Lead AI Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead AI Engineer based in the United States.

This is a high-impact opportunity to help establish and scale enterprise AI capabilities within a fast-growing technology environment.

• Design, build, test, deploy, and maintain production-grade AI-enabled applications, generative AI solutions, AI agents, tools, and enterprise workflows.
• Establish foundational AI Center of Excellence standards, reusable architectural patterns, engineering guardrails, and implementation practices.
• Contribute to an AI experimentation lab supporting rapid prototyping, evaluation, experimentation, and iterative development of emerging AI capabilities.
• Define and operationalize AI Development Lifecycle practices covering experimentation, evaluation, governance, deployment, monitoring, and continuous improvement.
• Build reusable AI platforms, services, APIs, orchestration frameworks, and service layers that can scale across enterprise use cases.
• Identify, prioritize, and deliver AI opportunities that generate measurable operational efficiencies, customer experience improvements, or revenue impact.
• Apply modern generative AI patterns including retrieval-augmented generation, prompt engineering, agent orchestration, tool/function calling, embeddings, vector search, and human-in-the-loop workflows.
• Develop AI agents and integrate enterprise applications, APIs, tools, and data sources into reliable orchestration workflows.
• Work with large and small language models, embeddings, vector databases, model APIs, and leading AI ecosystems to select appropriate technologies for each use case.
• Design secure, observable, maintainable Python-based AI services using modern architecture patterns such as microservices, APIs, and event-driven systems.
• Establish evaluation frameworks, quality benchmarks, monitoring practices, feedback loops, and observability capabilities to continuously improve AI system performance.
• Implement responsible AI, data protection, compliance, governance, and human-oversight practices throughout the AI development lifecycle.
• Partner with business and technical stakeholders to translate problems and opportunities into scalable AI solutions, taking initiatives from concept through production and expansion.
• Create technical designs, reusable frameworks, documentation, and engineering standards that improve consistency and accelerate future AI development.
• Mentor engineers in AI engineering, AI-native development, experimentation, evaluation, and modern development practices.

• Bachelor’s degree in Computer Science or equivalent professional experience.
• 8+ years of experience in cloud software engineering and/or AI engineering, including 8+ years of programming experience with Python.
• Hands-on experience building AI-enabled applications, generative AI solutions, AI agents, or production AI workflows.
• Strong experience with AWS and/or Azure and AI-native cloud services such as AWS Bedrock, AWS AgentCore, Azure AI Foundry, or Azure OpenAI.
• Deep understanding of generative AI concepts and implementation patterns, including LLM/SLM selection, RAG, prompt engineering, evaluation, agentic workflows, tool/function calling, embeddings, vector search, human-in-the-loop systems, and AI observability.
• Experience with agent frameworks and orchestration technologies such as LangGraph or Semantic Kernel.
• Experience working with major LLM ecosystems and providers, including OpenAI, Anthropic, Llama, Mistral, or comparable technologies.
• Hands-on experience with vector databases and retrieval platforms such as Pinecone or Azure AI Search.
• Experience with AI interoperability protocols and architectures, including AG-UI, A2A, MCP, registries, reusable service layers, or comparable standards.
• Strong experience integrating APIs, enterprise systems, data sources, and business applications into AI workflows.
• Solid understanding of modern software architecture, including microservices, APIs, event-driven systems, scalable services, and cloud-native development.
• Experience with Agile/Scrum methodologies and modern software delivery practices.
• Understanding of AI governance, responsible AI, data protection, privacy, security, and compliance considerations.
• Ability to translate ambiguous business challenges into practical AI solutions with measurable outcomes.
• Strong analytical, problem-solving, communication, collaboration, and stakeholder-management skills.
• Self-directed and comfortable operating in an evolving environment where AI standards and technologies are continually changing.
• Experience contributing to an AI Center of Excellence, AI platform, or AI innovation team is preferred.
• Experience defining or implementing an AI Development Lifecycle and structured Context Engineering practices is a plus.
• Familiarity with observability and evaluation tools such as OpenTelemetry, Datadog, CloudWatch, or LangSmith is preferred.