What are the responsibilities and job description for the Applied AI Developer (W2 Only) position at Ryzlink Corporation?
**Job Title: Senior Applied AI Engineer (Agentic Systems & LLMs)**
**Location: Palo Alto, CA (Hybrid – 3–4 days onsite)**
**Experience: Min 8 Years Required**
**Job Type: Contract - W2 only**
**About the Role**
As part of our Enterprise AI team, you’ll go beyond experimentation and bring AI into real-world impact. You’ll evaluate where AI truly adds value, build scalable platforms, and enable teams to adopt modern AI patterns — from LLM orchestration to agentic workflows and governance.
This role is highly hands-on and outcome-driven — ideal for someone who loves prototyping, experimenting with cutting-edge AI, and shipping production-grade solutions that drive measurable efficiency.
**What You’ll Do**
* Think **AI-first**: Identify where agentic AI outperforms traditional approaches and build robust evaluation frameworks (evals, simulations, regression testing).
* Design and build **agentic systems**: orchestration, reasoning, memory, MCP integrations, and human-in-the-loop workflows.
* Implement **AI governance**: guardrails, data lineage, auditability, and responsible AI practices.
* Drive adoption through **POCs, pilots, and scalable implementations**.
* Collaborate cross-functionally with Product, Security, and Engineering teams to deliver **end-to-end AI solutions**.
**What We’re Looking For**
* 5 years of software engineering experience, with 2 years in applied AI (production systems).
* Strong proficiency in **Python and/or Go**.
* Proven experience building and scaling **multi-agent / agent-driven systems** in real-world environments.
* Hands-on with modern AI ecosystems:
* Frameworks: LangGraph, Google ADK, Mastra, Claude Agent SDK
* Observability & evals: Langfuse, LangSmith, Braintrust
* AI SDKs: OpenAI, Anthropic
* Strong backend/system design fundamentals (scalability, reliability, performance).
* Experience with **cloud platforms** (AWS and/or GCP).
* Excellent collaboration and communication skills.
**Nice to Have**
* Experience with AI evaluation frameworks or custom eval pipelines.
* Built custom MCP servers (not just integrations).
* Familiarity with **Docker, Kubernetes**.
* Experience optimizing **LLM inference costs at scale**.
* Strong ownership mindset with a bias for action.