Architect Agentic Systems
Design and implement new features and functions across the app ecosystem in partnership with Product Managers and data engineers
Build scalable agentic AI architectures for MCP servers and multi-agent environments
Implement Advanced Retrieval Design RAG and GraphRAG pipelines to ensure agents are grounded in accurate, high-context, and real-time data
Optimize retrieval strategies for enhanced agent performance and responsiveness
Develop infrastructure that delivers seamless, responsive AI experiences for internal and external users
Integrate Salesforce technologies and open-source tools to create the enterprise agentic data foundation
Collaborate with Data Scientists to translate evaluation metrics into scalable, production-grade services
Establish frameworks to continuously measure and improve agent performance
Define and enforce coding standards, testing strategies, and best practices to maintain high-quality, high-performance systems
Produce strategic technical documentation that captures architecture, product strategy, and implementation details

Bachelor’s or Master’s degree in Computer Science, AI, Information Technology, or related fields
8+ years of proven experience as a full-stack software engineer, developing robust web and AI-enabled applications
Strong knowledge of embedding models, LLM grounding, and agentic AI skills development
Familiarity with the Salesforce ecosystem, Agentforce, and pro-code tools such as Heroku
Hands-on experience with NoSQL and Graph databases (Neo4j, MongoDB, Cassandra, Redis) and vector databases (Milvus, Pinecone)
Proficient in back-end development using Python, Java, or similar languages and server-side frameworks
Skilled in version control (Git) and CI/CD pipelines for production deployment
Ability to translate complex AI research into actionable engineering solutions
Strong problem-solving skills and the ability to think strategically about emerging AI technologies

Lead AI Engineer – Search, AI Components

Key skills