Senior AI Engineer

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)

Evaluation, Safety & Reliability

• 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

Technical Leadership

• 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

Cross-Functional Collaboration

• 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

Core Responsibilities

• 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

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Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities


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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.