What are the responsibilities and job description for the Artificial Intelligence Engineer position at Marlabs?
Hiring Fulltime AI Engineer, Englewood Cliffs, NJ- Onsite 5 days a week. NO C2C
Job Description:
This position will identify high-impact business opportunities, design scalable AI-enabled solutions, and build production-ready capabilities that improve how teams work across the company. The ideal candidate combines hands-on AI engineering skills, a strong software engineering foundation, and the ability to translate business needs into reliable enterprise-grade solutions.
The AI/AX team operates as an internal forward-deployed engineers embedded directly with the company's business domain teams. In this model, this role works closely with each domain to learn its processes deeply, reimagine legacy workflows into future-state AI-enabled solutions, and deliver them hands-on. Strong people skills and product management instincts are essential to gather requirements, build trust, and translate business needs into practical, high-impact solutions.
What You Will Own
- Drive enterprise AI transformation initiatives from opportunity discovery through solution design, implementation planning, and measurable business adoption.
- Design and build AI-enabled workflows and agent-based solutions that support business process improvement, decision support, and operational automation across enterprise functions.
- Design scalable AI and data solution architectures that connect enterprise systems, modern data platforms, APIs, and analytics workflows into reliable production capabilities.
- Partner with business stakeholders across business units, supply chain, eCommerce, marketing, legal, finance, and related functions to translate business processes into AI-enabled workflows, data models, and software solutions.
- Create AI transformation artifacts including capability roadmaps, solution blueprints, intake and prioritization frameworks, implementation plans, and executive-ready progress reporting.
Required Qualifications
- 10 years combined experience across software engineering, applied AI/ML, data engineering, or enterprise architecture, with a strong record of delivering production-quality technical solutions.
- Strong coding skills in Python, Java, JavaScript, TypeScript, and SQL.
- Hands-on experience building LLM-based applications or agent systems, including prompt/context engineering, orchestration, and tool-use design.
- Solid software engineering foundation, including API design, backend service development, cloud-native architecture, system integration, testing discipline, and maintainable code practices.
- Demonstrated ability to translate ambiguous business problems into scoped AI and software solutions, and to communicate technical tradeoffs clearly to business and executive stakeholders.
- Strong people skills and product management ability to embed with business domain teams, learn their processes quickly, and imagine future-state designs that replace legacy workflows with AI-enabled solutions.
- Experience designing and implementing internal AI applications, workflow automation, or AI-enabled business process solutions in enterprise environments.
- Proven experience driving multiple concurrent projects with engineers and cross-functional contributors, including setting direction, managing execution, resolving blockers, and ensuring delivery accountability.
Preferred Qualifications
- Domain knowledge in SCM, sales forecasting, eCommerce, marketing, consumer electronics, appliances, retail, or another B2B/B2C hybrid enterprise is a plus.
- Experience setting up ontologies or enterprise knowledgebases for AI-enabled business applications is a major plus.
- Experience developing, maintaining, and releasing production enterprise-grade AI applications, including RAG pipelines or knowledge graph-based solutions, is preferred.
- Ability to prepare clear, well-structured materials and present project updates, proposals, and recommendations effectively to senior leadership.
- Understanding of big data concepts and practical data science skills is a plus.
- Experience with multi-agent orchestration, AI chat experiences, guardrails, model evaluation, or fine-tuning is nice to have.