Staff Backend Engineer
Our Purpose
At Fiddler, we understand the implications of AI and the impact that it has on human lives. Our company was born with the mission of building trust into AI. The rise of Generative AI and Agents has unlocked generalized intelligence but also widened the risk aperture and made it harder to ensure that AI applications are working well. Fiddler enables organizations to get ahead of these issues by helping deploy trustworthy, and transparent AI solutions.
Fiddler partners with AI-first organizations to help build a long-term framework for responsible AI practices, which, in turn, builds trust with their user base. AI Engineers, Data Science, and business teams use Fiddler AI to monitor, evaluate, secure, analyze, and improve their AI solutions to drive better outcomes. Our platform enables engineering teams and business stakeholders alike to understand the "what", “why”, and "how" behind AI outcomes.
Our Founders
Fiddler AI is founded by Krishna Gade (engineering leader at Facebook, Pinterest, Twitter, and Microsoft) and Amit Paka (product leader at Microsoft, Samsung, Paypal and two-time founder). We are backed by Insight Partners, Lightspeed Venture Partners, and Lux Capital.
Why Join Us
Our team is motivated to help build trust into AI to enable society harness the power of AI. Joining us means you get to make an impact by ensuring that AI applications at production scale across industries have operational transparency and security. We are an early-stage startup and have a rapidly growing team of intelligent and empathetic doers, thinkers, creators, builders, and everyone in between. The AI and ML industry has a rapid pace of innovation and the learning opportunities here are monumental. This is your chance to be a trailblazer.
Fiddler is recognized as a pioneer in the field of AI Observability and has received numerous accolades, including: 2022 a16z Data50 list, 2021 CB Insights AI 100 most promising startups, 2020 WEF Technology Pioneer, 2020 Forbes AI 50 most promising startups of 2020, and a 2019 Gartner Cool Vendor in Enterprise AI Governance and Ethical Response. By joining our brilliant (at least we think so) team, you will help pave the way in the AI Observability space.
🚀 What You’ll Do:
Design and build core services and components of a world-class cloud platform to help enterprises develop, monitor and improve their full suite of AI based applications (covering predictive models, LLMs, GenAI models and agentic applications)
Lead the design and implementation of distributed systems and microservices that compute, persist, and expose new ML + agentic observability metrics (e.g., response relevancy, hallucination scores) from raw trace data
Design enterprise-grade, scalable data infrastructure, services and APIs to support enterprise scale workloads and meet compliance needs and SLAs
Spearhead the development of new types of metrics and evaluation capabilities to satisfy evolving customer needs. Take part in conversations with customers around discovery and support
Define and evolve the operational maturity (reliability, latency, SLOs, observability) of core services, establish best practices and champion improvements to internal CI/CD processes, testing frameworks, error handling, efficiency and resiliency
Team & Culture Building: you will take an active role in building a world-class engineering team and actively participate in the talent acquisition process through interviewing, candidate evaluation and coaching
🎯 What We’re Looking For:
Masters or Bachelors degree in Computer Science or related field, combined with 7+ years of industry experience, with demonstrated solid foundation in software development.
Deep proficiency with Python and a strong command of essential backend technologies like Postgres, Redis, Kafka, RabbitMQ, Ray. This includes the ability to design, build, and debug complex, large-scale systems.
Adaptability & Ownership: proven ability to thrive in ambiguity and a fast-paced environment. We need a self-motivated initiator who can take ownership of projects with a high degree of autonomy, confidently filling in the gaps when the full picture isn't available.
System Design & Optimization: A strong grasp of distributed systems and the capacity to troubleshoot production issues. A nice to have would be experience with cloud infrastructure (AWS/GCP, Kubernetes) and specialized databases (Clickhouse/Druid), indicating a deeper understanding of system architecture and performance optimization.
Technical Leadership & Collaboration: Demonstrated ability to plan, execute, and deliver projects by effectively breaking down complex problems into manageable tasks, and guiding a small team of engineers. Must be adept at cross-functional collaboration across a geographically distributed team, working closely with product managers, designers, frontend developers, and data scientists to ensure alignment and successful project outcomes
Coaching & Mentorship: you should be an excellent collaborator and a mentor to other team members, raising the technical bar for the entire team and regularly engage in code and design reviews.
Nice to Have:
Experience with deploying and working with ML/LLM models in production. The candidate should be comfortable with modern LLM frameworks (e.g., Langchain, HuggingFace, vLLM) and evaluation frameworks (e.g., Ragas, MLFlow) to ensure model performance and reliability.
The posted range represents the expected salary range for this job requisition and does not include any other potential components of the compensation package and perks previously outlined. Ultimately, in determining pay, we'll consider your experience, leveling, location, and other job-related factors.
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 in order to complete the interviews or perform job duties, please inform the recruiter at the beginning of the process.
Beware of job scam fraud. Our recruiters use @fiddler.ai email addresses exclusively. In the US, we do not conduct interviews via text or instant message, or ask for sensitive personal information such as bank account or social security numbers.