Senior Engineer, Generative AI

We are seeking a dynamic and innovative Senior Generative AI Engineer to join our team, reporting directly to Hearst’s Chief Product & AI Strategist. This role sits at the intersection of software engineering and artificial intelligence, focusing on building and deploying cutting-edge AI applications that drive business value.

Key Responsibilities:

• Design and develop Generative AI applications and features using modern LLM APIs and open-source models
• Create and optimize multi-agent systems using frameworks like LangChain and advanced RAG architectures
• Build robust systems that combine traditional software engineering with Generative AI capabilities
• Implement and maintain AI pipelines using vector databases and retrieval systems
• Develop evaluation frameworks to assess Generative AI application performance and reliability
• Collaborate with product teams to identify and implement AI-driven solutions

Requirements:

• 5+ years of software development experience with strong proficiency in Python and JavaScript
• Familiarity with containerized development (e.g. Docker) and deployment
• Exposure to one or more modern JS frameworks like React/Next/Node
• Experience with modern Generative AI development frameworks and tools (LangChain, Vector DBs)
• Demonstrated ability to work with LLM APIs (GPT-4, Claude, etc.)
• Familiarity the use of agentic software development tools like Cline and Cursor
• Strong understanding of prompt engineering and LLM capabilities
• A commitment to automated testing and software development best practices
• Strong problem solving and project management skills and ability to work with ambiguous requirements
• Excellent communication skills to explain AI capabilities and limitations to stakeholders

Advanced Skills (Nice to Have)

• Experience with complex RAG architectures incorporating graph databases
• Familiarity with agent orchestration frameworks like LangGraph or CrewAI
• Experience with LLM evaluation and monitoring tools like LangSmith
• Knowledge of advanced retrieval techniques beyond semantic search