Engineering Manager (Artificial Intelligence)

Anaplan; Manchester; On-site; GBP 120,000 - 170,000; Full time

Job summary

Anaplan in Manchester is seeking a hands-on Technical Lead to build and lead our Enterprise Grade AI Platform. You’ll drive the conversational AI and agentic AI roadmap while mentoring a team of 5–8 engineers and remaining hands-on.

You will manage end-to-end delivery, collaborate with product management, establish engineering best practices, and ensure CI/CD pipelines and rigorous testing for reliable AI applications.

Qualifications

• Experience leading AI/ML engineering teams to deliver complex projects.
• Hands-on ability to build and deploy AI applications in production.
• Strong leadership, mentoring, and stakeholder management.
• Deep knowledge of LLMs, prompt engineering, and conversational AI patterns.
• Background in distributed systems, microservices or cloud-native architectures.
• Familiarity with RAG, vector stores and semantic search.

Responsibilities

• Lead a team of 5–8 AI engineers, driving technical excellence and delivery.
• Own the AI feature roadmap and align with product management priorities.
• Build and maintain CI/CD pipelines for AI applications with testing.
• Oversee end-to-end development of conversational AI features in production.
• Collaborate with AI Solutions Architects to translate architecture into plans.
• Mentor engineers and promote cohesive, high-performing teams.
• Communicate progress, risks and technical decisions to leadership.

Skills

Agile/Scrum

AI engineering leadership

Python

LLM APIs

Distributed systems

CI/CD

RAG systems

Job description

Responsibilities

• We’re looking for a hands-on Technical Lead to build and lead our Enterprise Grade AI Platform
• You’ll drive execution of our conversational AI, Generative and agentic AI roadmap, managing a team of talented engineers while remaining hands-on yourself
• This role requires both exceptional leadership skills and the ability to roll up your sleeves and solve complex technical problems
• Lead, mentor, and grow a team of 5-8 AI engineers, fostering a culture of technical excellence, innovation, and delivery
• Drive end-to-end execution of conversational AI features that enable users to interact with Anaplan models through natural language
• Oversee the development of agentic AI systems that can autonomously analyse data, generate insights, and execute planning workflows
• Own the team’s delivery roadmap, working closely with product management to prioritise features and manage technical trade-offs
• Establish engineering best practices for AI development, including testing strategies, evaluation frameworks, and deployment patterns
• Lead sprint planning, technical design reviews, and retrospectives to ensure consistent delivery velocity and quality
• Collaborate with AI Solutions Architects to translate architectural vision into executable engineering plans
• Build and maintain CI/CD pipelines for AI applications, including automated testing and prompt regression suites
• Partner with platform teams to ensure AI features integrate seamlessly with Anaplan’s core infrastructure
• Communicate progress, risks, and technical decisions to senior leadership and cross-functional stakeholders

Requirements

• Strong project management skills with experience using Agile/Scrum methodologies
• Strong hands-on experience building and deploying AI applications in production
• Proven track record of delivering complex technical projects on time with high quality
• Experience with agentic frameworks and autonomous agent architectures
• Demonstrated ability to mentor engineers and build cohesive, productive teams
• Proficiency in Python and modern software development practices (testing, code review, CI/CD)
• Software engineering experience while leading engineering teams
• Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns
• Excellent communication and stakeholder management abilities
• Background in distributed systems, microservices, or cloud-native architectures
• Familiarity with model fine-tuning, evaluation, and continuous improvement workflows
• Knowledge of financial planning, analytics, or business intelligence domains
• Experience with RAG systems, vector databases, and semantic search
• Experience leading teams in fast-growing startups or enterprise software companies