At Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.
What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.
Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.
Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.
Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!
- Contribute to the architecture and take ownership of the design, development, and deployment of scalable Generative AI and Machine Learning systems into production environments.
- Develop end-to-end GenAI features, including backend API services, model integration, model monitoring, evaluations, and deployments.
- Integrate and optimize LLMs for specific business planning use cases, including prompt engineering and RAG implementation.
- Build cutting-edge conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language.
- Implement evaluation frameworks to measure and improve GenAI feature quality, including accuracy, latency, and user satisfaction metrics.
- Design and develop APIs that expose AI capabilities to Anaplan's platform and third-party integrations.
- Optimize model inference pipelines for performance, cost, and scalability in production environments.
- Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behavior.
- Participate in code reviews, lead technical design discussions, and mentor junior and mid-level engineers.
- Extensive hands-on experience in AI, ML, or related engineering fields.
- End-to-end exposure in model lifecycle development, including demonstrated experience deploying and maintaining ML models in production environments.
- Strong knowledge of LLM APIs, prompt engineering, and conversational AI patterns.
- Experience in fine-tuning LLMs for domain-specific enterprise applications.
- Experience with MLOps and LLMOps, ensuring scalable, reliable, and monitorable model deployments.
- Worked with agentic frameworks and autonomous agent architectures.
- Proficiency in Python and modern software development practices (testing, code review, CI/CD).
- Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models.
- Experience with model serving frameworks (vLLM, TensorRT, Ray).
- Experience with A/B testing and experimentation frameworks for AI features.
- Experience with model observability tools (LangSmith, W&B, MLflow).
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Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)
We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day!
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.
Fraud Recruitment Disclaimer
It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.
Anaplan does not:
- Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.
- Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.
All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to [email protected] before taking any further action in relation to the correspondence.
Skills Required
- Extensive hands-on experience in AI, ML, or related engineering fields.
- End-to-end model lifecycle development, deploying and maintaining ML models in production.
- Strong knowledge of LLM APIs, prompt engineering, and conversational AI patterns.
- Experience fine-tuning LLMs for domain-specific enterprise applications.
- Experience with MLOps and LLMOps for scalable, reliable model deployments.
- Experience with agentic frameworks and autonomous agent architectures.
- Proficiency in Python and modern software development practices (testing, code review, CI/CD).
- Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models.
- Experience with model serving frameworks (vLLM, TensorRT, Ray).
- Experience with A/B testing and experimentation frameworks for AI features.
- Experience with model observability tools (LangSmith, W&B, MLflow).
Anaplan Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Anaplan and has not been reviewed or approved by Anaplan.
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Strong & Reliable Incentives — Earnings potential in sales is considered good or fair, with on‑target earnings achievable when plans are met. This indicates variable pay can meaningfully boost total compensation when targets are hit.
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Healthcare Strength — Medical, dental, and vision coverage are described as strong, complemented by mental‑health resources and EAP support. Company‑wide paid wellbeing days reinforce the health and wellness focus.
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Parental & Family Support — Equitable parental and caregiver leave are highlighted alongside fertility and adoption support. Family‑forming programs such as Carrot are part of the offering.
Anaplan Insights
What We Do
Anaplan is building a future where connected leaders and teams are able to constantly adapt, transform and reinvent their businesses. We make it possible to share actionable insights, empower and unleash creativity, and drive innovation. With Anaplan, finance and operational leaders across the organization can model complex scenarios, forecast continuously with added intelligence, and make agile decisions with confidence.
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