Lead AI Engineer

This is a fully remote position, open to applicants in California, +15 more states.

📋 Description

• Design, develop, test, implement, and sustain AI-driven solutions, encompassing AI agents, tools, and applications powered by GenAI.

• Set foundational standards for an AI Center of Excellence, including reusable patterns and engineering guidelines.

• Contribute to an AI laboratory focused on experimentation, prototyping, assessment, and rapid iteration.

• Define and execute practices for the AI Development Lifecycle, which includes experimentation, evaluation, governance, deployment, and monitoring.

• Create scalable and reusable AI platforms, services, APIs, and orchestration frameworks.

• Identify and implement AI use cases that enhance operational efficiency and deliver business value.

• Utilize RAG, prompt engineering, agent orchestration, tool invocation, and human-in-the-loop processes.

• Develop AI agents, integrate tools, and orchestrate workflows across enterprise systems.

• Work with LLMs, SLMs, embeddings, vector search, and model APIs.

• Produce technical designs, reusable frameworks, and implementation standards.

• Deploy secure, observable, and maintainable AI services using Python.

• Establish and adhere to AI governance protocols that include responsible AI practices, data protection, and compliance.

• Aid in the building, deployment, monitoring, and troubleshooting of AI applications.

• Create evaluation frameworks, quality standards, and feedback mechanisms.

• Collaborate with stakeholders to transform AI concepts into production and scale.

• Mentor engineers on AI engineering techniques and AI-native development.

⛳️ Requirements

• Bachelor's degree in computer science or equivalent experience.

• Over 8 years of experience in cloud software engineering and/or AI engineering.

• More than 8 years of programming experience in Python.

• Practical experience in developing AI-enabled applications, GenAI solutions, or AI agents.

• Familiarity with AWS and/or Azure, including AI-native PaaS cloud services like AWS Bedrock, AWS AgentCore, Azure AI Foundry, and Azure OpenAI.

• Strong comprehension of LLM/SLM model selection, RAG, prompt engineering and evaluation, agentic workflows, tool/function invocation, embeddings and vector search, human-in-the-loop systems, and AI observability and monitoring.

• Experience with agent frameworks and orchestration tools such as LangGraph and Semantic Kernel.

• Proficiency in LLM ecosystems and providers including OpenAI, Anthropic, Llama, and Mistral.

• Experience with vector databases and retrieval systems like Pinecone and Azure AI Search.

• Familiarity with AG-UI, A2A, and MCP interoperability protocols, registries, and reusable service layers.

• Capability to integrate APIs and enterprise systems into AI workflows.

• Comprehensive understanding of microservices, APIs, and event-driven architecture patterns.

• Experience in Agile/Scrum environments.

• Insight into AI governance, responsible AI, and compliance factors.

• Ability to translate business challenges into AI solutions.

• Strong analytical and problem-solving capabilities.

• Excellent collaboration and communication skills.

• Preferred: experience with AI Centers of Excellence, AI platforms, AI innovation teams, AI-DLC, Context Engineering, observability and evaluation tools, CI/CD, containerization, infrastructure automation, regulated environments, operational automation, customer experience, revenue-generating products, and AI governance frameworks such as ISO/IEC 42001 and NIST AI RMF.

🏝️ Benefits

• Annual performance-based bonus, commission, or other variable pay plan may be available.

• Medical benefits.

• Dental benefits.

• 401k.

• Engaging, fast-paced work environment with ample opportunities for growth.

• Commitment to diversity and inclusion.