Senior AI Engineer
CliftonLarsonAllen LLP
CLA is a top 10 national professional services firm where our purpose is to create opportunities every day, for our clients, our people, and our communities through industry-focused wealth advisory, digital, audit, tax, consulting, and outsourcing services. Even with more than 8,500 people, 130 U.S. locations, and a global reach, we promise to know you and help you.
CLA is dedicated to building a culture that invites different beliefs and perspectives to the table, so we can truly know and help our clients, communities, and each other.
CLA is currently seeking a Senior AI Engineer to join our growing CLA Digital - Data and Automation Team. The Senior AI Engineer will lead the design and implementation of production-grade AI solutions across machine learning, optimization, and generative AI. This role is ideal for someone who can translate business problems into scalable, reliable technical solutions that perform in real-world environments.
You will work closely with AI leadership while providing day-to-day technical guidance to junior team members. This position blends applied machine learning, software engineering, cloud architecture, and end-to-end solution delivery. Success in this role requires a strong understanding that production AI involves far more than model development-it includes evaluation, observability, integration, governance, and operational excellence.
About the role:
AI Solution Development & Architecture
- Lead the implementation of production-ready AI systems across predictive modeling, optimization, and LLM-powered applications
- Design end-to-end architectures including data pipelines, APIs, model services, orchestration layers, and monitoring systems
- Build and deploy AI workflows within Azure and Databricks environments
- Develop robust evaluation frameworks for both ML models and LLM-based systems
- Design and implement AI applications with strong grounding, safety, evaluation, and cost controls
- Build AI workflows including tool integration, memory systems, and orchestration logic
- Implement model routing, fallback strategies, and guardrails
- Develop context and memory systems (retrieval, summarization, session continuity)
- Establish robust evaluation frameworks for ML and LLM systems
- Define and monitor:
- Task success metrics and regression testing
- Hallucination and grounding performance
- Safety risks (prompt injection, data leakage)
- Implement observability practices including logging, tracing, and monitoring
- Ensure system reliability through testing, deployment standards, and incident readiness
- Translate ambiguous business needs into clear technical designs and delivery plans
- Provide mentorship and technical oversight to junior engineers
- Lead architecture reviews, code reviews, and technical design discussions
- Establish engineering standards across testing, CI/CD, deployment, and monitoring
- Partner with product, engineering, security, and business stakeholders
- Support solution design, feasibility assessments, and delivery planning
- Contribute to proposals, technical narratives, and client-facing engagements
- Own major technical workstreams for AI delivery from design through deployment
- Build scalable data and model pipelines for batch and real-time use cases
- Lead development of LLM-based applications with strong grounding, evaluation, safety, and cost controls
- Implement classical AI and advanced analytics approaches including forecasting, anomaly detection, optimization, recommendation, and decision support
- Define and implement MLOps and LLMOps standards including versioning, deployment, monitoring, and rollback strategies
- Design secure and supportable integrations across enterprise systems, APIs, and data platforms
- Evaluate tradeoffs across tools, frameworks, and architecture choices in Azure and Databricks
- Troubleshoot complex issues in production environments across data, infrastructure, and application layers
- Drive technical quality and ensure solutions are maintainable, scalable, and aligned to client needs
- Support business development by contributing to solution framing, estimates, and technical narratives
What you will need:
- 2 years of relevant experience required
- 5-7 years of experience in AI engineering, machine learning, or software engineering preferred
- Strong proficiency in Python and production-grade development practices preferred
- Proven experience deploying ML/AI systems into production environments preferred
- Experience designing APIs, pipelines, and service-oriented architectures preferred
- Strong understanding of model evaluation, experimentation, and performance tradeoffs preferred
- Ability to work independently and mentor junior team members
- Strong communication skills across technical and non-technical audiences
Our Perks:
* Flexible PTO (designed to offer flexible time away for you!)
* Up to 12 weeks paid parental leave
* Paid Volunteer Time Off
* Mental health coverage
* Quarterly Wellness stipend
* Fertility benefits
* Complete list of benefits here
#LI-JH1
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
Click here to learn about your hiring rights.Wellness at CLA
To support our CLA family members, we focus on their physical, financial, social, and emotional well-being and offer comprehensive benefit options that include health, dental, vision, 401k and much more.
To view a complete list of benefits click here.
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