AI Engineer — Agentic Systems, RAG (LangGraph / Vertex AI)

As an AI Engineer, you will be at the forefront of our innovation engine, architecting the next generation of intelligent agentic systems. This isn't just about prompt engineering; it's about building scalable, production-ready Generative AI ecosystems that solve high-stakes business challenges.

Key Responsibilities

• Architect & Deploy: Design end-to-end GenAI solutions, specialized AI agents, and high-performance RAG pipelines.

• Lead Innovation: Rapidly build and validate Proof of Concepts (PoCs) to showcase the "art of the possible" to stakeholders.

• Consult & Collaborate: Partner with cross-functional teams and interface directly with clients to translate complex needs into tailored AI strategies.

• Research & Evaluate: Stay ahead of the curve by benchmarking emerging models, agentic frameworks, and dev kits.

The Profile

• The Experience: 3+ years of industry-hardened experience in Applied AI or Machine Learning.

• The Tech Stack: Expert-level command of agentic frameworks (LangGraph, Agno, Google ADK) and Vector Databases.

• Cloud Fluency: Deep familiarity with at least one major Hyperscaler (GCP, AWS, or Azure).

• Bonus Points: Proficiency with the Google Cloud AI stack (Vertex AI, Gemini), MLOps (Docker/K8s), and rigorous evaluation frameworks like RAGAs or LangSmith.

• AI agent building: know-how.

Compensation: USD 2,000–3,500/mo depending on seniority and specific stack match. Remote, full-time. English B2 or higher is required for client-facing work.