Software Engineer

Software EngineerOnsite in Foster City, CA | 5 days in officeCore Responsibilities• Design and develop AI agents and autonomous systems capable of complex task execution anddecision-making• Build conversational AI solutions including chatbots and voice-based customer service systems• Create AI-powered application integrations across platforms and services• Develop and optimize Retrieval-Augmented Generation (RAG) systems for enhanced AI applicationperformance• Implement and optimize machine learning models using PyTorch• Evaluate and deploy appropriate LLMs based on specific needs—balancing accuracy, latency, cost, anduser experience• Collaborate with cross-functional teams to translate business requirements into technical AI solutions• Architect and maintain production-grade AI solutions with focus on scalability, reliability, and performanceQualifications• 6+ years Proficiency in Python for AI/ML development• 6+ years Experience with PyTorch (or willingness to learn for entry-level candidates)• Understanding of AI agents and their application to real-world problems• Hands-on experience or strong interest in building chatbots and/or voice-based conversational systems• Knowledge of RAG system components: vector databases, embeddings, retrieval strategies, and promptengineering• Familiarity with major LLM providers (OpenAI, Anthropic, Google, Meta, etc.) and understanding of theirtrade-offs in terms of performance, cost, latency, and capabilities• Understanding of transformer neural network architecture and attention mechanisms• 6+ years Experience integrating AI capabilities into applications or eagerness to learn applicationdevelopmentBonus Qualifications• Proficiency in Kotlin programming• Full-stack development experience with both backend and frontend technologies• Cloud software development experience, especially microservices architecture and integration• Experience with REST APIs, gRPC, and/or Kafka for service communication and event-drivenarchitectures• Knowledge of cloud platforms (AWS, GCP, Azure) for AI deployment• Familiarity with containerization and orchestration (Docker, Kubernetes)• Experience with AI frameworks like LangChain, LlamaIndex, AutoGen, or similar tools• Understanding of CI/CD pipelines and DevOps practice