Agent Design Manager

📍 Job Overview

Job Title: Agent Design Manager

Company: PolyAI

Location: London, England, United Kingdom

Job Type: Full-Time

Category: Conversational AI Design & Engineering Management

Date Posted: 2026-04-02T16:43:05

Experience Level: 5-10 Years

Remote Status: Hybrid

🚀 Role Summary

• Lead and mentor a multidisciplinary team of Agent Designers and Agent Design Engineers in the creation of lifelike voice assistants and conversational AI experiences.

• Drive the end-to-end lifecycle of conversational agent development, encompassing user journey mapping, dialogue design, tone, technical implementation (prompting, tool integration, context engineering), testing, and iterative improvement.

• Act as the design authority for conversational UX, establishing and upholding standards for naturalness, clarity, consistency, and overall user-centricity across all voice assistants.

• Foster a collaborative and continuously improving team culture, prioritizing user-centered thinking and championing design quality throughout the development process.

📝 Enhancement Note: This role bridges conversational UX design and technical implementation, focusing on the 'feel' of conversations and the underlying systems. The "Agent Design Manager" title implies a strong emphasis on leading a team to create sophisticated, human-like conversational agents, integrating advanced AI concepts like prompt engineering and tool access. The operations context here is in ensuring the efficient, high-quality delivery of complex AI product features.

📈 Primary Responsibilities

• Lead, mentor, and develop a team of Agent Designers and Agent Design Engineers, enhancing both their design craft and technical execution capabilities to meet high standards.

• Set clear team objectives, provide constructive and actionable feedback, and actively support the professional growth and career development of each team member.

• Cultivate a team culture characterized by curiosity, robust collaboration, and a commitment to continuous improvement, with a strong user-centered design ethos.

• Define and enforce standards for conversational UX, ensuring all voice assistants exhibit naturalness, clarity, appropriate tone, and consistent interaction quality.

• Maintain hands-on involvement in agent design and implementation, particularly for complex projects or those with significant strategic impact, to ensure practical understanding and leadership.

• Guide the team through the complete agent development lifecycle: user journey mapping, conversation design, implementation (including prompting, tool integration, and context engineering), rigorous testing, and data-driven iteration.

• Develop and refine internal processes that effectively balance creative exploration with reliable, high-quality product delivery for conversational AI agents.

• Collaborate closely with Engineering, Product Management, and Project Management teams to champion design quality and advocate for user experience throughout the product development lifecycle.

• Stay at the forefront of agentic AI workflows, actively experiment with new tooling and patterns, and integrate learnings to enhance the team's building capabilities and methodologies.

📝 Enhancement Note: The responsibilities emphasize leadership, process ownership, and technical depth in conversational AI. The "driving the discipline forward" aspect highlights the need for innovation and continuous improvement in AI agent design methodologies, which is a key GTM and operations function for a cutting-edge tech company.

🎓 Skills & Qualifications

Education: While no specific degree is mandated, a strong foundation in a technical or design-related field is expected. Candidates from backgrounds in Computer Science, Human-Computer Interaction, Linguistics, or related disciplines are likely to possess the necessary analytical and creative skills.

Experience:

• A minimum of 5 years in a technical or design-adjacent role within a technology company, requiring hands-on experience in areas such as conversational design, software engineering, or a hybrid of both.

Required Skills:

• Conversational UX Design: Deep understanding of conversational design principles, dialogue flow, user journey mapping, and crafting natural, intuitive interactions for voice and chat interfaces.

• Team Leadership & Mentorship: Proven ability to lead, mentor, and develop technical and design talent, fostering growth and high performance within a team.

• Python Proficiency: Ability to read, review, and meaningfully contribute to Python codebases, essential for understanding and guiding technical implementation. Engineering-focused candidates should be prepared to engage at a deeper coding level.

• Agentic AI Workflow Engagement: Demonstrated hands-on experimentation and opinion-forming regarding agentic AI, multi-agent systems, prompt engineering, tool use, and context management.

• Attention to Detail: Meticulous focus on language precision, consistency in tone, interaction quality, and overall user experience.

• Communication Skills: Excellent ability to communicate clearly and inclusively, effectively bridging the gap between design and engineering concepts for diverse stakeholders.

• Technical Implementation Understanding: Familiarity with concepts such as prompting, tool integration, and context engineering within AI systems.

Preferred Skills:

• Experience designing or deploying conversational AI assistants (voice or chat) across various platforms.

• Practical familiarity with Large Language Models (LLMs), including prompt engineering, tool use, retrieval-augmented generation (RAG), and context management.

• Hands-on experience with agentic frameworks or orchestration patterns, such as multi-step reasoning, structured workflows, and tool-calling agents.

• Proficiency with agile delivery methodologies, including sprint planning, retrospectives, and capacity management.

• Experience managing external client relationships and stakeholder expectations.

📝 Enhancement Note: The blend of design and engineering requirements, along with a focus on agentic AI and Python proficiency, indicates a role that requires a technically savvy design leader. The "5+ years in a technical or design adjacent role" and "3+ years of people management" clearly defines the seniority. The preference for LLM and agentic framework experience highlights the cutting-edge nature of the role.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Conversational Design Case Studies: Demonstrating the design process for complex conversational flows, including user journey mapping, dialogue design, and rationale behind tone and interaction choices.

• Technical Implementation Examples: Showcasing contributions to or understanding of the technical aspects of agent development, such as prompt engineering, tool integration logic, or context management strategies. This could include code samples (Python) or detailed architectural diagrams.

• Team Leadership & Process Improvement: Evidence of managing design/engineering teams, including examples of process improvements implemented, mentorship strategies, and how team performance was enhanced.

• User-Centricity & Iteration: Examples of how user feedback and data were incorporated to iterate and improve conversational agent performance and user experience.

Process Documentation:

• Workflow Design & Optimization: Ability to document and present clear workflows for agent development, from initial concept to production deployment, highlighting efficiency gains and quality controls.

• Implementation Standards: Documented approaches to prompt engineering, tool integration, and context management that ensure scalability, reliability, and maintainability of conversational agents.

• Performance Measurement & Analysis: Processes for tracking agent performance metrics, analyzing conversational data, and using insights to drive continuous improvement.

📝 Enhancement Note: For a role like this, a portfolio should not only showcase design and technical output but also the candidate's ability to lead teams, establish processes, and drive innovation in a rapidly evolving AI field. The emphasis is on demonstrating a holistic approach to agent design and development, reflecting the "full picture" ownership mentioned in the job description.

💵 Compensation & Benefits

Salary Range: For an Agent Design Manager in London with 5-10 years of experience, particularly in a high-growth AI company like PolyAI, the estimated salary range is £80,000 - £120,000 per annum. This estimate is based on current market data for similar leadership roles in AI/Tech in London, considering the specialized skills in conversational AI design, technical implementation, and people management.

Benefits:

• Equity: Participation in the company’s employee share options plan, offering a stake in PolyAI's long-term success.

• Time Off: 25 days of annual holiday, in addition to UK bank holidays.

• Flexible Work: A flexible working from home policy, allowing for a hybrid work model.

• Global Mobility: Opportunity to work from outside the UK for up to 6 months each year.

• Well-being Support: Access to TELUS Health EAP 24/7 for confidential support for work, health, and life challenges.

• Family Support: Enhanced parental leave policies.

• Commuting Benefits: Bike2Work scheme to encourage sustainable commuting.

• Professional Development: Annual learning and development allowance for continuous skill enhancement.

• Home Office Setup: A one-off WFH allowance provided upon joining to improve home working comfort and productivity (e.g., for headphones or desk chairs).

• Family Planning: Company-funded fertility and family-forming programmes.

• Health Programs: Menopause care programme with Maven, and private healthcare and dental cover.

• Additional Perks: Discounts on gym memberships and relaxation apps, and access to a range of mental health programs.

Working Hours: While a standard full-time role is implied, the "Flexible working from home policy" and the global mobility option suggest a degree of flexibility in working hours, provided team collaboration and project deadlines are met. A typical work week would likely involve around 40 hours, with potential for extended hours during critical project phases.

📝 Enhancement Note: The salary range is a professional estimate for a London-based role of this seniority and specialization. The benefits package is comprehensive, highlighting PolyAI's commitment to employee well-being, professional growth, and a modern, flexible work environment, which are key attractions for operations and tech professionals.

🎯 Team & Company Context

🏢 Company Culture

Industry: Artificial Intelligence (AI), specifically focused on Conversational AI and Voice Assistants for customer service automation. PolyAI is a leader in creating lifelike voice assistants that enhance customer service operations.

Company Size: PolyAI is a growing tech company, likely in the scale-up phase, with a significant number of employees but still maintaining an agile and innovative environment. The exact size classification isn't provided, but the ambition and customer base suggest a company with substantial resources and growth trajectory.

Founded: PolyAI was founded in 2016, indicating a company with established expertise and a proven track record in the advanced AI space, built on years of research and development.

Team Structure:

• The Agent Design team is multidisciplinary, comprising Agent Designers and Agent Design Engineers. This structure promotes close collaboration between UX/conversational design expertise and technical implementation skills.

• The Manager will report into a senior leadership role, likely within Product or Engineering, overseeing the strategic direction and execution of conversational AI experiences.

Methodology:

• Data-Driven Design: The team will likely employ a data-driven approach, using insights from customer interactions and performance metrics to inform design decisions and drive continuous improvement of AI agents.

• Agile Development: The mention of "agile delivery practices" suggests a workflow that involves iterative development, sprint planning, and regular feedback loops to ensure rapid and effective delivery of AI features.

• User-Centric Experimentation: A culture of experimentation is implied, with a focus on actively exploring new AI tooling and patterns, and a bias for action to quickly bring innovations into production.

Company Website: https://poly.ai/

📝 Enhancement Note: PolyAI operates at the cutting edge of AI, focusing on practical applications in customer service. The company's founding date suggests maturity, while its product focus points to a dynamic, innovation-driven culture. The team structure and methodologies emphasize a blend of creative design and rigorous engineering, essential for building sophisticated AI products.

📈 Career & Growth Analysis

Operations Career Level: This role represents a senior leadership position within the Conversational AI product development lifecycle. It sits at the intersection of product design, engineering management, and AI specialization. The "Manager" title indicates responsibility for a team and a significant impact on product quality and delivery.

Reporting Structure: The Agent Design Manager will lead a team of Agent Designers and Agent Design Engineers, likely reporting to a Director or VP of Product/Engineering. This structure allows for strategic guidance from senior leadership while enabling the manager to drive execution and team development.

Operations Impact: The primary impact of this role is on the quality, effectiveness, and naturalness of PolyAI's voice assistant products. This directly influences customer satisfaction, operational efficiency for PolyAI's clients, and ultimately, the company's competitive advantage and revenue potential by enabling scalable, high-quality customer service automation.

Growth Opportunities:

• Team Expansion & Leadership: Potential to grow the Agent Design team, onboard new talent, and take on broader management responsibilities within the AI product organization.

• Strategic Influence: Opportunity to influence the strategic direction of PolyAI's conversational AI offerings, shape future product roadmaps, and contribute to the company's overall AI strategy.

• Specialization Advancement: Deepen expertise in cutting-edge areas like agentic AI, LLM orchestration, and advanced conversational UX, potentially becoming a recognized subject matter expert within the company and industry.

• Cross-Functional Leadership: Develop broader leadership skills by collaborating closely with Product, Engineering, and client-facing teams, gaining insights into different aspects of the business.

📝 Enhancement Note: This role offers significant growth potential beyond managing a team, extending into strategic product direction and leadership within the AI domain. The impact on customer experience and operational efficiency for clients makes it a critical function for PolyAI's success.

🌐 Work Environment

Office Type: PolyAI offers a hybrid work environment, balancing in-office collaboration with the flexibility of remote work. This model is designed to foster team cohesion and innovation while supporting employee well-being and autonomy.

Office Location(s): The primary stated location is London, England, United Kingdom. PolyAI may have additional office locations, but for this role, presence in or proximity to London for collaborative days is expected.

Workspace Context:

• Collaborative Focus: The hybrid model encourages in-office days for team meetings, brainstorming sessions, and building stronger interpersonal connections, which are crucial for complex problem-solving in AI development.

• Technology & Tools: Employees will have access to PolyAI's advanced technology stack, including development tools, AI platforms, and collaboration software necessary for designing and implementing sophisticated conversational agents.

• Team Interaction: Opportunities for regular interaction with direct reports, peers in Product and Engineering, and potentially with senior leadership, fostering a dynamic and engaged work environment.

Work Schedule: The role implies a standard full-time commitment (approximately 40 hours per week). However, the "flexible working from home policy" and the option to "Work from outside of the UK for up to 6 months each year" suggest a high degree of autonomy and flexibility in managing one's schedule, provided core responsibilities, team collaboration, and project deadlines are met.

📝 Enhancement Note: The emphasis on a hybrid model and global work flexibility indicates a modern, employee-centric approach to work, common in fast-growing tech companies. This environment is conducive to operations roles that require focused deep work balanced with collaborative problem-solving.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter or hiring manager will review applications to assess alignment with core requirements, focusing on leadership experience, technical background (Python, AI concepts), and conversational design expertise.

• Hiring Manager Interview: A discussion with the hiring manager to delve deeper into leadership philosophy, team management experience, technical depth in AI/conversational design, and strategic thinking. Candidates should be prepared to discuss their approach to building and developing teams.

• Team/Peer Interviews: Meetings with potential team members (Agent Designers, Engineers) and peers in Product/Engineering. These sessions will assess collaborative style, technical acumen, and cultural fit. Expect discussions on practical problem-solving and mentorship.

• Portfolio Review & Design/Technical Challenge: A critical stage where candidates present their portfolio, showcasing past work in conversational design, technical implementation, and leadership. A practical challenge, potentially involving designing a conversational flow for a specific use case or reviewing/refining existing technical implementation details, may be included.

• Final Interview: Likely with a senior leader (e.g., VP of Product/Engineering) to discuss strategic vision, long-term impact, and overall fit within PolyAI's leadership team.

Portfolio Review Tips:

• Showcase Leadership: Beyond individual contributions, highlight instances where you led teams to achieve significant design or technical milestones. Quantify team impact where possible.

• Bridge Design & Engineering: Clearly articulate how you translate design vision into actionable technical requirements and vice-versa. Use specific examples of prompt engineering, tool integration, or context management you've overseen or contributed to.

• Demonstrate Process Ownership: Present examples of processes you've developed or improved for agent design and development, emphasizing efficiency, quality, and scalability.

• Highlight User-Centricity: Explain how user feedback and data analysis informed design decisions and iterative improvements in your past projects.

• Be Ready for Technical Deep Dives: For candidates with an engineering background, be prepared to discuss Python code, AI concepts (LLMs, agentic frameworks), and technical challenges in depth. For design backgrounds, articulate the technical implications of design choices.

Challenge Preparation:

• Conversational Flow Design: Practice designing end-to-end conversational flows for various customer service scenarios. Focus on natural language, error handling, and achieving user goals efficiently.

• Technical Problem-Solving: Familiarize yourself with common challenges in conversational AI implementation, such as prompt optimization, managing context across turns, and integrating external tools.

• Team Management Scenarios: Prepare to discuss how you would handle common team management situations, such as performance issues, conflict resolution, or fostering innovation.

• AI Trend Awareness: Stay updated on the latest developments in agentic AI, LLMs, and conversational UX best practices.

📝 Enhancement Note: The interview process is designed to rigorously assess leadership, technical depth, and design sensibility. The portfolio review is central, requiring candidates to demonstrate their ability to manage complex AI product development from concept to execution, with a strong emphasis on team leadership and process.

🛠 Tools & Technology Stack

Primary Tools:

• Conversational Design Platforms: While specific platforms aren't listed, experience with tools used for dialogue flow mapping, state management, and intent recognition in conversational AI is crucial.

• Programming Languages: Proficiency in Python is explicitly required for code review and meaningful engagement. Candidates with an engineering background are expected to go deeper.

• AI/ML Frameworks: Familiarity with libraries and frameworks relevant to Large Language Models (LLMs), prompt engineering, and agentic AI development (e.g., LangChain, LlamaIndex, Hugging Face libraries) is highly preferred.

• Version Control Systems: Git is standard for code management and collaboration.

Analytics & Reporting:

• Analytics Platforms: Tools for analyzing conversational data, user behavior, and agent performance metrics. This could include custom dashboards or specialized AI analytics tools.

• Data Visualization Tools: To present insights on agent performance and user experience to stakeholders.

CRM & Automation:

• CRM Systems: While not directly mentioned for this role, an understanding of how AI agents integrate with CRM systems to access customer data or log interactions would be beneficial.

• Workflow Automation Tools: Familiarity with tools or concepts related to automating complex workflows, especially within AI agent orchestration.

📝 Enhancement Note: The explicit mention of Python and the strong preference for experience with LLMs, prompt engineering, and agentic frameworks (like LangChain) are key indicators of the technology stack. This role requires a leader who can navigate and guide the team within this advanced AI ecosystem.

👥 Team Culture & Values

Operations Values:

• Only the Best: This value translates to high expectations for performance, quality, and continuous self-improvement. For operations, this means striving for excellence in efficiency, accuracy, and impact.

• Ownership: A deep sense of responsibility for initiatives, decisions, and outcomes. Operations professionals are expected to proactively manage their areas and deliver results.

• Relentlessly Improve: A commitment to continuous, obsessive improvement. This aligns with operations' focus on process optimization, efficiency gains, and adapting to new technologies and methodologies.

• Bias for Action: A drive to take calculated risks and deliver impact quickly. In operations, this means being decisive, proactive in problem-solving, and efficient in execution.

• Disagree and Commit: A culture where diverse opinions are valued, but once a decision is made, the team fully commits to its success. This fosters healthy debate and unified execution.

• Build for People: Creating experiences that people (both end-users and internal teams) enjoy and benefit from. For operations, this means building user-friendly processes and systems that enhance productivity and satisfaction.

Collaboration Style:

• Cross-functional Integration: The role demands strong collaboration across design, engineering, product, and potentially client-facing teams to ensure cohesive development and successful deployment of AI agents.

• Feedback-Driven: A culture that encourages open feedback exchange, particularly around design quality, technical implementation, and process improvements.

• Knowledge Sharing: Encouraging the sharing of best practices, learnings from experiments, and insights from operational data to foster collective growth and innovation.

📝 Enhancement Note: PolyAI's values are strongly geared towards high performance, innovation, and a proactive, ownership-driven culture. These are critical for operations roles that manage complex systems and drive efficiency in a fast-paced tech environment.

⚡ Challenges & Growth Opportunities

Challenges:

• Rapidly Evolving AI Landscape: Staying ahead of the curve in agentic AI, LLMs, and conversational design requires continuous learning and adaptation. The challenge is to translate cutting-edge research into practical, scalable product features.

• Balancing Design Craft and Technical Rigor: Effectively leading a team that spans distinct disciplines—conversational UX design and software engineering—requires a leader who can deeply understand and bridge both worlds.

• Ensuring Human-Centricity in AI: Developing AI agents that feel intuitive and human, rather than robotic, is a persistent challenge, requiring meticulous attention to detail and user empathy.

• Process Scalability: Establishing and evolving processes that support rapid iteration and experimentation while ensuring the reliability and quality of deployed AI agents is crucial for growth.

Learning & Development Opportunities:

• Deep Specialization: Opportunities to become an expert in advanced AI concepts like multi-agent systems, sophisticated prompt engineering, and complex conversational AI orchestration.

• Industry Engagement: Potential to attend leading AI and UX conferences, contribute to industry discussions, and bring back new methodologies to the team.

• Leadership Development: Formal and informal opportunities to hone leadership skills, strategic thinking, and cross-functional influence within a high-growth tech company.

• Mentorship: Access to senior leadership and peers for guidance on navigating complex technical and leadership challenges.

📝 Enhancement Note: The primary challenges revolve around navigating the fast-paced AI field and managing a hybrid team of designers and engineers. Growth opportunities are strong, focusing on deepening AI expertise and expanding leadership capabilities within a cutting-edge company.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you led a team through a significant technical or design challenge in an AI product. What was your approach to problem-solving and how did you ensure successful delivery?" (Focus on leadership, process, technical depth, and impact.)

• "How would you approach setting standards for conversational quality and naturalness across multiple AI agents developed by your team? What metrics would you use to measure success?" (Assesses understanding of design authority, metrics, and operational quality control.)

Company & Culture Questions:

• "Based on our values (Only the Best, Ownership, Relentlessly Improve, Bias for Action, Disagree and Commit, Build for People), how do you see yourself embodying these in your role as an Agent Design Manager?" (Requires research into PolyAI's values and articulation of alignment.)

• "How do you foster a culture of continuous improvement and innovation within a technical and design team?" (Assesses leadership style and team-building approach.)

Portfolio Presentation Strategy:

• Structure for Impact: Organize case studies logically: Problem, your approach/solution (highlighting design and technical aspects), your role/leadership, implementation details (e.g., prompt engineering, tool use), results/impact (quantified if possible), and key learnings.

• Quantify Achievements: Whenever possible, use data to demonstrate the impact of your team's work or your direct contributions (e.g., improved conversion rates, reduced customer service costs, increased agent efficiency).

• Showcase Breadth and Depth: Include examples demonstrating both your leadership/management capabilities and your hands-on understanding of conversational design and technical implementation (Python, LLMs, agentic AI).

• Articulate Trade-offs: Be prepared to discuss the decisions made, the trade-offs considered (e.g., design vs. technical feasibility, speed vs. perfection), and the rationale behind them.

• Engage and Discuss: Present your portfolio interactively, inviting questions and discussion rather than just delivering a monologue. This demonstrates communication skills and collaborative spirit.

📝 Enhancement Note: Interview preparation should focus on demonstrating a blend of strong leadership, deep technical understanding of AI and conversational design, and a commitment to PolyAI's specific values and operational excellence.

📌 Application Steps

To apply for this Agent Design Manager position:

• Submit Your Application: Complete and submit your application through the provided link on Greenhouse. Ensure your resume and any supplementary materials are up-to-date.

• Tailor Your Resume: Highlight experience relevant to AI product management, conversational UX design, technical leadership (especially Python and AI concepts), and people management. Use keywords from the job description.

• Prepare Your Portfolio: Curate a portfolio that clearly showcases your leadership in managing design and engineering teams, your hands-on understanding of conversational AI development (including prompt engineering, tool integration, context management), and quantifiable results from past projects. Focus on case studies that demonstrate your ability to bridge design and technical implementation.

• Research PolyAI: Thoroughly understand PolyAI's mission, products, and company values. Prepare to discuss how your experience and leadership style align with their culture and goals, particularly in the context of advancing conversational AI.

• Practice Your Pitch: Rehearse your presentation of your portfolio and prepare thoughtful answers to common interview questions, especially those related to leadership, technical challenges in AI, and collaboration.

⚠️ 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.