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About the Role

The Applied AI Engineer identifies, develops, and implements AI, machine learning, and automation solutions to drive business value, improve efficiency, and enhance decision-making. This role partners across the organization to evaluate opportunities, deploy solutions, integrate third-party AI technologies, and ensure AI systems are secure, scalable, compliant, and sustainable.

Responsibilities

• Identify, prioritize, and implement high-impact AI and automation opportunities that drive measurable business outcomes.
• Design, build, test, and deploy scalable, production-ready AI solutions.
• Streamline business processes through automation and innovative technologies.
• Ensure AI solutions meet security, compliance, governance, monitoring, reliability, and operational readiness standards.
• Identify, assess, prioritize, and deliver high-value AI and automation initiatives aligned with business objectives.
• Partner with stakeholders to evaluate opportunities and determine appropriate AI-driven solutions.
• Develop rapid prototypes and iterate solutions based on business feedback and operational needs.
• Design, develop, implement, and support AI-powered applications, intelligent assistants, and workflow automation solutions.
• Build end-to-end solutions that improve business performance and operational efficiency.
• Apply machine learning technologies, pre-trained models, and cloud-based AI services where appropriate.
• Establish and maintain MLOps practices to support model lifecycle management.
• Oversee model versioning, experiment tracking, testing, deployment, monitoring, drift detection, and retraining processes.
• Support reliable and scalable production AI environments.
• Ensure all AI solutions comply with governance, security, regulatory, reliability, and operational readiness requirements.
• Implement monitoring and support processes that promote system stability and long-term performance.
• Apply responsible AI and data governance principles throughout solution development and deployment.
• Evaluate, select, and implement third-party AI, machine learning, and software-as-a-service solutions.
• Determine the most effective approach for solving business problems, balancing build, buy, and integration decisions.
• Integrate vendor technologies into existing business processes, applications, and infrastructure.

Requirements

• Bachelor’s Degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Software Engineering, Information Systems, or a related field required.
• Equivalent combination of education, professional certifications, and directly related experience may be considered.
• Minimum of five (5) years of experience in software engineering, data science, applied artificial intelligence, machine learning, or a related technical discipline required.
• Demonstrated proficiency in Python or a comparable programming language with strong experience integrating APIs and developing end-to-end technology solutions.
• Experience developing, implementing, or supporting large language models (LLMs), workflow automation, and cloud-based AI/ML services.
• Working knowledge of machine learning concepts, methodologies, and model deployment practices.
• Ability to evaluate business requirements and determine the most effective approach, including custom development, third-party solutions, or integrated technology platforms.
• Understanding of production support concepts including monitoring, performance optimization, reliability, and operational readiness.
• Availability to participate in an on-call support rotation as required.
• Experience working in enterprise, financial services, or other regulated environments preferred.
• Experience with Azure, AWS, Google Cloud Platform, or comparable cloud technologies preferred.
• Experience with machine learning platforms and tools such as Azure Machine Learning, MLflow, Databricks, SageMaker, Vertex AI, or similar technologies preferred.
• Experience building and managing machine learning pipelines including data preparation, training, evaluation, deployment, monitoring, and retraining preferred.
• Experience with AI development platforms and tools such as Microsoft Foundry, Azure OpenAI, Copilot Studio, or similar technologies preferred.
• Practical experience implementing MLOps practices and supporting production AI environments preferred.
• Knowledge of data governance, responsible AI principles, and AI risk management practices preferred.
• Ability to travel periodically to company locations, meetings, training sessions, or business-related events, as needed.

Skills

• Python
• API Integration
• End-to-end technology solutions
• Large language models (LLMs)
• Workflow automation
• Cloud-based AI/ML services
• Machine learning concepts
• Machine learning methodologies
• Model deployment practices
• Production support
• Monitoring
• Performance optimization
• Reliability
• Operational readiness
• Azure
• AWS
• Google Cloud Platform
• Azure Machine Learning
• MLflow
• Databricks
• SageMaker
• Vertex AI
• Machine learning pipelines
• Data preparation
• Model training
• Model evaluation
• Model deployment
• Model monitoring
• Model retraining
• Microsoft Foundry
• Azure OpenAI
• Copilot Studio
• MLops practices
• Data governance
• Responsible AI principles
• AI risk management

Location

• On-call support rotation

Work Type

• Full-time

Experience Level

• Minimum of five (5) years of experience

Education Level

• Bachelor’s Degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Software Engineering, Information Systems, or a related field
• Equivalent combination of education, professional certifications, and directly related experience

Salary/Compensations

• USD $105,000.00 - USD $145,000.00 /Yr.

Benefits

• Medical
• Dental
• Vision
• 401(k) Match
• Profit Sharing
• Paid Time Off
• 11 Holidays
• Tuition Reimbursement
• Free Parking throughout Tompkins Community Bank
• Employee Referrals

About the Company

• Tompkins is committed to a policy of Equal Employment Opportunity ("EEO") with respect to all team members and applicants for employment and a work environment free from discrimination (including unlawful harassment) based on race, color, religion, sex, sexual orientation, transgender status, gender non-conformity, gender identity, gender expression, national origin, age, marital status, domestic violence victim status, disability, predisposing genetic characteristics, military or veteran status or status in any group protected by federal, state, or local law.

Equal Opportunity

• Tompkins is committed to a policy of Equal Employment Opportunity ("EEO") with respect to all team members and applicants for employment and a work environment free from discrimination (including unlawful harassment) based on race, color, religion, sex, sexual orientation, transgender status, gender non-conformity, gender identity, gender expression, national origin, age, marital status, domestic violence victim status, disability, predisposing genetic characteristics, military or veteran status or status in any group protected by federal, state, or local law.