Fiddler AI
Staff Backend Engineer (Hybrid)
Join Fiddler AI as a Staff Backend Engineer. This role focuses on building reliable, scalable AI observability tools for enterprise customers.
Our Purpose At Fiddler, we build trustworthy AI systems. The rise of Generative AI and agents unlocks immense potential but also introduces significant risk. Our mission is to enable organizations to deploy secure, transparent AI solutions that build user trust.
Why Join Us Our team is dedicated to solving high‑impact challenges in AI safety and reliability. As an early‑stage startup, we offer rapid learning, cross‑disciplinary collaboration, and a chance to shape the future of AI observability.
What You’ll Do
Design and build core services that support enterprises in developing, monitoring, and improving AI applications—including LLMs, GenAI models, and agentic applications.
Lead the design and implementation of distributed systems and microservices that compute, persist, and expose ML + agentic observability metrics (e.g., response relevancy, hallucination scores) from raw trace data.
Build enterprise‑grade, scalable data infrastructure, services, and APIs to support large‑scale workloads while meeting compliance needs and SLAs.
Develop new metrics and evaluation capabilities to satisfy evolving customer requirements; collaborate with customers on discovery and support.
Define and evolve operational maturity (reliability, latency, SLOs, observability) of core services; champion best practices in CI/CD, testing, and reliability.
Take an active role in building a world‑class engineering team, participating in talent acquisition, interviewing, and coaching.
What We’re Looking For
Master’s or Bachelor’s in Computer Science or related field with 7+ years of industry experience.
Deep proficiency in Python and core backend technologies (Postgres, Redis, Kafka, RabbitMQ, Ray) with experience designing large‑scale systems.
Hands‑on experience deploying and working with ML/LLM models in production, familiarity with frameworks such as Langchain, HuggingFace, vLLM, and evaluation tools like Ragas or MLFlow.
Strong system design and optimization skills, with experience in distributed systems and troubleshooting production issues.
Experience with cloud infrastructure (AWS/GCP, Kubernetes) and specialized databases (ClickHouse, Druid) is a plus.
Technical leadership and collaborative mindset; ability to manage and mentor small engineering teams.
Excellent communication and mentorship skills; active participation in code and design reviews.
Ability to work in the Palo Alto office 3 days a week.
Compensation $190,000 – $300,000 + equity + benefits.
Equal Opportunity Fiddler is proud to be an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. If you require special accommodations to complete interviews or perform job duties, please inform the recruiter at the beginning of the process.
Job Scam Notice Beware of job‑scam fraud. Our recruiters use only @fiddler.ai email addresses. In the US, we do not conduct interviews via text or instant message, nor do we request sensitive personal information such as bank account or social security numbers.
#J-18808-Ljbffr
Our Purpose At Fiddler, we build trustworthy AI systems. The rise of Generative AI and agents unlocks immense potential but also introduces significant risk. Our mission is to enable organizations to deploy secure, transparent AI solutions that build user trust.
Why Join Us Our team is dedicated to solving high‑impact challenges in AI safety and reliability. As an early‑stage startup, we offer rapid learning, cross‑disciplinary collaboration, and a chance to shape the future of AI observability.
What You’ll Do
Design and build core services that support enterprises in developing, monitoring, and improving AI applications—including LLMs, GenAI models, and agentic applications.
Lead the design and implementation of distributed systems and microservices that compute, persist, and expose ML + agentic observability metrics (e.g., response relevancy, hallucination scores) from raw trace data.
Build enterprise‑grade, scalable data infrastructure, services, and APIs to support large‑scale workloads while meeting compliance needs and SLAs.
Develop new metrics and evaluation capabilities to satisfy evolving customer requirements; collaborate with customers on discovery and support.
Define and evolve operational maturity (reliability, latency, SLOs, observability) of core services; champion best practices in CI/CD, testing, and reliability.
Take an active role in building a world‑class engineering team, participating in talent acquisition, interviewing, and coaching.
What We’re Looking For
Master’s or Bachelor’s in Computer Science or related field with 7+ years of industry experience.
Deep proficiency in Python and core backend technologies (Postgres, Redis, Kafka, RabbitMQ, Ray) with experience designing large‑scale systems.
Hands‑on experience deploying and working with ML/LLM models in production, familiarity with frameworks such as Langchain, HuggingFace, vLLM, and evaluation tools like Ragas or MLFlow.
Strong system design and optimization skills, with experience in distributed systems and troubleshooting production issues.
Experience with cloud infrastructure (AWS/GCP, Kubernetes) and specialized databases (ClickHouse, Druid) is a plus.
Technical leadership and collaborative mindset; ability to manage and mentor small engineering teams.
Excellent communication and mentorship skills; active participation in code and design reviews.
Ability to work in the Palo Alto office 3 days a week.
Compensation $190,000 – $300,000 + equity + benefits.
Equal Opportunity Fiddler is proud to be an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. If you require special accommodations to complete interviews or perform job duties, please inform the recruiter at the beginning of the process.
Job Scam Notice Beware of job‑scam fraud. Our recruiters use only @fiddler.ai email addresses. In the US, we do not conduct interviews via text or instant message, nor do we request sensitive personal information such as bank account or social security numbers.
#J-18808-Ljbffr