Applied AI Engineer
About The Position
The Applied AI Engineer will advance internal AI capabilities by owning and improving high-value, production-ready AI solutions that are reliable, maintainable, and integrated into core business workflows. Working at the intersection of LLMs, machine learning, and modern software engineering, the role partners closely with AI, Business, and Enterprise Data teams to build enterprise-grade systems across cloud and enterprise platforms. Success requires translating technical outcomes into clear business value while helping shape long-term AI strategy and deployment across internal and customer-facing experiences.
Requirements
- Strong problem-solving skills, intellectual curiosity, and a builder mindset to break down ambiguous problems and design, prototype, and iterate on AI or software solutions
- Strong Python skills with solid software engineering fundamentals and experience deploying ML/AI systems into production
- Experience building APIs or service-based architecture and working with LLM-based systems (RAG, prompt orchestration, evaluation frameworks)
- Experience working with cloud platforms and operating effectively in fast-evolving, ambiguous environments with a strong sense of ownership
- Ability to balance execution speed with engineering discipline and communicate technical concepts clearly to business stakeholders
Nice To Haves
- Experience with enterprise data platforms, semantic modeling, ontology-driven or knowledge-based systems
- Experience integrating AI solutions into operational business workflows
- Familiarity with monitoring, observability, and MLOps practices supporting production AI systems
Responsibilities
- Design, develop, and deploy LLM and ML based AI solutions into production
- Build and maintain RAG pipelines, prompt orchestration workflows, and AI-driven automation systems
- Develop scalable inference services, APIs, and integration layers
- Investigate and resolve complex system and data challenges across AI pipelines, diagnosing root causes and implementing robust solutions
- Define and implement evaluation frameworks to assess AI performance, reliability, and business impact
- Integrate AI systems with cloud data platforms and enterprise applications
- Partner with business stakeholders to translate operational challenges into structured, measurable AI solutions
- Contribute to architectural decisions that ensure scalability, maintainability, and clear system boundaries
- Uphold strong engineering standards, documentation practices, and reproducibility across AI systems
Benefits
- Quarterly profit-sharing bonus
- Hybrid Work schedule
- Team member appreciation events and recognition programs
- Volunteer opportunities
- Casual dress code
- On demand pay options
- Health insurance
- 401(k) with match
- Employee assistance programs
- Time away
- Paid parental leave
- Professional development opportunities
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
