Lead AI Engineer - GenAI Platform & CoE Architect

Accurate Background; United States; Remote; USD 121,000 - 185,000; Full time

Job summary

Accurate Background seeks a Lead AI Engineer to establish and scale AI capabilities within a new team focused on reusable AI platforms, AI governance, and production-ready AI solutions. This role drives the AI Development Lifecycle and orchestrates AI patterns across enterprise systems.

You will mentor engineers, work with LLMs/embeddings, tool calling, and end-to-end AI services, delivering measurable business value while advancing governance and compliance in a fast-paced setting.

Qualifications

• Bachelor's degree in computer science or equivalent experience.
• 8+ years of cloud software or AI engineering experience.
• 8+ years of Python programming.
• Hands-on experience building AI-enabled applications, GenAI solutions, or AI agents.
• Experience with AWS and/or Azure, including AI-native PaaS cloud services (e.g., AWS Bedrock, AWS AgentCore, Azure AI Foundry, Azure OpenAI).
• Strong understanding of GenAI patterns: LLM/SLM model selection, Retrieval-Augmented Generation (RAG), Prompt engineering and evaluation, Agentic workflows, Tool/function calling, Embeddings and vector search, Human-in-the-loop systems, AI observability and monitoring.
• Experience with agent frameworks and orchestration tools (LangGraph, Semantic Kernel etc.).
• Experience with LLM ecosystems and providers (OpenAI, Anthropic, Llama, Mistral, etc.).
• Experience with vector databases and retrieval systems (Pinecone, Azure AI Search, etc.).
• Experience with tool/agent AG-UI, A2A, MCP interoperability protocols, registries, and reusable service layers.
• Experience integrating APIs and enterprise systems into AI workflows.
• Solid understanding of modern architecture patterns (microservices, APIs, event-driven systems).
• Experience working in Agile/Scrum environments.
• Understanding AI governance, responsible AI, and compliance considerations.
• Ability to translate business problems into AI solutions.
• Strong analytical and problem-solving skills.
• Self-starter with strong collaboration and communication skills.

Responsibilities

• Design, build, test, deploy, and maintain AI-enabled solutions including AI agents, tools, and GenAI-powered applications.
• Establish foundational AI CoE standards, reusable patterns, and engineering guardrails.
• Contribute to development of an AI lab for experimentation, prototyping, evaluation, and rapid iteration.
• Define and implement AI‑DLC practices including experimentation, evaluation, governance, deployment, and monitoring.
• Build reusable and scalable AI platforms, services, APIs, and orchestration patterns.
• Identify and deliver AI use cases that drive operational efficiencies and business value.
• Apply GenAI patterns such as RAG, prompt engineering, agent orchestration, tool calling, and human-in-the-loop workflows.
• Develop AI agents, tool integrations, and orchestration workflows across enterprise systems.
• Work with LLMs, SLMs, embeddings, vector search, and model APIs.
• Create technical designs, reusable frameworks, and implementation standards.
• Implement secure, observable, and maintainable Python-based AI services.
• Establish and follow AI governance practices including responsible AI, data protection, and compliance.
• Support build, deployment, monitoring, and troubleshooting of AI applications.
• Develop evaluation frameworks, quality benchmarks, and feedback loops.
• Partner with stakeholders to move AI ideas from concept through production and scale.
• Mentor engineers on AI engineering practices and AI-native development.

Skills

Python

Cloud engineering

AI engineering

GenAI patterns

LLM/SLM

AWS/Azure

AI governance

Agent frameworks

Observability

CI/CD

Education

Bachelor's degree in computer science

Tools

LangGraph

Semantic Kernel

Pinecone

OpenTelemetry

Job description

Accurate Background seeks a Lead AI Engineer to establish and scale AI capabilities within a new team focused on reusable AI platforms, AI governance, and production-ready AI solutions. This role drives the AI Development Lifecycle and orchestrates AI patterns across enterprise systems.

You will mentor engineers, work with LLMs/embeddings, tool calling, and end-to-end AI services, delivering measurable business value while advancing governance and compliance in a fast-paced setting.