AI Engineering Lead

Jobtailor

Dearborn (MO)

On-site

USD 140,000 - 210,000

Full time

3 days ago

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Job summary

Jobtailor in Dearborn, MO is seeking a seasoned AI leader to drive enterprise AI initiatives across Generative AI, RAG, and conversational interfaces. You will partner with business and engineering teams to define visions, roadmaps, and measurable success metrics while delivering production-ready AI solutions.

You will establish Responsible AI governance, lead cross-functional programs, and mentor AI engineers, building reusable frameworks and accelerating enterprise adoption.

Qualifications

5 to 8 years delivering enterprise software, analytics, data, or AI solutions.
5+ years Python development and modern software practices.
3+ years deploying AI/ML or Generative AI in production.
Experience building Generative AI, conversational AI, Copilot, or agent-based solutions.
Experienced senior technical lead with architectural decision experience.
Experience with Cloud AI Platforms (GCP preferred).
Legal authorization to work in the United States.

Responsibilities

Partner with leaders to identify high-value AI opportunities and translate them into scalable solutions.
Define AI solution vision, roadmaps, and measurable success metrics.
Drive AI strategy across Generative AI, Agentic AI, and intelligent automation.
Establish governance for Responsible AI, security, compliance, and scalability.
Lead cross-functional AI programs and influence executive stakeholders with business cases.
Architect and oversee conversational AI, Copilot, RAG, and enterprise AI deployments.

Skills

Python Programming

Generative AI

AI Solution Architecture

Leadership

Mentoring

Stakeholder Influence

Education

Bachelor's Degree in Computer Science/AI/Data Science/Engineering/IT

Master's Degree in AI/CS/DS/Engineering

Tools

Vertex AI

OpenAI

Anthropic

Gemini

LangChain

LangGraph

Semantic Kernel

SQL

Spark

Vector Databases

Job description

Partner with business leaders and product teams to identify high-value AI opportunities and translate them into scalable AI-powered solutions
Define and communicate AI solution vision, roadmaps, and measurable success metrics
Drive AI strategy across Generative AI, Agentic AI, conversational experiences, AI-enabled analytics, and intelligent automation initiatives
Establish governance frameworks for Responsible AI, security, compliance, scalability, and enterprise adoption
Lead cross-functional AI programs and influence executive stakeholders through business cases, demonstrations, and measurable outcomes
Architect and oversee conversational AI, Copilot, RAG, agentic AI, AI-powered analytics, natural-language interfaces, workflow automation, decision-support, semantic search, and enterprise knowledge-management solutions
Design and deploy enterprise AI solutions using LLMs, foundation models, prompt engineering, and model evaluation frameworks
Implement AI Engineering, MLOps, and LLMOps practices including CI/CD, prompt versioning, testing, governance, monitoring, and lifecycle management
Establish reusable AI frameworks, accelerators, and engineering patterns
Evaluate emerging AI technologies and support architectural reviews
Implement Responsible AI principles including governance, explainability, privacy, security, and ethical AI compliance
Own end-to-end AI solution delivery with Product, Engineering, Data, and Business teams
Deploy production-grade AI applications, copilots, and agent-based solutions using containerization, orchestration, and scalable cloud infrastructure
Embed AI capabilities into dashboards, self-service analytics platforms, applications, and business workflows
Establish monitoring frameworks for AI performance, reliability, governance, and user adoption
Lead and mentor AI engineers and establish enterprise AI development standards
Build shared tooling, libraries, delivery patterns, Communities of Practice, and AI Centers of Excellence
Support talent development and serve as a thought leader for enterprise AI adoption and transformation

Requirements

Bachelor's Degree in a related field (Computer Science, Artificial Intelligence, Data Science, Engineering, Information Technology, or equivalent)
5 to 8 years of experience delivering enterprise software, analytics, data, or AI solutions
5+ years of experience using Python-based development technologies and modern software engineering practices
3+ years of experience designing, deploying, and supporting AI/ML or Generative AI solutions in production environments
Experience building and deploying Generative AI, conversational AI, Copilot, or agent-based solutions
Experience acting as a senior technical lead facilitating solution trade-offs and architectural decisions
Experience using Cloud AI Platforms (GCP preferred)
Strong understanding of APIs, cloud-native architectures, CI/CD pipelines, and enterprise application development
Hands-on experience with Generative AI technologies, Retrieval-Augmented Generation (RAG), and enterprise AI deployment
Candidates must be legally authorized to work in the United States
Preferred: Master's Degree in Artificial Intelligence, Computer Science, Data Science, Engineering, or related field
Preferred: Experience managing and growing high-performing AI engineering teams
Preferred: Experience developing enterprise copilots, AI assistants, agent-based systems, and intelligent automation solutions
Preferred: Experience implementing RAG architectures, vector databases, semantic search, and knowledge-grounding strategies
Preferred: Strong working knowledge of GCP and enterprise AI architecture patterns
Preferred: Expertise in Python, LangChain, LangGraph, Semantic Kernel, SQL, Spark, and modern AI development frameworks
Preferred: Experience with Vertex AI, OpenAI, Anthropic, Gemini, or comparable enterprise AI ecosystems
Preferred: Experience building reusable AI platforms, accelerators, frameworks, and enablement capabilities
Preferred: Experience deploying AI solutions into business workflows, analytics products, self-service insights platforms, or decision-support solutions
Preferred: Experience implementing Responsible AI, AI governance, MLOps, and LLMOps practices at enterprise scale

Core Competencies

Demonstrates expertise in designing and deploying AI solutions, particularly in Generative AI and conversational AI, while ensuring compliance with Responsible AI principles. Proven ability to lead cross-functional teams and drive AI strategy through measurable outcomes and governance frameworks.

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