Job Description
Engineer - Agentic AI
WHAT WE DO
We are transforming how businesses optimize their data operations with an industry-leading data observability platform. The platform helps organizations maximize performance, reduce costs, and ensure reliability across complex data ecosystems including Databricks, Snowflake, BigQuery, Amazon EMR, Spark, and Kafka. Intelligent automation enables data teams to troubleshoot faster, optimize workloads, and gain more value from their data infrastructure investments.
ROLE DESCRIPTION
We are looking for a highly skilled Python Engineer with experience in building AI Agents.
Responsibilities :
-
Design, build, and deploy autonomous AI agents that analyze and reduce cloud data platform costs across Snowflake, BigQuery, and Databricks.
- Own the full AI agent lifecycle including observability instrumentation, cost signal ingestion, automated remediation, and human-in-the-loop workflows.
- Collaborate with Data Engineering, FinOps, and Platform teams to convert cost policies into scalable agent-driven governance rules.
- Work at the intersection of data engineering, applied AI, and product innovation to rapidly deliver AI Agent capabilities.
SKILLS REQUIRED
- 4–6 years of experience in Data Engineering, ML Engineering, or Backend Engineering.
- Minimum 2 years of hands-on experience building or productionizing LLM-powered applications, AI agents, or tool-use pipelines.
- Experience with agent frameworks such as LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex, OpenAI APIs, Anthropic APIs, or Gemini Enterprise Agent Platform.
- Strong programming skills in Python, SQL, TypeScript, Bash/Shell.
- Experience with tools and infrastructure including dbt, Airflow/Prefect, Docker, Kubernetes, Terraform, Prometheus, Grafana.
- Familiarity with vector databases like Pinecone, Weaviate, pgvector, and RAG architectures.
- Knowledge of cloud platforms (AWS/GCP/Azure) and serverless computing.
- Strong analytical and problem-solving mindset.
Good to Have:
- Experience with FinOps practices such as cost allocation, budget alerting, or cloud query optimization.
- Exposure to Snowflake query profiling, BigQuery slot reservations, or Databricks compute management.
- Contributions to open-source AI/ML or agent frameworks.
- FinOps certifications or cloud cost management tooling experience.
ROLES & RESPONSIBILITIES
- Design and maintain Python-based AI/Agentic solutions.
- Build multi-agent systems using LLM planners and tool-use frameworks for anomaly detection, root-cause analysis, and automated corrective actions.
- Apply GenAI and LLM techniques to generate insights and recommendations.
- Integrate with Snowflake, BigQuery, and Databricks APIs for real-time spend analysis.
- Develop evaluation frameworks to measure agent accuracy, savings, and false positives.
- Work with product managers and domain experts to create innovative AI capabilities.
- Implement safe and auditable agent workflows with approval systems and rollback mechanisms.
- Collaborate on prompt engineering, RAG pipelines, and fine-tuning strategies.
WHY JOIN US
- Innovation-driven engineering culture.
- Strong focus on ownership and fast execution.
- Collaborative and learning-oriented environment.
- Encouragement for new ideas, experimentation, and product innovation.
- Opportunity to work on cutting-edge AI Agent systems and cloud optimization platforms.
