ABOUT THE ROLE 

This role sits within Anaplan's IT Customer Experience organization and is focused on transforming how Anaplan employees work. You will design, build, and scale AI tools, agents, and capabilities that drive productivity, smarter decision-making, and operational efficiency across our global workforce. 

Anaplan is building its Enterprise AI Center of Excellence (COE) — a one-stop shop for all internal AI at Anaplan — and is looking for an AI Principal Architect to lead it from a technical standpoint. This is a senior, newly created role at the intersection of hands-on enterprise AI engineering, internal system architecture, technical leadership, and workforce enablement. 

The AI Principal Architect will own the technical vision for Anaplan's internal AI — designing the reference architecture for LLMs, agentic AI, and Gemini Enterprise; setting engineering standards; evaluating emerging platforms; and ensuring every employee-facing initiative is built with rigor, scalability, and responsible design. 

This role carries a hybrid profile: deep individual technical contribution combined with team leadership influence. You will mentor engineers, guide architectural decisions, serve as the primary technical escalation point, and contribute a forward-looking perspective to the 2–3 year AI technology roadmap — without necessarily holding formal management authority over all contributors. 

You will report directly to the Director, IT Customer Experience, who co-leads the Enterprise AI COE alongside the Financial Flexibility Lead and a GTM Champion as a 3-in-a-box. You will collaborate closely with Technical/Engineering teams (dotted-line, for agent development and delivery) and the Transformation & Financial Flexibility team (to identify AI-driven cost-saving opportunities). 

KEY RESPONSIBILITIES 

Reference Architecture & Enterprise AI Engineering 

• Own and publish the reference architecture for Anaplan's internal AI — covering LLMs, agentic AI frameworks, Gemini Enterprise integrations, and data pipelines. 

• Architect end-to-end internal enterprise AI solutions designed for the scale, security, and reliability requirements of a global workforce. 

• Set and enforce AI engineering standards, coding practices, code review processes, and technical guardrails across all internal AI projects. 

• Lead hands-on technical design reviews and guide implementation decisions from intake through production deployment. 

• Evaluate, select, and onboard new enterprise AI platforms and tools — providing technical recommendations grounded in internal workforce needs. 

• Design the LLM abstraction layer and multi-model strategy to optimize cost, performance, and flexibility. 

• Own technical debt management, system observability, and scalability planning for Anaplan's internal AI systems. 

AI Platform Governance & Enablement 

• Define and maintain technical evaluation criteria for the AI intake process — assessing feasibility, build complexity, security risk, and integration requirements for employee-facing tools. 

• Ensure all internal AI initiatives pass engineering, security, compliance, and responsible AI review before development begins. 

• Maintain enterprise AI technical policies, engineering standards, and responsible AI guardrails in partnership with Security and Compliance. 

• Translate approved internal use cases into clear technical specifications and hand off to engineering teams with full architectural context. 

• Define enterprise AI data layer and integration architecture across core systems (Salesforce, ServiceNow, Gainsight, Workday). 

• Integrate with ServiceNow AI Control Tower to track all AI use cases, agents, and realized business value. 

• Implement human-in-the-loop, explainability, and auditability frameworks for all decision-impacting AI systems. 

• Partner with Finance to define and measure AI-driven ROI, ensuring alignment with enterprise value targets. 

• Establish full lifecycle management for AI agents, including monitoring, feedback loops, and continuous improvement. 

Technical Team Leadership 

• Provide technical direction, coaching, and mentorship to engineers across the AI Governance & Enablement and AI Operations & Insights teams. 

• Serve as the primary technical escalation point for complex internal AI delivery challenges and architecture decisions. 

• Partner with Technical/Engineering teams (dotted-line) on agent architecture, build quality, and delivery timelines. 

• Help define the technical bar for AI team hiring and contribute to onboarding and skills development programs. 

• Foster a culture of engineering rigor, experimentation, and continuous improvement across the internal AI function. 

AI Operations & Workforce Adoption 

• Oversee the technical deployment and operationalization of AI agents and solutions, ensuring production readiness and stability for Anaplan employees. 

• Drive Gemini Enterprise adoption and lead AI Friday sessions with genuine technical depth. 

• Build and maintain engineering dashboards tracking internal AI system performance, adoption rates, and ROI metrics. 

• Translate engineering decisions into executive-ready business value narratives for the Director, CIO, and Finance audiences. 

Innovation, R&D & Emerging Technology 

• Research and prototype emerging AI/ML techniques, large language models, agent frameworks, and enterprise tooling to identify internal productivity and cost-saving opportunities. 

• Design and lead proof-of-concept pilots that validate novel internal use cases before committing to full engineering investment. 

• Build and maintain the AI innovation pipeline — a living backlog of high-potential experiments. 

• Contribute the technical perspective on where internal AI capabilities should be invested over the next 2–3 years, collaborating with the Director on the roadmap. 

Cross-Functional Technical Partnership 

• Work hand in hand with the Transformation & Financial Flexibility team to identify and technically validate AI-driven cost-saving opportunities in Anaplan's internal operations. 

• Act as technical advisor and AI subject matter expert to business units identifying internal AI use cases. 

• Support the 3-in-a-box COE co-leadership (IT, Finance, GTM) with technical analysis, architecture reviews, and feasibility assessments. 

• Build trusted technical relationships across Engineering, Security, Compliance, Legal, and HR. 

REQUIRED QUALIFICATIONS 

• 7+ years of software or AI/ML engineering experience, with at least 3 years in a technical lead, staff engineer, or principal-level role — ideally with exposure to enterprise IT or internal tooling environments. 

• Deep hands-on expertise across the AI/ML stack: LLMs, retrieval-augmented generation (RAG), agent frameworks, or MLOps pipelines — with experience in enterprise or workforce deployment contexts. 

• Proven experience architecting and deploying enterprise-scale internal AI systems from design through production, including reliability, observability, and performance engineering. 

• Proficiency in Python and enterprise cloud AI platforms (GCP Vertex AI, Azure AI, or AWS SageMaker) and AI orchestration tooling. 

• Hands-on experience with Google Workspace AI and Gemini Enterprise, or equivalent enterprise AI platforms (e.g., Microsoft Copilot, OpenAI Enterprise). 

• Demonstrated ability to provide technical leadership, mentorship, and architectural guidance to engineering teams without formal management authority. 

• Ability to manage competing priorities, dependencies, and delivery timelines across multiple workstreams. 

• Strong business acumen and communication skills — able to translate complex enterprise AI/ML concepts into business value narratives for C-level audiences. 

• Experience in enterprise SaaS environments with complex stakeholder landscapes, security requirements, and compliance obligations. 

PREFERRED QUALIFICATIONS 

• Experience with AI governance frameworks, responsible AI principles, or enterprise AI policy and risk management for internal deployments. 

• Familiarity with ServiceNow or similar ITSM platforms and integration patterns. 

• Background in enterprise change management, internal AI enablement, or large-scale digital transformation programs. 

• Experience working with cross-functional finance or business transformation teams on AI-driven cost optimization. 

• Prior experience in an internal IT or enterprise technology function at a high-growth SaaS company. 
• Enterprise technology function at a high-growth SaaS company. 

MaintainX est la première plateforme mobile au monde dédiée à la gestion des actifs et des tâches dans les environnements industriels et de première ligne. Nous proposons une solution moderne, basée sur l'IoT et le cloud, qui facilite la maintenance, la sécurité et l'exploitation des équipements et installations physiques.

Nous aidons plus de 12 000 organisations, dont Duracell, Univar Solutions, Titan America, McDonald's, Brenntag, Cintas, Xylem et Shell, à atteindre l'excellence opérationnelle et la fiabilité à grande échelle.

À la suite de notre série D de 150 millions de dollars menée par Bain Capital Ventures, Bessemer Ventures, August Capital, Amity Ventures et Ridge Ventures, MaintainX a levé un total de 254 millions de dollars, valorisant la société à 2,5 milliards de dollars.

Alors que nous entrons dans notre prochaine phase de croissance, nous investissons massivement dans l'IA/ML, les LLM et l'IoT industriel afin de transformer le mode de fonctionnement des équipes de première ligne, en prédisant les pannes avant qu'elles ne se produisent, en automatisant les flux de travail et en intégrant l'intelligence dans chaque actif et chaque procédure.

Le poste

Nous recherchons un développeur(se) senior en apprentissage automatique appliqué hautement qualifié et motivé pour orienter la direction technique et l'architecture de nos initiatives en matière de maintenance prédictive et d'intelligence des actifs.

Vous combinerez une expertise approfondie en apprentissage automatique avec de solides compétences en génie logiciel et en sens du leadership. Vous encadrerez des ingénieurs, développerez des systèmes et piloterez la feuille de route pour l'intelligence de maintenance basée sur l'IA sur des milliers de sites industriels.

Ce poste se situe à la croisée de l'architecture d'apprentissage automatique, des systèmes de données IoT et de l'impact des produits, et constitue le fondement de la stratégie d'IA prédictive et générative de MaintainX.

Ce que vous ferez:

• Diriger la direction technique pour la maintenance prédictive, la détection des anomalies et l'intelligence alimentée par LLM dans tous les produits MaintainX.
• Concevoir des systèmes ML de bout en bout, de l'ingestion des données et le développement des fonctionnalités à la formation, au déploiement et à la surveillance des modèles.
• Encadrer une équipe croissante de développeurs(ses) ML et de données, en inculquant les meilleures pratiques en matière d'expérimentation, d'évaluation et de gestion du cycle de vie des modèles.
• Collaborer avec les responsables des produits et de développement afin d'aligner la feuille de route de l'IA sur les besoins des clients et les objectifs commerciaux.
• Concevoir des boucles de données et de rétroaction fiables qui relient la télémétrie des clients et les commentaires des opérateurs au réentraînement des modèles.
• Optimiser les performances grâce à des techniques telles que la quantification, la distillation et le service d'inférence évolutif.
• Travailler avec des cadriciels LLM (LangChain, LlamaIndex, Hugging Face) pour créer des systèmes de raisonnement et des flux de travail agentifs pour l'intelligence des actifs et du travail.
• S'assurer que l'infrastructure ML répond aux normes de production en matière de latence, de fiabilité, d'explicabilité et de sécurité.

À propos de vous:

• Plus de 7 ans d'expérience dans le domaine de l'apprentissage automatique, de la science des données ou de l'IA appliquée.
• Expertise en Python et excellente maîtrise de PyTorch, TensorFlow et des piles ML cloud (AWS, Databricks ou similaires).
• Expérience avérée dans le déploiement à grande échelle de systèmes ML de production, et pas seulement de prototypes.
• Solide expérience en LLM, modélisation de séries chronologiques et détection d'anomalies pour les données du monde réel.
• Capacité avérée à diriger les décisions architecturales, à encadrer les développeurs(ses) et à collaborer avec les équipes chargées des produits, des données et des plateformes.
• Connaissance des outils MLOps (Docker, Kubernetes, Weights & Biases, MLflow, SageMaker).
• Diplôme de deuxième cycle (master/doctorat) en informatique, apprentissage automatique ou dans un domaine connexe préféré.

Une attention particulière est accordée aux candidats présentant les caractéristiques suivantes:

• Expérience avec l'OCR pour l'extraction de données structurées à partir de documents.
• Expérience dans la modélisation de séries chronologiques pour la maintenance prédictive et la détection d'anomalies.
• Connaissance des systèmes IoT industriels (capteurs, télémétrie, edge computing).
• Expérience dans l'application de l'apprentissage par renforcement ou des architectures agentuelles pour les systèmes de prise de décision et de contrôle.
• Contributions à des frameworks ML open source ou à la recherche dans les domaines de la fiabilité, de l'explicabilité ou des jumeaux numériques.

Quels sont les avantages pour vous?:

• Un salaire compétitif et des opportunités d'équité significatives.
• Couverture des soins de santé, des soins dentaires et de la vue.
• Programme d'inscription 401(k) / RRSP.
• Prenez les congés dont vous avez besoin.
• Une culture du travail :
• Vous travaillerez avec des personnes intelligentes, humbles et optimistes à travers le monde.
• Un environnement méritocratique où les idées et les résultats sont publiquement célébrés.

Qui sommes-nous:

MaintainX s'engage à créer un environnement diversifié. Tous les candidats qualifiés seront pris en considération pour un emploi sans considération de race, de couleur, de religion, de sexe, d'identité ou d'expression de genre, d'orientation sexuelle, d'origine nationale, de génétique, d'invalidité, d'âge ou de statut d'ancien combattant.

MaintainX is the world’s leading mobile-first Asset and Work Intelligence platform for industrial and frontline environments. We’re a modern, IoT-enabled, cloud-based solution that powers maintenance, safety, and operations on physical equipment and facilities.

We help 12,000+ organizations—including Duracell, Univar Solutions, Titan America, McDonald’s, Brenntag, Cintas, Xylem, and Shell—achieve operational excellence and reliability at scale.

Following our $150 million Series D led by Bain Capital Ventures, Bessemer Ventures, August Capital, Amity Ventures, and Ridge Ventures, MaintainX has raised a total of $254 million, valuing the company at $2.5 billion.

As we enter our next phase of growth, we’re investing deeply in AI/ML, LLMs, and Industrial IoT to transform how frontline teams operate—predicting failures before they happen, automating workflows, and embedding intelligence into every asset and procedure.

The Role

We are seeking a highly skilled and motivated Senior Applied Machine Learning Developer to guide the technical direction and architecture of our Predictive Maintenance and Asset Intelligence initiatives.

You’ll combine deep ML expertise with strong software development and leadership skills—mentoring developers, scaling systems, and driving the roadmap for AI-enabled maintenance intelligence across thousands of industrial sites.

This role sits at the intersection of ML architecture, IoT data systems, and product impact, shaping the foundation for MaintainX’s predictive and generative AI strategy.

What you’ll do:

• Lead technical direction for predictive maintenance, anomaly detection, and LLM-powered intelligence across MaintainX products.
• Architect end-to-end ML systems—from data ingestion and feature development to model training, deployment, and monitoring.
• Mentor a growing team of ML and data developers, instilling best practices for experimentation, evaluation, and model lifecycle management.
• Partner with product and software development leaders to align AI roadmap with customer needs and business goals.
• Design reliable data and feedback loops that connect customer telemetry and operator feedback to model retraining.
• Drive performance optimization through techniques like quantization, distillation, and scalable inference serving.
• Work with LLM frameworks (LangChain, LlamaIndex, Hugging Face) to build reasoning systems and agentic workflows for asset and work intelligence.
• Ensure ML infrastructure meets production standards for latency, reliability, explainability, and security.

About you:

• 7+ years of experience in Machine Learning, Data Science, or Applied AI.
• Expertise in Python, and strong familiarity with PyTorch, TensorFlow, and cloud ML stacks (AWS, Databricks, or similar).
• Proven experience deploying production ML systems—not just prototypes—at scale.
• Strong background in LLMs, time-series modeling, and anomaly detection for real-world data.
• Demonstrated ability to lead architectural decisions, mentor developers, and collaborate across product, data, and platform teams.
• Knowledge of MLOps tooling (Docker, Kubernetes, Weights & Biases, MLflow, SageMaker).
• Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field preferred.

Bonus skills: 

• Experience with OCR for extracting structured data from documents.
• Background in time-series modeling for predictive maintenance and anomaly detection.
• Familiarity with Industrial IoT systems (sensors, telemetry, edge computing).
• Experience applying reinforcement learning or agentic architectures for decision-making and control systems.
• Contributions to open-source ML frameworks or research in reliability, explainability, or digital twins.

What’s in it for you:

• Competitive salary and meaningful equity opportunities.
• Healthcare, dental, and vision coverage.
• 401(k) / RRSP enrollment program.
• Take what you need PTO.
• A high impact Culture:
• You’ll work with Smart, Humble Optimists across the globe.
• Meritocratic environment where ideas and outcomes are publicly celebrated.

About us:

We exist to make the lives of frontline and maintenance teams easier by building software that meets their real-world needs. Our product transforms how 80% of the global workforce—those who don’t sit behind a desk—manage their operations, assets, and teams.

MaintainX is committed to creating a diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

We are seeking a Data Engineer to join our dynamic team. The ideal candidate is an enthusiastic problem-solver who excels at building scalable data systems and has hands-on experience with Databricks, Looker, AWS, MongoDB, PostgreSQL, and Terraform. You will work alongside sales, customer success and engineering to design, implement, and maintain the operational data infrastructure that powers our analytics and platform offerings.

What you'll do:

1. Data Pipeline & Integration
• Design, build, and maintain end-to-end data pipelines using Databricks (SparkSQL, PySpark) for data ingestion, transformation, and processing.
• Integrate data from various structured and unstructured sources, including medical imaging systems, EMRs, Change-Data-Capture from SQL Databases, and external APIs.
2. Analytics & Visualization
• Collaborate with the analytics team to create, optimize, and maintain dashboards in Looker.
• Implement best practices in data modeling and visualization for operational efficiency.
3. Cloud Infrastructure
• Deploy and manage cloud-based solutions on AWS (e.g., S3, EMR, Lambda, EC2) to ensure scalability, availability, and cost-efficiency using IaC tooling (Terraform and Databricks Asset Bundles).
• Develop and maintain CI/CD pipelines for data-related services and applications.
4. Database Management
• Oversee MongoDB and PostgreSQL databases, including schema design, indexing, and performance tuning.
• Ensure data integrity, availability, and optimized querying for both transactional and analytical workloads.
5. Security & Compliance
• Adhere to healthcare compliance requirements (e.g., HIPAA) and best practices for data privacy and security.
• Implement error handling, logging, and monitoring frameworks to ensure reliability and transparency.
• Implement data governance frameworks to maintain data integrity and confidentiality.
6. Collaboration & Documentation
• Work cross-functionally with data scientists, product managers, and other engineering teams to gather requirements and define data workflows.
• Document data pipelines, system architecture, and processes for internal and external stakeholders.

About you:

• Education & Experience
• 7+ years of professional experience in data engineering or a similar role.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Technical Skills
• Databricks (Spark): Proven expertise in building large-scale data pipelines.
• Looker: Experience in creating dashboards, data models, and self-service analytics solutions.
• AWS: Proficient with core services like S3, EMR, Lambda, IAM, EC2, etc.
• MongoDB & PostgreSQL: Demonstrated ability to design schemas, optimize queries, and manage high-volume databases.
• SQL & Scripting: Strong SQL skills, plus familiarity with Python, Scala, or Java for data-related tasks.
• Soft Skills
• Excellent communication and team collaboration abilities.
• Strong problem-solving aptitude and analytical thinking.
• Detail-oriented, with a focus on delivering reliable, high-quality solutions.
• Preferred
• Experience in healthcare or imaging (e.g., DICOM, HL7/FHIR).
• Familiarity with DevOps tools (Docker, Kubernetes, Terraform) and CI/CD pipelines.
• Knowledge of machine learning workflows and MLOps practices.

The base salary range for this position is $120,000 - $180,000.  Our job postings cover multiple career levels and individual compensation will depend on various factors, including qualifications, skills, experience, location, and applicable laws. In addition to base salary, this role is eligible to participate in our equity incentive and competitive benefits plans.