Senior AI Engineer

CliftonLarsonAllen LLP
Arlington, United States of America
1 month ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Arlington, United States of America

Tech stack

API
Artificial Intelligence
Application Layers
Azure
Code Review
Continuous Integration
Information Leak Prevention
Decision Support Systems
Monitoring of Systems
Python
Machine Learning
Regression Testing
Service-Oriented Architecture
Software Engineering
Management of Software Versions
Data Logging
Large Language Models
Reliability of Systems
Data Management
Machine Learning Operations
Data Pipelines
Databricks

Job description

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

Requirements

  • 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

Benefits & conditions

· 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 #LI-JH1 Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities Click 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 .

About the company

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 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., © 2026 Careerjet All rights reserved

Apply for this position