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Explainable Ai Jobs in Ohio (NOW HIRING)

... AI-driven applications. As a Product Manager in the C360 team, you are an integral part of the ... are explainable, traceable, and auditable for downstream reliance. * Owns the arbitration and ...

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Explainable Ai information

What is the difference between Explainable Ai vs Data Scientist?

AspectExplainable AiData Scientist
CredentialsTypically requires knowledge of AI, machine learning, and data analysis; certifications like AI or ML courses are commonRequires degrees in computer science, statistics, or related fields; certifications in data analysis or machine learning are beneficial
Work EnvironmentWorks within AI development teams, focusing on model transparency and interpretabilityWorks across data analysis, model building, and business insights, often in research or corporate settings
Industry UsageUsed in AI development, healthcare, finance, and any field requiring transparent AI modelsApplied in tech, finance, healthcare, and research for data-driven decision making

Explainable Ai focuses on making AI models transparent and understandable, ensuring trust and compliance. Data Scientists develop and analyze models, often working with complex data. While both roles involve AI and data, Explainable Ai specialists emphasize interpretability, whereas Data Scientists focus on model creation and insights.

What are some of the typical challenges faced when working in Explainable AI and how do professionals address them?

Professionals in Explainable AI often encounter challenges such as balancing model accuracy with interpretability, translating complex model outputs into understandable insights for non-technical stakeholders, and ensuring transparency without compromising sensitive data. Addressing these issues typically involves using specialized tools and frameworks for visualization, collaborating closely with data scientists, domain experts, and business teams, and staying updated on the latest research in model interpretability. Continuous learning and open communication are key to overcoming these challenges and delivering AI solutions that are both effective and trustworthy.

What are the key skills and qualifications needed to thrive as an Explainable AI specialist?

To thrive as an Explainable AI specialist, you need a strong background in machine learning, data science, and statistics, typically with an advanced degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, and libraries like LIME or SHAP, as well as experience in model interpretability tools, is essential. Strong analytical thinking, effective communication, and the ability to translate complex technical concepts for non-technical stakeholders are crucial soft skills. These capabilities ensure that AI models are transparent, trustworthy, and can be responsibly integrated into decision-making processes.

What is Explainable AI?

Explainable AI (XAI) refers to methods and techniques in artificial intelligence that make the results of AI models understandable and interpretable by humans. XAI aims to provide transparency into how AI systems make decisions, helping users trust and effectively manage AI applications. This is especially important in fields like healthcare, finance, and law, where understanding the reasoning behind AI-driven outcomes can be crucial for accountability and compliance. By making AI more transparent, XAI also helps identify and address biases or errors in AI systems.
What are popular job titles related to Explainable Ai jobs in Ohio? For Explainable Ai jobs in Ohio, the most frequently searched job titles are:
What cities in Ohio are hiring for Explainable Ai jobs? Cities in Ohio with the most Explainable Ai job openings:
Infographic showing various Explainable Ai job openings in Ohio as of August 2026, with employment types broken down into 48% Full Time, and 52% Contract. Highlights an 82% In-person, and 18% Remote job distribution.

Lead Infrastructure Engineer - Infrastructure (HPE NonStop/Tandem) with AI/Automation

J.P. Morgan

Columbus, OH โ€ข On-site

$103K - $136K/yr

Full-time

Medical, Retirement

Posted 10 days ago


Job description

hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role.

JOB DESCRIPTION

Assume a vital position as a key member of a high-performing team that delivers infrastructure and performance excellence. Your role will be instrumental in shaping the future at one of the world's largest and most influential companies.

As a Lead Infrastructure Engineer at JPMorgan Chase within the Corporate Technology team, you apply deep knowledge of software, applications, and technical processes within the infrastructure engineering discipline. You will be responsible for designing, deploying, and supporting payment infrastructure deployments. The ideal candidate will have hands-on experience with HPE NonStop hardware and architecture, as well as a strong understanding of related subsystems and secure key management. This role is responsible for configuring, maintaining, and troubleshooting HPE NonStop systems and associated components, ensuring high availability and security for enterprise operations. Continue to evolve your technical and cross-functional knowledge outside of your aligned domain of expertise.

Job responsibilities

  • Configure, maintain, and troubleshoot HPE NonStop hardware and architecture.
  • Manage and configure Enterprise Secure Key Managers to ensure robust security for sensitive data.
  • Set up and maintain Etinet servers, ensuring optimal performance and integration with HPE NonStop systems.
  • Understand and support HPE NonStop subsystems (Mediacom, TMF, KMSF), and their relationship to hardware for effective troubleshooting and planning of upgrades or installations.
  • Utilize and manage SCF, ZZSTO, ZZZCIP, and ZZKRN utilities for system configuration, monitoring, and maintenance.
  • Uses enterprise-authorized AI capabilities within the work environment to accelerate infrastructure analysis and design documentation, validating outputs and handling operational data according to sensitivity and security requirements.
  • Applies reuse-first, AI-assisted practices within delivery and automation routines to identify recurring issues and validate remediation options, ensuring changes are traceable/auditable and aligned to resiliency and security expectations.
  • Leverage AI-assisted operations (AIOps) techniques to improve incident triage, reduce MTTR, and proactively detect infrastructure risks (e.g., anomaly detection on system/EMS logs, event correlation, early-warning indicators).
  • Build and curate high-quality operational knowledge (KB articles, runbooks, known-error records) that can be used by AI assistants to provide accurate, auditable troubleshooting guidance.
  • Partner with SRE/Observability and Cyber teams to evaluate, implement, and govern AI-enabled monitoring and alerting, ensuring model outputs are explainable, traceable, and compliant with security controls.
  • Document configurations, procedures, and troubleshooting steps for knowledge sharing and compliance, collaborate with cross-functional teams to plan and execute system upgrades and installations.

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience 
  • In-depth knowledge of HPE NonStop hardware and architecture, including system configuration and maintenance.
  • Experience with Enterprise Secure Key Managers: ability to configure and manage secure key solutions in an enterprise environment.
  • Proficiency in configuring Etinet servers and integrating them with HPE NonStop systems.
  • Strong understanding of HPE NonStop subsystems (Mediacom, TMF, KMSF) and their interaction with hardware, especially for troubleshooting and upgrade/install planning.
  • Hands-on experience with SCF, ZZSTO, ZZZCIP, and ZZKRN for system configuration and management.
  • Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support infrastructure engineering workflows with strong validation habits and awareness of data sensitivity.
  • Ability to review and validate AI-assisted recommendations before implementation, escalating when uncertain and ensuring outcomes align to resiliency, security, and auditability expectations.
  • Experience applying AIOps / ML-driven monitoring concepts (anomaly detection, alert correlation, noise reduction, trend forecasting, predictive capacity/health signals) in a production infrastructure environment.
  • Ability to work with telemetry pipelines (logs/metrics/traces), define data quality expectations, and operationalize signals for automation and reliability outcomes.
  • Practical experience using AI assistants for troubleshooting and documentation, with an emphasis on validation, secure handling of sensitive data, and producing audit-ready outputs.

Preferred qualifications, capabilities, and skills

  • Experience implementing or operating AIOps platforms and integrating them with incident/ticketing workflows.
  • Exposure to LLM governance concepts in enterprise settings (data classification, access controls, audit logging, model risk considerations).
  • Experience building operational analytics (e.g., Python/SQL) to mine EMS/application logs for recurring patterns, failure modes, and leading indicators.
  • Familiarity with reliability practices (SLOs/SLIs, error budgets, blameless postmortems) and using AI to improve these processes.

ABOUT US

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

ABOUT THE TEAM

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.