Core Technical Skills
- Programming: Proficiency in Python is essential. Experience with asynchronous programming and API development (FastAPI/Flask).
- Generative AI & LLMs: Deep understanding of Large Language Models (LLMs), their capabilities, limitations, and tuning techniques (RAG, fine-tuning).
- Agent Frameworks: Hands-on experience with modern agent frameworks such as:
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- Google GenAI SDK / Vertex AI Agent Builder
- Anthropic Claude SDK / Tools / Skills
- Microsoft Agent Framework
- LangChain / LangGraph
- Agent Design: Solid grasp of agent design patterns (ReAct, Chain-of-Thought, planning, reflection) and tool-use definitions.
Cloud & DevOps
- Cloud Platforms: Strong experience with Azure / AWS / GCP ecosystems.
- Deployment: Expertise in deploying AI applications using containerization (Docker, Kubernetes) and serverless technologies (Azure Functions, AWS Lambda, GCP Cloud Run).
- MLOps/LLMOps: Familiarity with pipelines for evaluating, monitoring, and managing the lifecycle of LLM-based applications.
Experience Levels
Mid-Level Engineer
- Experience: 3-5 years in software/AI engineering with proven experience building LLM applications.
- Focus: Designing agent workflows, optimizing prompt performance, managing cloud infrastructure for AI apps, and mentoring junior members.
Senior Engineer
- Experience: 5+ years in AI/Software Engineering with significant expertise in Generative AI and system architecture.
- Focus: Leading the architecture of complex multi-agent systems, defining best practices for agent design, driving strategic technical decisions, and overseeing large-scale deployments.
Soft Skills
- Excellent problem-solving and analytical skills.
- Strong communication skills to articulate complex technical concepts to stakeholders.
- Ability to work effectively in a fast-paced, collaborative global environment.
- Good command of English (verbal and written).
