AI Engineer (React UI) - Remote US

📍 Job Overview

Job Title: AI Engineer (React UI)

Company: Cielo

Location: United States (Remote)

Job Type: Full-time

Category: AI Engineering / Front-end Development / Talent Technology Operations

Date Posted: April 19, 2026

Experience Level: 5-10 years

Remote Status: Remote Solely

🚀 Role Summary

• Develop and maintain intuitive, responsive user interfaces for AI-powered talent acquisition applications using React.

• Integrate front-end solutions with cutting-edge AI/ML models, including Large Language Models (LLMs), to enhance recruitment processes.

• Collaborate on back-end API development and data engineering tasks to connect diverse data sources for AI-driven insights.

• Design and implement interactive data visualizations to present complex AI-generated information in actionable formats.

• Contribute to the advancement of innovative talent acquisition solutions by staying abreast of emerging front-end and AI technologies.

📝 Enhancement Note: This role blends core front-end engineering responsibilities with a specialized focus on AI integration within the Talent Acquisition technology domain. The emphasis on React UI development, coupled with AI/LLM integration and data engineering aspects, positions this as a hybrid role requiring strong technical depth in both front-end frameworks and the practical application of AI in a business context.

📈 Primary Responsibilities

• Design, develop, and deploy robust, scalable, and accessible user interfaces using React for AI-driven talent acquisition platforms.

• Create reusable, modular UI components and implement efficient state management patterns (e.g., Redux) for complex application workflows.

• Integrate front-end applications with AI/ML models focused on talent acquisition use cases such as candidate matching, skill assessment, and predictive analytics.

• Implement interactive data visualizations using libraries like D3.js or Chart.js to effectively communicate AI-driven insights to users.

• Collaborate with back-end engineers to build and consume RESTful and SOAP APIs, ensuring seamless data flow between front-end and back-end systems.

• Support data engineering initiatives by connecting front-end applications to data from internal systems, client Applicant Tracking Systems (ATS), and third-party vendors.

• Assist in the implementation and fine-tuning of Large Language Models (LLMs) for specific talent acquisition tasks, ensuring an optimal user interface experience.

• Develop front-end components for agentic AI systems designed to assist human recruiters in their daily workflows.

• Ensure cross-browser compatibility, optimize applications for peak performance and scalability, and adhere to accessibility standards (WCAG).

• Partner with UX/UI designers to translate visual concepts into functional, user-friendly interfaces that enhance the overall user experience.

• Engage with cross-functional teams, including product managers and data scientists, to gather business requirements and translate them into effective technical solutions.

• Create comprehensive documentation for front-end architectures, components, and integration points to facilitate knowledge sharing and long-term maintenance.

• Proactively research and adopt emerging front-end technologies and advancements in AI to continuously enhance the company's talent acquisition capabilities.

📝 Enhancement Note: The responsibilities clearly indicate a need for a developer who can not only build user-facing features but also understand and integrate with complex backend systems and AI models. The mention of "agentic AI systems" and "LLM integration" suggests a role at the forefront of AI application development in HR Tech.

🎓 Skills & Qualifications

Education: Bachelor’s degree in Computer Science, Web Development, a related technical field, or equivalent practical experience.

Experience:

• 5+ years of professional software engineering experience within Agile methodologies.

Required Skills:

• Strong proficiency in modern JavaScript (ES6+), HTML5, and CSS3.

• Deep understanding and practical experience with the React ecosystem, including state management (e.g., Redux), routing (e.g., React Router), and modern build tools.

• Proven experience building and consuming RESTful APIs for front-end integration with back-end services (2+ years).

• Working knowledge of Python for back-end development and API creation.

• Experience with relational databases, specifically PostgreSQL.

• Familiarity with cloud data warehouses, particularly Snowflake.

• Understanding of responsive design principles and ensuring cross-browser compatibility.

• Experience with front-end testing frameworks and methodologies (e.g., Jest, React Testing Library).

• Familiarity with modern LLM technologies (e.g., Anthropic Claude, OpenAI GPT) and their integration into user interfaces.

• Experience designing and implementing user interfaces for AI agent interactions, including conversational UIs and agent feedback mechanisms.

• Hands-on experience using AI coding assistants (e.g., Claude Code, GitHub Copilot) to enhance development workflows.

Preferred Skills:

• Experience creating interactive data visualizations using libraries such as D3.js, Chart.js, or similar.

• Understanding of accessibility standards (WCAG) and practical implementation in web applications.

• Knowledge of CI/CD pipelines and deployment strategies for web applications.

• Familiarity with cloud architectures, with a primary focus on AWS, and secondary exposure to Azure and GCP.

• Understanding of current trends in Data Science, Artificial Intelligence, Machine Learning, and Deep Learning.

• Awareness of ethical considerations and best practices in AI, particularly within hiring and candidate assessment contexts.

• Prior work experience in talent acquisition, HR tech, or related fields.

• Familiarity with data pipeline tools like Apache Airflow.

📝 Enhancement Note: The requirement for both front-end (React) and back-end (Python) skills, along with specific database (PostgreSQL) and data warehousing (Snowflake) experience, indicates a need for a full-stack capable engineer with a front-end specialization. The emphasis on AI coding assistants and LLM integration points to a forward-thinking role.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrate projects showcasing complex React application development, highlighting component reusability and state management solutions.

• Include examples of front-end integrations with APIs, illustrating data fetching, manipulation, and presentation.

• Present case studies of user interfaces designed for AI-driven features or data visualization, emphasizing user experience and clarity of information.

Process Documentation:

• Be prepared to discuss your approach to Agile development, including sprint planning, execution, and retrospectives.

• Detail your process for ensuring code quality, including testing methodologies (unit, integration, end-to-end) and code reviews.

• Explain your workflow for collaborating with designers and back-end engineers, emphasizing communication and feedback loops.

• Describe your process for staying updated with new technologies and integrating them into development workflows.

📝 Enhancement Note: While not explicitly stated, for a role of this nature, demonstrating practical application of skills through a portfolio is crucial. Projects involving data visualization, API integration, and ideally some AI/ML component interaction would be highly beneficial.

💵 Compensation & Benefits

Salary Range: Based on the experience level (5-10 years), the location (US Remote), and the specialized skills required (React, AI, LLM integration), a competitive salary range for an AI Engineer (React UI) in the United States would typically fall between $120,000 and $170,000 per year. This estimate considers the demand for skilled AI and front-end engineers, the company's standing as a global talent acquisition partner, and the remote work arrangement.

Benefits:

• Comprehensive health, dental, and vision insurance plans.

• Retirement savings plan options (e.g., 401(k) with company match).

• Paid time off (PTO), including vacation, sick leave, and holidays.

• Professional development opportunities, including training, certifications, and conference attendance.

• Potential for performance-based bonuses or incentives.

• Flexible work environment and remote work support.

• Access to cutting-edge AI tools and technologies for professional growth.

Working Hours: Regular full-time position, approximately 40 hours per week. Preference for candidates in the Central or Eastern time zones to facilitate collaboration.

📝 Enhancement Note: The salary estimate is based on industry benchmarks for similar roles in the US, factoring in the specific technical requirements and the candidate's experience level. Benefits are standard offerings for full-time roles at established companies.

🎯 Team & Company Context

🏢 Company Culture

Industry: Talent Acquisition Technology / Human Resources Services. Cielo operates at the intersection of HR technology and talent strategy, providing innovative solutions to help companies find and retain the best talent. This industry is rapidly evolving with the integration of AI and automation.

Company Size: Cielo is described as the "world's leading Talent Acquisition Partner," suggesting a large, established, and global organization with a significant employee base. This implies robust processes, established career paths, and a structured work environment.

Founded: The founding date is not specified, but the company's positioning as a leader indicates a history of growth and innovation in the talent acquisition space.

Team Structure:

• The AI Engineer will likely be part of a broader Engineering or Technology team, potentially within a dedicated AI/ML or Product Development group.

• This team will collaborate closely with Product Management, UX/UI Design, Data Science, and potentially client-facing teams.

Methodology:

• Data Analysis & Insights: Emphasis on leveraging data from ATS, CRM, and other HR systems to drive AI model development and reporting.

• Workflow Planning & Optimization: Focus on designing and implementing efficient workflows for talent acquisition processes, enhanced by AI.

• Automation & Efficiency: A core tenet of Cielo's business is to automate and optimize talent acquisition, with AI playing a central role in this mission.

Company Website: https://www.cielotalent.com/ (Inferred from company description and general knowledge of Cielo)

📝 Enhancement Note: Cielo's focus on being a "Talent Acquisition Partner" suggests a client-centric approach. The role likely involves building solutions that directly impact client hiring outcomes, requiring a blend of technical excellence and business acumen.

📈 Career & Growth Analysis

Operations Career Level: This role represents a mid-to-senior level engineering position. It requires substantial experience in front-end development and a growing expertise in AI integration, positioning the individual as a key contributor to the company's AI-driven product strategy. The "AI Engineer" title suggests a specialization beyond general software engineering.

Reporting Structure: The AI Engineer will likely report to an Engineering Manager or a Lead AI Engineer. They will collaborate closely with Product Managers, UX Designers, Data Scientists, and other engineers. The remote nature of the role necessitates strong self-management and proactive communication.

Operations Impact: The work of this AI Engineer will directly impact the efficiency and effectiveness of talent acquisition processes for Cielo's clients. By developing intuitive UIs for AI tools, they will help recruiters make better matches, optimize hiring workflows, and ultimately improve the candidate and hiring manager experience. This has a direct correlation to revenue generation through improved placement rates and client satisfaction.

Growth Opportunities:

• Specialization: Deepen expertise in AI/ML integration, LLMs, and specific talent acquisition use cases, potentially moving into an AI Specialist or ML Engineer role.

• Leadership: Progress to a Senior AI Engineer or Tech Lead role, mentoring junior engineers and taking ownership of larger project initiatives.

• Cross-functional Mobility: Transition into roles with more direct product strategy involvement or management within the engineering organization.

• Learning & Development: Access to training, certifications, and conferences in AI, machine learning, and advanced front-end development.

📝 Enhancement Note: The combination of React and AI skills is highly sought after. Growth opportunities will likely involve deepening AI expertise and potentially moving into more senior technical or leadership roles within the engineering function.

🌐 Work Environment

Office Type: This is a fully remote position within the United States. The company culture supports remote work, likely leveraging digital collaboration tools extensively.

Office Location(s): While the role is remote, the company has a presence in Wauwatosa, Wisconsin, and likely other locations globally, as indicated by their status as a "world's leading Talent Acquisition Partner." Candidates are ideally located in the Central or Eastern time zones for better collaboration.

Workspace Context:

• Collaborative Environment: Expect a highly collaborative virtual environment, relying on tools like Slack, Microsoft Teams, Zoom, and project management software.

• Operations Tools & Technology: Access to a modern technology stack including cloud platforms (AWS), development tools, and AI-specific platforms.

• Team Interaction: Regular virtual team meetings, stand-ups, code reviews, and brainstorming sessions will be part of the routine.

Work Schedule: Standard 40-hour work week, Monday to Friday. Flexibility is often a feature of remote roles, but adherence to core working hours, particularly within the Central or Eastern time zones, is encouraged for effective team synchronization.

📝 Enhancement Note: The remote-first nature means strong emphasis will be placed on asynchronous communication, clear documentation, and proactive engagement with team members.

📄 Application & Portfolio Review Process

Interview Process:

1. Initial Screening: A recruiter will likely conduct an initial call to assess basic qualifications, experience, and cultural fit.

2. Technical Interview(s): Expect one or more technical interviews focusing on:

• React Fundamentals: Deep dives into component lifecycle, state management, hooks, performance optimization.
• JavaScript Concepts: Advanced JavaScript features, asynchronous programming, closures, etc.
• API Integration: Designing and consuming APIs, handling responses, error management.
• Problem-Solving: Algorithmic challenges and practical coding exercises.
• AI/LLM Concepts: Discussion of LLM integration, understanding of AI concepts relevant to talent acquisition.

1. Coding Challenge/Take-Home Assignment: A practical assignment to build a small feature or solve a defined problem, often involving React and potentially some API interaction or data handling.

2. Hiring Manager/Team Interview: A discussion with the hiring manager and potential team members to assess overall fit, collaboration style, and deeper technical understanding.

3. Final Interview: Potentially with a senior leader to discuss career aspirations and final alignment.

Portfolio Review Tips:

• Curate Select Projects: Focus on 2-3 projects that best demonstrate your React UI development skills, API integration capabilities, and any experience with AI/data visualization.

• Highlight Impact: For each project, clearly articulate the problem you solved, your specific contributions, the technologies used, and the outcome or impact (e.g., improved user engagement, faster data processing).

• Code Quality: Ensure any linked code repositories are clean, well-documented, and follow best practices.

• AI Integration Examples: If you have projects involving LLMs, AI agents, or data visualization derived from AI, showcase them prominently. Explain the AI component and how your UI facilitated its use.

• Quantify Achievements: Use metrics where possible to demonstrate the success of your work (e.g., "Reduced load times by X%", "Increased user interaction with feature Y by Z%").

Challenge Preparation:

• Algorithm Practice: Brush up on common data structures and algorithms.

• React Deep Dive: Review core React concepts, performance optimization techniques, and common patterns.

• API Design: Understand principles of RESTful API design and how to consume them effectively.

• AI/LLM Context: Familiarize yourself with common LLM applications in business, especially in HR/recruitment. Understand concepts like prompt engineering and agentic behavior.

• Whiteboarding/Live Coding: Practice explaining your thought process while coding, as this is often tested in live coding sessions.

📝 Enhancement Note: Given the role's focus, expect a strong emphasis on practical coding skills, architectural thinking regarding UI/API integration, and an understanding of how AI can be leveraged through user interfaces.

🛠 Tools & Technology Stack

Primary Tools:

• Front-end Framework: React (primary)

• JavaScript Libraries: Redux, React Router, potentially others for state management and UI components.

• Build Tools: Webpack, Babel, Vite, or similar.

• Styling: CSS3, SASS/LESS, potentially CSS-in-JS solutions.

Analytics & Reporting:

• Data Visualization Libraries: D3.js, Chart.js, Recharts, or similar.

• Analytics Tools: Google Analytics, Mixpanel, or internal analytics platforms for tracking user behavior.

• Dashboarding Tools: Tools for creating and managing dashboards, potentially integrated with backend data sources.

CRM & Automation:

• CRM: While not directly a CRM role, understanding how to integrate with ATS (Applicant Tracking Systems) is key.

• Cloud Platforms: AWS (primary), with potential exposure to Azure and GCP. Services like S3, EC2, Lambda, CloudFront are likely relevant.

• Data Warehouses: Snowflake.

• Databases: PostgreSQL.

• Data Pipeline Tools: Apache Airflow (familiarity).

• AI/LLM Platforms: APIs and SDKs for integrating with models from OpenAI, Anthropic, and potentially others.

• AI Coding Assistants: Claude Code, GitHub Copilot, or similar.

📝 Enhancement Note: This is a modern tech stack heavy on JavaScript, cloud services, and AI integration. Proficiency across these areas is critical.

👥 Team Culture & Values

Operations Values:

• Innovation & Forward-Thinking: A commitment to leveraging cutting-edge AI and technology to solve complex talent acquisition challenges.

• Data-Driven Decision Making: Utilizing data insights to inform product development, optimize processes, and measure impact.

• Collaboration & Teamwork: Fostering an environment where cross-functional teams work together seamlessly to achieve common goals.

• Client Focus: Dedication to delivering exceptional talent acquisition solutions that drive value for clients.

• Efficiency & Optimization: Continuously seeking ways to streamline processes and improve outcomes through technology and best practices.

Collaboration Style:

• Agile & Iterative: Working in sprints, embracing feedback, and adapting to changing requirements.

• Cross-Functional Partnership: Close collaboration with Product, Design, Data Science, and other engineering disciplines.

• Open Communication: Encouraging candid feedback, knowledge sharing, and transparent discussions.

• Remote-First Mindset: Adapting collaboration strategies for a distributed workforce, emphasizing clear documentation and asynchronous communication.

📝 Enhancement Note: Expect a culture that values technical expertise, innovation in AI, and a collaborative approach to solving business problems for clients.

⚡ Challenges & Growth Opportunities

Challenges:

• Rapidly Evolving AI Landscape: Keeping pace with the fast-changing advancements in AI, LLMs, and related technologies.

• Integrating Complex Systems: Seamlessly connecting front-end interfaces with sophisticated AI models and diverse data sources.

• Balancing Innovation with Stability: Implementing new AI features while ensuring the reliability, scalability, and security of the platform.

• Translating Technical Concepts: Effectively communicating complex AI capabilities and data insights through intuitive user interfaces.

• Remote Collaboration: Maintaining strong team cohesion and productivity in a fully remote environment.

Learning & Development Opportunities:

• AI/ML Specialization: Opportunities to deepen expertise in AI model integration, prompt engineering, and potentially fine-tuning LLMs.

• Cloud Architecture: Further development of skills in cloud platforms like AWS.

• Advanced Front-end Techniques: Mastering new React features, performance optimization strategies, and modern UI patterns.

• Industry Knowledge: Gaining deep insights into the talent acquisition and HR tech landscape.

• Mentorship Programs: Access to senior engineers and leaders for guidance and career development.

📝 Enhancement Note: This role offers significant opportunities to grow at the intersection of AI and HR technology, a rapidly expanding and high-demand field.

💡 Interview Preparation

Strategy Questions:

• "Describe a complex UI you built with React. What were the main challenges, and how did you overcome them?" (Focus on architecture, state management, and performance.)

• "How would you integrate an LLM API to provide resume summarization directly within a recruiter's workflow? What UI considerations would be important?" (Focus on practical AI application and UI design.)

• "Walk me through your process for debugging a front-end issue that involves interaction with a backend API. What tools and techniques do you use?" (Focus on systematic troubleshooting.)

Company & Culture Questions:

• "What interests you about working with AI in the talent acquisition space?" (Showcase your understanding of the industry and AI's role.)

• "How do you stay current with advancements in React and AI technologies?" (Demonstrate initiative and continuous learning.)

Portfolio Presentation Strategy:

• Storytelling: Frame each portfolio project as a narrative: the problem, your solution, the technology stack, and the impact.

• Focus on Relevance: Tailor your presentation to highlight skills most relevant to the job description – React UI, API integration, and any AI/data visualization components.

• Show, Don't Just Tell: If possible, provide live demos or interactive walkthroughs of your projects.

• Quantify Results: Use metrics to back up claims about the success of your work.

• Explain Your Role: Clearly articulate your specific contributions, especially in team projects.

📝 Enhancement Note: Be prepared to discuss both your technical proficiency in React and your understanding of how AI can be applied and presented to users in a recruitment context.

📌 Application Steps

To apply for this AI Engineer (React UI) position:

• Submit your application through the provided link on the SmartRecruiters platform.

• Tailor Your Resume: Ensure your resume highlights your React development experience, JavaScript proficiency, API integration skills, and any exposure to AI, LLMs, Python, or data visualization tools. Use keywords from the job description.

• Prepare Your Portfolio: Have 2-3 key projects ready to showcase, focusing on React UI development and demonstrating your ability to integrate with backend services or visualize data. Be ready to discuss your contributions and the impact of your work.

• Research Cielo: Understand their mission as a Talent Acquisition Partner and how AI is integrated into their offerings. Prepare to discuss why you are interested in their specific approach.

• Practice Interview Questions: Review common React, JavaScript, API integration, and AI-related interview questions. Be ready to articulate your thought process clearly.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.