Manager, Software Development

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 whos who in the Fortune 50. Coca-Cola LinkedIn Adobe LVMH and Bayer are just a few of the 2400 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 youll be inspired connected developed and rewarded here. Everything that makes you unique is welcome; join us and lets build whats next - together!

About the Role

Anaplan is seeking a strong TechLeadto join our Predictive Insights team the group responsible for designing building andoperatingthe machine learning systems that deliver classification-driven intelligence across Anaplans Connected Planning this role you will serve as the technical authority for a cross-functional squad of Backend Frontend and QA engineers guiding everything from model design and data engineering to production deployment and observability.

You will own the end-to-end lifecycle of classification models and ML pipelines: from prototyping in Python and feature-store integration throughcontaineriseddeployment on Kubernetes to real-time serving backed by Redis and MongoDB. As a hands-onleaderyou will set architectural standards mentor engineers at all levels and work closely with Product and Data Science to translate customer needs into reliable scalable predictive capabilities.

Key Responsibilities

Technical Leadership

• Lead the design development and deployment of production-grade ML pipelines for classification tasks including binary multi-class and multi-label models.

• Define the end-to-end ML lifecycle: data ingestion feature engineering model training evaluation deployment and continuous monitoring.

• Establish coding standards design-review practices and engineering excellence benchmarks for the team.

• Drive architectural decisions across the full stack including Python servicescontainerisedworkloads on Kubernetes and data-layer integrations with MongoDB and Redis.

• Conduct rigorous code reviews and technical deep-dives ensuring quality performance and security across all layers.

Team Leadership & People Management

• Manage and mentor a diverse teamcomprisingBackend Engineers Frontend Engineers and QA Engineers adapting leadership style to each discipline.

• Own individual growth plans performance feedback cycles and career development conversations for direct reports.

• Foster a culture of psychological safety continuous learning and technical curiosity across a geographically distributed team.

• Partner with Engineering Managers and cross-functional leads to balance workloads remove blockers andmaintaindelivery velocity.

• Actively recruit interview and onboard strong engineering talent in India.

ML Pipelines & Classification Models

• Architect andmaintainscalable ML pipelines from raw data processing through to model serving using Python-first tooling (scikit-learnXGBoostLightGBMPyTorch).

• Own model selection hyperparameter tuning cross-validation strategies and performance benchmarking for classification workloads.

• Integrate feature stores and ensure reproducible version-controlled experiments using tools such asMLflowor similar.

• Define and enforce model monitoring drift detection and retraining policies in production.

• Collaborate with Data Scientists tooperationaliseresearch prototypes into robust maintainable services.

Infrastructure & Platform

• Lead adoption of Kubernetes (k8s) best practices: pod design resource management horizontal scaling health checks and rolling deployments for ML services.

• Design andoptimisedata access patterns in MongoDB (document modelling indexing aggregations) and Redis (caching strategies pub/sub and session management).

• Work with DevOps/Platform teams tomaintainCI/CD pipelinescontainerisationstandards and cloud infrastructure (AWS Azure or GCP).

• Ensure high availability fault tolerance andperformanceSLAs for prediction-serving APIs.

Cross-Functional Collaboration

• Partner with Product Management to define technical roadmap and translate business requirements into engineering plans.

• Collaborate with the QAleadto design comprehensive test strategies unit integration and model validation covering both software and ML components.

• Interface with Frontend Engineers to specify clean versionedpredictionAPIs and ensure seamless UX integration.

• Contribute to and review technical RFCs and architecture decision records (ADRs) across the broader Engineeringorganisation.

Required Qualifications

Machine Learning & Python

• Pythonproficiency:7 years of production Python development; expert-level use of scikit-learn Pandas NumPy and at least one deep learning framework (PyTorchor TensorFlow).

• Classification models:Deep hands-on experience building and deploying classification systems including feature selection imbalanced-class handling calibration and explainability (SHAP LIME).

• ML pipelines:Proven ability to design build andmaintainend-to-end ML pipelines in production including orchestration (Airflow Prefect or similar).

• MLOps:Strong command of model lifecycle management versioning registry A/B testing canary deployments monitoring and alerting.

Infrastructure & Data Technologies

• Kubernetes (k8s):Hands-on experience deploying andoperatingcontainerisedapplications on Kubernetes; familiarwith Helm resource quotas HPA and service mesh fundamentals.

• MongoDB:Solid experience with document-oriented data modelling queryoptimisation aggregation pipelines and schema evolution strategies.

• Redis:Experience with Redis as a caching layer real-time feature store and/or message broker (Streams or pub/sub).

• Cloud platforms:Comfortable with at least one major cloud provider (AWS Azure or GCP) and related managed services (object storage managed databases container registries monitoring).

• CI/CD:Strong grasp of DevOps practices Docker GitHubActionsor similar automated testing andGitOpsworkflows.

Leadership & Communication

• 3 years of experience leading cross-functional engineering teams ideally including Backend Frontend and QA disciplines.

• Track recordof delivering complex multi-team projects on time and with high quality.

• Excellent written and verbal communication skills in English; able torepresenttechnical decisions to non-technical stakeholders.

• Experience working effectively in a globally distributedorganisationacross multiple time zones.

Preferred Qualifications

• Masters or Ph.D. in Computer Science Statistics or a closely related quantitative field.

• Experience with probabilistic classification and uncertainty quantification (calibrated probabilities conformal prediction).

• Familiarity with large-scale data processing frameworks such as Apache Spark orDask.

• Priorexposure to SaaS or enterprise platform environments particularly in finance supply chain or planning domains.

• Experience withadditionaldata stores relevant to the predictive stack: Elasticsearch Cassandra or similar.

• Contributions to open-source ML tooling or published research in applied ML.

Core Technology Stack

What Makes This Role Exciting

You will sit at the intersection of applied machine learning and platform engineering building the predictive intelligence layer that thousands of enterprise planning teams rely on daily. The Predictive Insights teamoperateswith significant technical autonomy and as its Tech Lead you will have the rare opportunity to shape both the engineering culture and the product direction from within India working in tight collaboration with global counterparts across the US and Europe.

You will lead a diverse team where Backend Frontend and QA perspectives are all valued equally and where engineeringrigourand customer impact are the twin north stars. If you are excited by the challenge of making classification models production-ready at enterprise scale and by growing the next generation of ML engineers this is the role for you.

About Anaplan

Anaplan is a cloud-native Connected Planning platform used by more than 2000 of the worlds leadingorganisationsto drive better decisions across finance supply chain sales and HR. Headquartered in San Francisco and with engineering hubs across the US Europe and India Anaplan is on a mission to turn complex business data into actionable insight at scale.

Our Commitment to Diversity Equity Inclusionand 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 arent just words on paper this is what drives our innovation its 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.

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