About this role
Anaplan requires a hands-on technical lead to bridge the gap between architectural vision and execution for an enterprise-grade AI platform. This hire will solve the challenge of scaling conversational, generative, and agentic AI capabilities that allow users to interact with planning models through natural language.
Working in Manchester, the engineering manager will direct a team of five to eight AI engineers while maintaining a direct hand in technical problem-solving. Success in this position requires a blend of software engineering leadership, production-level AI deployment experience, and collaborative project management.
What you will do
- Lead, mentor, and grow a team of five to eight AI engineers while fostering a culture of technical excellence.
- Drive the end-to-end execution of conversational AI features that enable users to interact with models through natural language.
- Oversee the development of agentic AI systems designed to autonomously analyze data, generate insights, and execute planning workflows.
- Own the team delivery roadmap and collaborate with product management to prioritize features and handle technical trade-offs.
- Establish engineering best practices for AI development, covering testing strategies, evaluation frameworks, and deployment patterns.
- Build and maintain CI/CD pipelines for AI applications, including automated testing and prompt regression suites.
What you need
- Bring software engineering experience alongside a background in leading engineering teams.
- Demonstrate strong hands-on experience building and deploying AI applications in production environments.
- Possess deep knowledge of large language model APIs, prompt engineering, and conversational AI patterns.
- Show proficiency in Python and modern software development practices such as testing, code review, and CI/CD.
- Exhibit a proven track record of delivering complex technical projects on time with high quality.
- Display strong project management skills utilizing Agile and Scrum methodologies.
Nice to have
- Experience leading teams in fast-growing startups or enterprise software companies
- Knowledge of financial planning, analytics, or business intelligence domains
- Experience with RAG systems, vector databases, and semantic search
- Familiarity with model fine-tuning, evaluation, and continuous improvement workflows
- Background in distributed systems, microservices, or cloud-native architectures
Skills and tech stack
Questions candidates ask
What team will I be managing?
You will lead, mentor, and grow a team of 5-8 AI engineers, fostering a culture of technical excellence, innovation, and delivery. This team focuses on building and maintaining an enterprise-grade AI platform with conversational, generative, and agentic AI capabilities.
Will I still write code in this role?
Yes, this role requires both exceptional leadership skills and the ability to roll up your sleeves and solve complex technical problems. You will remain hands-on yourself while managing a team of talented engineers.
How does the team handle development workflows?
You will establish engineering best practices for AI development, including testing strategies, evaluation frameworks, and deployment patterns. The position also involves leading sprint planning, technical design reviews, and retrospectives to ensure consistent delivery velocity and quality.