Member of Technical Staff (AI Supportability)

• Start with focused validation

  : Design experiments to test whether LLMs can assist with root cause analysis on real Zendesk escalations, determining if AI can accelerate diagnostic workflows and reduce time-to-resolution.

• Work embedded with our Bangalore technical support team:

  Partner with support engineers through regular collaboration sessions to understand diagnostic workflows, review experimental results, and gather insights.

• Work with real CockroachDB data

  : Process diagnostic telemetry including cluster metrics, SQL traces, system logs, plus observability data.

• Iterate on AI approaches

  : Experiment with OpenAI/Anthropic APIs, prompt engineering techniques, and different data contexts to optimize LLM diagnostic performance.

• Build rapid prototypes

  : Transform promising validation results into proof-of-concept tools and agents, defining next steps based on what the data tells us.

• Measure and document progress

  : Establish clear success metrics for LLM accuracy and track experimental results throughout the validation process.

• Scale successful experiments

  : Use Go, Python, and cloud infrastructure to build scalable applications from vali prototype.

• Explore advanced AI patterns

  : As validation results warrant, investigate sophisticated approaches like agentic workflows, MCP integrations, and multi-step reasoning chains for complex diagnostic scenarios

The Expectations

You Have

• Experimental mindset

  : Youre energized by ambiguous problems, rapid prototyping, and discovering solutions through data-driven experimentation

• Applied AI/ML work

  : Experience with LLMs, prompt engineering, and model evaluation through professional work, significant side projects, or deep technical exploration

• Strong programming skills

  : Proficiency in Go, Python or similar languages, with ability to quickly learn new technologies and APIs

• Data and systems experience

  : Comfort working with large-scale structured data, APIs, observability tools, logs, metrics, and distributed systems concepts

• Greenfield experience

  : Background building new products, prototypes, or research projects where the solution path wasnt predefined

• Embedded collaboration experience

  : Experience working directly with internal stakeholders, gathering requirements, and iterating based on user feedback

• Technical communication

  : Ability to explain complex experimental results and technical concepts to diverse audiences

• Ideally 5+ years

  of software engineering experience with hands-on AI/ML work, but we prioritize your ability to learn, experiment, and deliver measurable results
• BE/B-Tech/M-Tech in Computer Science or equivalent experience