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.

The Mission:

Forward Deployed Engineers bring trustworthy AI to life for our customers. Deploying, customizing, and optimizing complex, high-impact AI observability and agentic solutions in the field. A hands-on builder and strategic partner, translating customer goals into tangible, production-ready systems that deliver measurable business outcomes.

Configuring software, and engineering bespoke solutions, architect advanced integrations, and seen as the technical heartbeat of every engagement. FDE's combine deep technical mastery, problem-solving prowess, and customer empathy to help organizations operationalize responsible AI at scale.

About the Team:

You'll join a tight-knit team of engineers who thrive at the intersection of AI innovation and customer impact. We collaborate closely with data science and ML engineering teams across leading enterprises to design, deploy, and optimize AI systems in production.

We work remotely, move fast, and operate like a startup within a startup, curious, pragmatic, and deeply customer-obsessed. Every engagement is hands-on, every problem is unique, and every solution you build will push the boundaries of what's possible with AI Observability and Agentic AI.

What You'll Do:

Drive Technical Impact from Concept to Production

Lead the end-to-end delivery of advanced AI solutions; writing critical code, building integrations, and debugging complex data pipelines and model workflows. You'll own deployments that move the needle for our customers.

Engineer Bespoke AI & Agentic Solutions

Design, develop, and deploy custom intelligent agents and AI observability architectures tailored to each customer's data ecosystem and business objectives, leveraging frameworks like LangChain, LlamaIndex, and modern orchestration tools.

Architect Data & Integration Pipelines

Own the data lifecycle; from modeling and transformation to secure, high-throughput pipelines using technologies such as Snowflake, Databricks, Airflow, Kafka, and S3. You'll ensure AI systems are production-grade, performant, and explainable.

Lead Rapid Prototyping & Iteration

Work side-by-side with customer teams to build proofs-of-concept and minimum viable products that showcase Fiddler's capabilities and demonstrate measurable value quickly.

Be the Technical Voice of the Customer

Embed with client engineering and data science teams to deeply understand their goals, constraints, and architecture. Translate these needs into actionable technical designs while championing their feedback across Product and Engineering.

Evangelize Best Practices in AI Observability

Guide customers toward responsible AI deployment through robust monitoring, drift detection, explainability, and compliance workflows powered by Fiddler's platform.

Mentor & Elevate Technical Teams

Provide hands-on guidance to both internal peers and customer engineers. Set standards for excellence in engineering, scalability, and trustworthy AI deployment.

What We're Looking For:

5+ years of experience designing, building, and deploying production-grade ML or AI systems
Strong foundation in Computer Science, AI/ML, or a related engineering discipline
Expert-level coding skills in Python, JavaScript, or Java, with a focus on building scalable systems
Proven experience integrating or orchestrating LLM/Generative AI frameworks (LangChain, LlamaIndex, RAG, etc.)
Deep understanding of data modeling, pipelines, and enterprise integration patterns
Exceptional communication and collaboration skills—able to translate deep technical concepts into business impact
Demonstrated leadership in customer-facing engagements, balancing technical rigor with empathy and pragmatism
Entrepreneurial mindset with a bias for action, creativity, and ownership
Hybrid position for Bengaluru, with 2 days working in-office
Willingness to travel up to 25% for on-site customer collaboration

Even Better If You Have:

Experience with AI Observability tools or model monitoring platforms
Familiarity with Kubernetes, cloud platforms (AWS, GCP, Azure), and MLOps frameworks (MLflow, Kubeflow, Argo)
Prior experience building or deploying agentic or conversational AI in enterprise settings
Contributions to open-source AI frameworks or community-driven projects
Understanding of model explainability, bias detection, and responsible AI practices

Customer Success Forward Deployed Engineer