Senior Agentic AI Engineer

Role summary / purpose

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). You will combine deep technical architecture responsibility with daily hands-on coding centered on building robust, scalable multi-agent AI systems and serve as the team's go-to technical expert.

Key responsibilities

• Architecture: Design multi-agent AI systems, evaluate trade-offs between single vs. multi-agent, RAG vs. fine-tuning, and contribute to Architecture Decision Records.
• Hands-on coding: Develop 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.

Requirements – education & experience

• 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.

Required skills

• Proficiency with agentic coding tools such as OpenCode, Claude Code, or similar.
• Backend development with Python and FastAPI.
• Frontend development with Angular or React.
• Experience with multi-agent system design and orchestration.

Nice-to-have / preferred skills

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