Artificial Intelligence Engineer

Senior AI Engineer / AI Platform Engineer Location: New York City — Hybrid Compensation: $200,000–$250,000 base + bonus Experience: 8+ years The Role We are looking for a senior, hands-on AI Engineer / AI Platform Engineer to build an enterprise AI platform and agentic ecosystem from the ground up. This is not a role focused solely on experimenting with models or building proofs of concept. You will own the architecture and development of production-grade AI systems, including AI agents, LLM applications, MCP-based integrations, and the cloud infrastructure required to support them at scale. The ideal candidate is a strong Python engineer with deep AWS or Azure experience who has built and deployed AI/ML or GenAI solutions into production. You should be comfortable operating in a greenfield environment, making architectural decisions, writing code, and establishing the standards that future AI development will follow. Responsibilities Architect and build the organization's AI/GenAI platform from the ground up, taking projects from initial design through production. Design and develop AI agents and multi-agent workflows capable of reasoning, executing tasks, and interacting with enterprise systems. Build production-grade applications and services primarily using Python. Implement and expand Model Context Protocol (MCP) servers and integrations to securely connect AI agents with internal tools, applications, APIs, and data sources. Develop LLM-powered applications using techniques such as RAG, tool/function calling, structured outputs, embeddings, and vector search. Build orchestration frameworks for agent workflows, memory, context management, evaluation, and observability. Design scalable AI infrastructure within AWS or Azure, including compute, storage, networking, security, identity, and deployment architecture. Integrate commercial and open-source LLMs into enterprise applications. Establish standards around LLMOps/MLOps, CI/CD, testing, monitoring, model evaluation, security, and governance. Partner with engineering, data, security, and business stakeholders to identify high-value AI use cases and turn them into production solutions. Evaluate emerging AI frameworks and technologies and determine what should be incorporated into the platform. Qualifications 8+ years of software engineering, platform engineering, ML engineering, or related experience. Advanced development experience with Python and building production-grade backend systems and APIs. Strong hands-on experience with AWS or Azure in an enterprise environment. Demonstrated experience building and deploying Generative AI / LLM applications into production. Experience developing AI agents, agentic workflows, or autonomous systems. Hands-on knowledge of Model Context Protocol (MCP) and tool-based LLM integrations. Experience with frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar technologies. Strong understanding of RAG architectures, vector databases, embeddings, prompt engineering, and LLM evaluation. Experience working with models/platforms such as OpenAI, Anthropic Claude, Azure OpenAI, AWS Bedrock, or open-source LLMs. Strong understanding of APIs, microservices, distributed systems, containers, and modern cloud architecture. Experience with Docker, Kubernetes, Terraform, and CI/CD is highly desirable. Ability to operate successfully in a greenfield environment where architecture, tooling, standards, and development practices are still being established. What We're Looking For Someone who is fundamentally a builder. You should be excited by the opportunity to walk into an environment where the AI platform is not already established and take ownership of building it. You'll have significant influence over the architecture, technology stack, agent framework, MCP strategy, cloud infrastructure, and engineering standards that shape how AI is used across the organization. Show more Show less