AI Engineer

AI-Native Software Developer Profile (GenAI & Agentic AI, Full-Stack) We seek developers with an AI-first engineering mindset, able to choose between deterministic code, LLMs, and agents, and to design for probabilistic outputs with robust fallback strategies while balancing cost, latency, and reliability. Core GenAI & LLM expertise includes integrating LLMs into production, prompt engineering, structured outputs, RAG pipelines, effective context management, and quality/hallucination evaluation. Rapid solution development skills: proficiency with modern AI development platforms, APIs, and tooling to quickly prototype, iterate, and deploy functional AI capabilities into real-world systems. Agentic AI experience: building autonomous/semi-autonomous agents with clear goals, constraints, orchestration patterns, tool-calling, state/memory handling, guardrails, and behavioral observability. Full-stack capabilities: Backend API design (REST/GraphQL), secure services, data modeling, async workflows, external integrations. Frontend — modern frameworks (e.g., React), AI-native UX (streaming responses, explainability), state management, human-AI interaction patterns. Cloud-native experience in containerized/microservice environments, CI/CD for AI components, secure secrets handling, cost-aware designs, and performance optimization. Data & knowledge engineering: handling structured/unstructured data, building pipelines, preprocessing, embeddings, ranking, and versioning AI artifacts. Focus on reliability, security, and responsible AI: safeguard sensitive data, mitigate leakage/bias/safety risks, ensure auditability, and support graceful degradation. Excellent collaboration and communication: clear explanation of AI behavior, cross-functional teamwork, documentation, and critical output review. High learning agility and craftsmanship: staying current with evolving AI tools, delivering production-quality systems.