AI Engineering Lead

Location: Hybrid role in Dearborn, Michigan, United States. Candidates must be legally authorized to work in the United States. Visa sponsorship and relocation assistance are available.

Salary: $85,400–$192,000 annually, depending on salary grade, scope, experience, and market value.

Company

hirify.global is an established global automotive company developing transportation products and enterprise services.

What you will do

• Architect, build, and scale enterprise AI applications, copilots, agentic systems, RAG solutions, and intelligent workflow automation.
• Partner with product, engineering, analytics, data, and business stakeholders to identify high-value AI use cases and deliver measurable outcomes.
• Design reusable AI frameworks, accelerators, shared services, and engineering patterns for the Integrated Services Data, AI & Analytics portfolio.
• Lead production deployment of AI solutions using cloud-native architectures, containers, orchestration, and scalable infrastructure.
• Establish monitoring, governance, security, testing, observability, and lifecycle-management practices for AI systems.
• Lead and mentor AI engineers while developing engineering standards, shared tooling, and communities of practice.

Requirements

• Bachelor’s degree in computer science, artificial intelligence, data science, engineering, information technology, or a related field.
• 5–8 years of experience delivering enterprise software, analytics, data, or AI solutions, including 5+ years with Python-based development.
• 3+ years designing, deploying, and supporting AI/ML or generative AI solutions in production.
• Experience with generative AI, conversational AI, copilots, agent-based solutions, RAG, APIs, cloud-native architectures, and CI/CD.
• Strong technical leadership experience, including architectural decisions, solution trade-offs, and cross-functional delivery.
• Legal authorization to work in the United States is required.

Nice to have

• Master’s degree in artificial intelligence, computer science, data science, engineering, or a related field.
• Experience managing and growing high-performing AI engineering teams.
• Experience with vector databases, semantic search, knowledge grounding, and enterprise AI architecture.
• Knowledge of LangChain, LangGraph, Semantic Kernel, SQL, Spark, Vertex AI, OpenAI, Anthropic, or Gemini.
• Experience implementing responsible AI, governance, MLOps, and LLMOps at enterprise scale.

Culture & Benefits

• Hybrid work environment with opportunities to contribute to enterprise-wide AI adoption and innovation.
• Medical, dental, vision, prescription drug, family care, parental leave, and backup childcare benefits.
• Family-building benefits, vehicle discounts, tuition assistance, employee resource groups, and paid community-service time.
• Paid holidays, paid time off, and an option to purchase additional vacation time.