Top AI Specialist Jobs in Chicago, IL

The AI Engineering Specialist will oversee project tasks, manage expectations, mentor junior members, and design scalable AI systems while working with advanced AI models and ML pipelines.

Build and deploy AI-augmented workflows and agents to automate internal processes across departments. Identify high-value automation opportunities, optimize operational workflows, create reusable documentation and enablement resources, measure business impact, and help establish safe AI governance standards. The role requires cross-functional consulting, stakeholder management, process analysis, and practical experience with low-code platforms, LLM APIs, prompt engineering, or AI agent frameworks.

Drives AI adoption across a regional Wealth Management field organization. Builds relationships with advisors and leadership, translates AI capabilities into practical workflows, delivers training and coaching, supports product and technology rollouts, identifies business development opportunities, gathers feedback, and develops strategies to sustain adoption across client engagement, prospecting, campaigns, and growth activities.

Lead design and implementation of AI and data governance frameworks, privacy guardrails, metadata standards, and compliance with GDPR/HIPAA/CCPA/NIST AI RMF. Monitor and audit models for bias, explainability, and transparency; partner with engineers, stewards, and leaders to embed ethical decision-making, set KPIs, run audits, and produce dashboards and reports to drive governance adoption.

Build and scale agentic AI systems that automate customer experience workflows across Slack and Salesforce. Analyze transcripts, detect SLA risks and escalations, provide self-service operational insights, and develop AI memory architecture. Partner with data, QA, workforce management, and customer advocacy teams to ensure system accuracy, reliability, trustworthy outputs, and measurable operational impact. Productize internal tools and design human escalation patterns for scalable deployment.

Own customer AI implementations from discovery through launch and ongoing optimization. Configure LLM workflows, design prompts, build evaluations, run regression testing, troubleshoot production issues across integrations and APIs, and coordinate resolution with customers and internal teams. The role requires clear communication, technical investigation, customer testing facilitation, and improving AI reliability in production.

Develops AI and automation solutions for Commercial Operations by partnering with business stakeholders and IT. Responsibilities include designing agentic AI capabilities, integrating AI with enterprise data platforms and workflows, enabling data-driven decisions, evaluating emerging technologies, and scaling successful use cases. The role requires strong application or data experience, commercial operations knowledge, programming skills, cloud-native data services experience, and hands-on LLM agentic AI expertise.

Own monitoring, testing, and tuning of Inspira's AI virtual agent to improve resolution, deflection, and CSAT. Analyze conversation transcripts and performance data, run A/B and regression tests, adjust retrieval/configuration and intents, partner with Content and IT to fix knowledge gaps, maintain performance dashboards, lead root-cause analysis, and support go-lives for new bot capabilities.

Supports research, testing, and implementation of AI solutions for business processes, data analysis, and decision-making. Develops AI prototypes and proof-of-concepts, creates reports and dashboards, documents workflows and best practices, and collaborates with stakeholders to gather requirements and feedback. The role provides practical experience with AI tools, analytics, process automation, and cross-functional project delivery.

Annotates data accurately according to project guidelines, performs quality checks, provides feedback on annotation tools and processes, collaborates with project teams, maintains efficiency, and reports issues for resolution.

Annotate and label data accurately according to project guidelines, conduct quality checks, provide feedback on annotation tools and processes, collaborate with project teams, maintain efficiency, and identify issues for resolution. The role requires strong attention to detail, critical thinking, adaptability, communication skills, and comfort with repetitive computer-based work.

Annotate and evaluate videos, images, and metadata across major social platforms to support AI system training. Apply contextual and cultural guidelines, resolve ambiguous or sensitive content decisions, perform quality assurance, identify trends and edge cases, conduct root cause analysis, prepare weekly reports, and recommend improvements to labeling processes and tools. The role requires English and Hindi fluency, strong attention to detail, analytical judgment, and comfort handling sensitive content.

Develop, optimize, test, and maintain prompts for conversational AI, automation, and business applications. Evaluate AI outputs, conduct comparative experiments, improve response quality, and create reusable prompt libraries. Translate business needs into prompting strategies while collaborating with AI engineers, trainers, product teams, and stakeholders. Document standards, support governance, research emerging techniques, and contribute to Generative AI implementation and continuous improvement.

Supports responsible AI governance by developing frameworks, conducting fairness and risk assessments, monitoring regulatory requirements, maintaining compliance documentation, educating stakeholders, and improving AI oversight practices. Works across technical, legal, compliance, risk, and business teams to promote ethical, transparent, accountable, and trustworthy AI systems.

Design, implement, and optimize AI-powered workflow automation solutions. Analyze business processes, document current and future states, gather requirements, integrate automation tools, support testing and deployment, monitor performance, and identify improvements. Collaborate with business and technical stakeholders, provide training and troubleshooting support, promote automation best practices, and contribute to digital transformation and innovation initiatives.

Designs, implements, optimizes, and administers generative and agentic AI solutions. Translates business requirements into AI workflows, oversees model deployment and performance, analyzes implementation data using Power BI, and coordinates responsible AI governance. Collaborates with engineering, security, data science, sales, and reporting teams while supporting users and maintaining AI platforms, cloud services, and low-code tools.

Lead technical discovery and validation of enterprise Private AI use cases. Run hands-on workshops, assess data and infrastructure readiness, build lightweight proofs of concept and reference architectures, and translate qualified opportunities into engineering requirements for production handoff.

Reviews videos of robotic arms, identifies key actions and outcomes, and applies detailed grading guidelines to annotate events. Uses video annotation platforms to create structured datasets, collaborates with trainers to resolve ambiguities, documents findings, communicates progress, and participates in quality reviews. Strong attention to detail, organization, communication, and accuracy are essential. Experience with video annotation, AI training, machine learning data preparation, or robotics is preferred.

Own clinical quality for member-facing AI products by partnering with product, engineering, and clinical teams. Design clinical AI evaluations, define quality thresholds and rubrics, assess accuracy, omissions, hallucinations, medication-safety risks, and translate clinical reasoning into prompts and decision logic. Monitor evolving evidence and standards of care, validate product launches, and communicate findings to technical and clinical audiences.

Design, develop, and maintain enterprise AI applications, including conversational assistants, copilots, autonomous agents, RAG solutions, and workflow automation. Build scalable APIs and microservices integrating foundation models and enterprise systems. Apply prompt and context engineering, memory management, observability, governance, and performance optimization. Collaborate with cross-functional teams to identify automation opportunities and participate in Agile development, code reviews, CI/CD, and DevSecOps.

Support the Intelligent Process Automation Lab by managing business relationships, consolidating demand, prioritizing automation use cases, shaping portfolio strategy and roadmap, expanding RPA/AI PODs, enforcing discovery best practices and governance, and coordinating requirements and delivery with development teams.

Administer and maintain AI/ML and HPC testbed infrastructure: install and manage Linux systems, configuration management, version control, scripting, datacenter hardware operations, networking support, documentation, and collaborate with researchers and operations teams to ensure testbed availability and sustainability.

Design and build AI- and automation-driven solutions to accelerate Mortgage Cadence Platform configuration using LLMs and workflow automation. Develop integrations with system APIs, partner with implementation teams, create documentation and training, and propose new tools to improve implementation accuracy and scale.

Provide insurance subject-matter expertise to improve generative AI models: design insurance tasks, create reference solutions, evaluate AI outputs with structured rubrics, refine scoring guidelines, and collaborate with research and engineering teams to produce high-quality training and evaluation data. Commitment of 35+ hours/week and proven senior insurance experience required.

Design and run red-team evaluations to find failure modes and edge cases in frontier LLMs. Create reproducible, multi-step benchmark tasks, document technical findings, and collaborate with researchers to refine grading and improve model robustness. Commit ~35 hours/week as a remote independent contractor.