI agents capable of natural language understanding, dialogue management, and action execution using frameworks such as LangChain or Rasa.
- Debug and troubleshoot technical issues to ensure platform stability.
- Stay current with emerging technologies and best practices in software engineering and AI.
Required Qualifications
- Bachelor’s degree in Computer Science, Engineering, or related field.
- Strong foundation in programming languages (Python, JavaScript, or TypeScript).
- Familiarity with AI/ML concepts and frameworks (TensorFlow, PyTorch, Scikit-learn).
- Basic understanding of cloud platforms like Google Cloud Platform and AWS.
- Excellent communication skills and ability to work in a collaborative, in-person environment.
Nice-to-Have Skills
- Strong understanding of machine learning principles, including model development, evaluation, and deployment for real-world applications.
- Retrieval-Augmented Generation (RAG) Pipelines: Design and deploy RAG pipelines by integrating retrievers with generative models to enable contextual, real-time responses using vectorized knowledge bases.
- Continuous Learning: Incorporate user feedback loops and data augmentation techniques to iteratively improve the performance and relevance of AI agents and RAG pipelines.
Compensation
- Expected salary range: $100K–$120K annually, based on experience and location.
Skills
Python, JavaScript, TypeScript, TensorFlow, PyTorch, scikit-learn, GCP, AWS, LangChain, Rasa
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