Artificial Intelligence & Expert Systems

Artificial Intelligence & Expert Systems

This is a hands-on individual contributor role focused on building AI/agentic systems for an Enterprise Data Platform, with emphasis on multi-agent orchestration on Google Cloud Platform (GCP). Key expectations include:

• Architecture:
  Design multi-agent AI systems, evaluate trade-offs (single vs. multi-agent, RAG vs. fine-tuning), and contribute to Architecture Decision Records.
• Hands-on coding:
  Daily production-grade code across agent frameworks, backend/frontend, LLM-powered workflows (NL-to-SQL, semantic search, metadata enrichment), plus guardrails and observability for AI outputs.
• Full-stack work:
  Backend (Python/FastAPI) and frontend (Angular/React) development, chat and API interfaces, and evaluation/benchmarking tools, with end-to-end feature ownership.
• Engineering excellence:
  Maintain high code quality, lead by example in reviews, conduct root-cause analysis on agent failures, and act as the team's technical anchor for tough problems.
• Collaboration:
  
  Work with Product, Data Engineering, and Platform teams; mentor others, support sprint planning, and help onboard new hires.

In short, the role combines deep technical architecture responsibility with daily hands-on coding, centered on building robust, scalable multi-agent AI systems and serving as the team's go-to technical expert.

Skills Required:

• Artificial Intelligence & Expert Systems

Skills Preferred:

• GCP Experience

Required:

Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field. 5+ years of professional software engineering experience with demonstrated hands-on coding proficiency. Demonstrable experience building AI-powered applications or operating LLM-based systems in production environments. Proven ability to interpret ambiguous requirements and independently deliver functional, well-tested software.

Experience Preferred:
Experience with the Google Agent Development Kit (ADK) or comparable agent frameworks, such as CrewAI, or Lang Graph. Familiarity with data engineering practices and data governance processes. Applied machine learning experience encompassing embeddings, classification, clustering, natural language processing, and evaluation metrics.

Education Required:

Bachelor's Degree

Education Preferred:
Master's Degree