Lead - AI/ML Engineer (Generative AI Agent Systems)
Tasks
- Advise enterprise clients on AI architecture
- Build resilient distributed systems
- Define human-in-the-loop controls
- Define production readiness quality gates
- Define reusable agent delivery practices
- Design agent specifications for function calling
- Develop continuous shadow mode evaluation systems
- Drive technical discovery sessions
- Implement event-driven communication patterns
- Lead Generative AI strategy
- Lead technical delivery teams and mentorship
- Oversee proof of concept delivery
- Own production agent reference architecture
- Support AI governance and monitoring
Perks/Benefits
- Global collaboration
- High-impact projects
- Inclusive workplace
- Innovation-focused culture
- Professional growth
- Remote work
- Technical leadership
Skills/Tech-stack
AI Agent Development Kit | AI Governance | Access Management | Agent Development Kit | Agent Frameworks | Agent systems | Autonomous Agents | Cloud platform | Context Management | Data Drift | Data drift monitoring | Distributed Systems | Drift monitoring | Evaluation Frameworks | Event Driven | Event-driven architecture | Function Calling | Generative AI | Go | Golang | Google Cloud | Google Cloud Platform | Human-in-the-loop | IAM | Idempotency | Identity and Access Management | Identity and access | LLM Reasoning | Language Models | Large Language Models | Model Drift | Model drift monitoring | Model versioning | Multi-Agent | Multi-Agent Systems | Observability | Prompt engineering | Pub/Sub | Responsible AI | Service Controls | The Loop | VPC Service Controls | Vector Search | Vertex AI | Vertex AI Agent Development Kit
Education
N/A
Roles
AI | AI/ML Engineer | Engineer | Lead | Lead AI | Lead AI/ML Engineer | ML Engineer
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