Jobs at Anaplan

Lead and mentor a team of 5–8 AI engineers while driving delivery of conversational, generative, and agentic AI capabilities. Own the AI engineering roadmap, technical execution, testing and evaluation frameworks, CI/CD pipelines, and integration with core infrastructure. Partner with product, architecture, platform, and senior leadership teams to manage priorities, technical trade-offs, risks, and delivery. Remain hands-on in solving complex AI engineering problems and developing production-ready systems.

Lead the architecture, development, deployment, and optimization of production Generative AI and machine learning systems. Build end-to-end AI features, APIs, conversational interfaces, agentic workflows, RAG implementations, evaluation frameworks, and model monitoring. Optimize inference for performance, cost, and scalability while collaborating with data scientists to productionize models and forecasting algorithms. The role requires strong Python software engineering, LLM integration, prompt engineering, fine-tuning, MLOps, and LLMOps expertise.

Lead the architecture and production deployment of generative AI and machine learning systems. Build end-to-end AI features, APIs, conversational interfaces, agentic workflows, RAG implementations, evaluation frameworks, monitoring, and inference pipelines. Integrate and fine-tune LLMs for enterprise planning applications while optimizing performance, cost, scalability, and reliability. Collaborate with data scientists to productionize ML models and forecasting algorithms.

Lead end-to-end enterprise Anaplan implementations across the UKI market. Responsibilities include project governance, scoping, budgeting, forecasting, billing, risk and resource management, stakeholder engagement, executive communication, escalation handling, project recovery, Agile delivery, consensus building, and portfolio reporting. The role serves as a strategic customer advisor while coordinating internal teams and external partners to deliver successful, scalable solutions.

Lead a six-person Platform Engineering team responsible for GitOps deployment pipelines, Argo CD, feature flagging, developer tooling, non-production environments, orchestration, and self-healing systems. Coach engineers, manage delivery and on-call operations, establish environment governance, collaborate cross-functionally, and define platform strategy. Build automation for test data, user identities, environment provisioning, service hydration, rollback, and local development workflows.

Lead a DevOps team responsible for building, scaling, securing, and optimizing ML and GenAI infrastructure. Define cloud infrastructure roadmaps, automate provisioning, architect MLOps and LLMOps pipelines, deploy LLMs to production, and manage AI infrastructure budgets through FinOps practices. Implement resource-efficiency measures, observability, incident response, data governance, and security controls while collaborating with Data Science and Engineering leaders.

Own sales forecasting and pipeline reporting on the Anaplan platform. Partner with Field Operations and cross-functional teams to deliver reporting for forecasting, pipeline management, account planning, territories, strategic initiatives, and performance tracking. Ensure data accuracy across systems, translate business requirements into technical reporting solutions, coordinate priorities across teams, and communicate reporting changes to stakeholders.

Own and develop Anaplan’s Threat Intelligence function, including strategy, lifecycle, tooling, integrations, threat hunting, incident response support, intelligence research, detection content, and executive briefings. Build automated workflows across SIEM, SOAR, and EDR/XDR platforms; develop hunt methodologies and detections aligned with MITRE ATT&CK; and communicate actionable findings to technical and CISO-level stakeholders.

Design and lead enterprise GenAI, conversational AI, and agentic AI architectures for Anaplan’s planning platform. Define architecture patterns, APIs, data models, prompt engineering frameworks, observability, evaluation, guardrails, and scalable production systems. Collaborate with product, engineering, and data science teams; evaluate AI technologies; lead architecture reviews; and mentor engineers delivering secure, reliable AI solutions for forecasting, scenario planning, and financial modeling.

Generate inbound and outbound sales opportunities across key markets through calls, email, and social prospecting. Partner with enterprise sales representatives on account-based strategies, build relationships with target accounts, communicate the value of Anaplan’s planning platform, and consistently achieve activity and sales performance targets. The role requires native or bilingual German fluency and fluent English, with opportunities for training in value-based selling.

Sell Anaplan's connected planning platform to enterprise prospects in London. Hunt new logos, manage opportunities end-to-end, present to C-suite, apply value-based selling, forecast pipeline, and coordinate with Sales Development, Solutions Consultants, Marketing, and Customer Success to close and expand accounts.

Generate qualified sales opportunities via inbound follow-up and targeted outbound prospecting. Collaborate with enterprise reps on account-based strategies, conduct value-based conversations, and meet weekly/monthly metrics to hand off leads to enterprise sales.

Design, scale, and maintain cloud-native MLOps and LLMOps infrastructure. Provision GPU orchestration, optimise compute/network/storage, build CI/CD and MLOps pipelines, deploy LLMs with inference engines, automate with IaC, monitor model/data drift and latency, and manage cloud GPU cost and observability.

Lead a DevOps team to design, build, and operate scalable, secure MLOps/LLMOps infrastructure and CI/CD for GenAI. Manage cloud FinOps, optimize GPU/CPU spend, implement auto-scaling and observability, enforce data governance, and run 24/7 incident response for production LLM deployments.

The Principal Data Engineer will design and build AI features, manage data pipelines, and collaborate with data scientists to enhance machine learning models and their implementations.

Lead and grow a team of 5–8 AI engineers to build an enterprise AI platform delivering conversational, generative, and agentic AI features. Drive end-to-end execution, establish AI engineering best practices, maintain CI/CD pipelines, collaborate with product and platform teams, and communicate technical progress and risks to stakeholders.

Design, develop, and deploy scalable ML and time-series forecasting engines integrated into Anaplan applications. Lead customer onboarding and customize models to client data, build feature pipelines (SQL/Python/dbt), and operationalize models via MLOps tools (MLflow, Optuna). Collaborate with Product, Engineering, and Customer Success to deliver production-grade, monitored solutions.

Lead the development and integration of AI solutions, focusing on advanced modeling, generative AI architecture, and building user interfaces for decision-making tools.