Solutions Architect, Customer Success
Fiddler AI
full-time
Posted on:
Location Type: Remote
Location: Remote • California • 🇺🇸 United States
Visit company websiteSalary
💰 $160,000 - $200,000 per year
Job Level
Mid-LevelSenior
Tech Stack
AirflowAWSAzureBigQueryCloudGoogle Cloud PlatformHadoopKafkaKubernetesMongoDBPyTorchRabbitMQScikit-LearnSparkTensorflow
About the role
- Drive successful onboarding experiences. Partner closely with a Fiddler Delivery Manager to architect and implement onboarding solutions, aligning customer goals with Fiddler’s capabilities, and ensuring deployments are delivered on time, with precision, and with clear success criteria met.
- Be the trusted technical partner our customers rely on. You’ll build strong relationships with data science and ML engineering teams, guiding them through every stage of their AI observability journey and ensuring they realize measurable value from Fiddler.
- Champion the customer voice across Fiddler. Lead ongoing technical engagements, status syncs, roadmap discussions, QBRs, and escalation management; to ensure customer feedback influences our product roadmap and long-term strategy.
- Become a domain expert in AI Observability. Master Fiddler’s platform and help customers operationalize observability best practices improving model transparency, performance monitoring, and compliance across their ML lifecycle.
- Deliver seamless integrations and technical success. Write custom integration code that connects Fiddler to customer data ecosystems using tools like Snowflake, Airflow, MLflow, S3, Kafka, and more; ensuring robust, scalable, and secure pipelines.
- Accelerate platform adoption. Build and refine integration patterns between Fiddler and common data platforms, workflow tools, and ML infrastructures to reduce time-to-value for new customers.
- Uncover and drive expansion opportunities. Identify new ways Fiddler can provide impact; whether through advanced observability use cases, expanded integrations, or deeper model governance, helping drive renewals and growth.
Requirements
- Bachelor’s degree in Computer Science (AI/ML focus), Statistics, Mathematics, or related field with 5-7+ years of professional experience.
- 2+ years of hands-on experience deploying, monitoring, or maintaining ML models in production environments.
- Excellent communication, presentation, and storytelling abilities; able to distill complex technical concepts into clear, actionable insights for both technical and executive audiences.
- Strong organizational and project management skills, with the ability to balance multiple customer engagements and priorities.
- Demonstrated collaboration across cross-functional teams—Product, Engineering, and Delivery—to drive customer outcomes.
- A customer-first mindset with empathy, curiosity, and a deep sense of ownership for delivering value.
- Passion for continuous learning and a desire to inspire customers and peers through thought leadership and technical credibility.
- Understanding of data science concepts, model interpretability, and explainability techniques used in modern ML systems.
- Working knowledge of data and workflow tools such as Hadoop, MongoDB, Snowflake, BigQuery, Spark, Kafka, Kinesis, RabbitMQ, Airflow, MLflow, Luigi, Kubeflow, or Argo.
- Experience with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.
- Proficiency with Kubernetes and cloud platforms (AWS, Azure, GCP).
Benefits
- Competitive pay + equity
- Unlimited PTO
- Premium health, dental & vision (*100% premium coverage for employees)*
- 401(k) plan
- Monthly fitness reimbursement
- Paid parental leave
- Annual Caltrain pass
- Monthly in-office massages
- Fastrak reimbursement
- Lunch provided Mon–Thurs
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learningmodel deploymentmodel monitoringmodel maintenancedata sciencemodel interpretabilityexplainability techniquesintegration codingproject managementdata analysis
Soft skills
communicationpresentationstorytellingorganizational skillscollaborationcustomer-first mindsetempathycuriosityownershipthought leadership