AI Engineer – Agentic AI, Node Js
Job in
Phoenix, Maricopa County, Arizona, 85001, USA
Listed on 2026-07-01
Listing for:
Artech
Full Time
position Listed on 2026-07-01
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Job Description & How to Apply Below
AI Engineer – Agentic AI, Node Js
Location:
New York, NY / Phoenix, AZ / Sunrise, FL (Onsite) Duration: 6 Months Pay Range: $47 - $51/hr
- 6+ years of experience building large-scale distributed systems.
- Strong experience with LLM systems, agentic workflows or advanced ML infrastructure, async processing, queues, and streaming systems.
- Experience working on Typescript and Python, Gen AI, Agentic AI.
- Advanced proficiency in Python.
- Hands-on experience with PyTorch, Tensor Flow, Hugging Face.
- Practical knowledge of model orchestration frameworks (e.g., Lang Chain, Llama Index, CrewAI).
- Familiarity with vector databases.
- Experience with cloud platforms (AWS, Azure AI, Google Cloud Vertex AI) and containerization technologies.
- Proven ownership of complex, cross-cutting agentic systems spanning multiple teams or products.
- Strong engineering fundamentals across backend systems, APIs, data pipelines, and cloud infrastructure.
- Deep experience across the agentic AI stack, including planning, tool use, memory, and evaluation.
- Fluency with AI-assisted and agentic development workflows.
- Ability to influence technical direction and align teams without formal authority.
- Problem-solving, cross-functional collaboration, and the ability to articulate complex AI concepts to non-technical business stakeholders.
- Drive technical direction for agentic AI initiatives, influencing architecture patterns, autonomy boundaries, and system design.
- Design, build, and operate production-grade agentic AI systems used across multiple products.
- Own and evolve shared agentic AI capabilities, including:
- Design and develop agent frameworks and orchestration layers.
- Planning, tool use, and memory strategies.
- Design retrieval and grounding (RAG) pipelines.
- LLM infrastructure, inference, and model gateways.
- Evaluation, observability, and safety tooling for autonomous systems.
- Lead technical design reviews and help teams navigate tradeoffs involving autonomy, safety, reliability, scalability, and cost.
- Partner across teams to deliver complex, cross-cutting agentic AI initiatives from concept to production.
- Evaluate emerging models, techniques, and agentic patterns and translate them into practical, enterprise-ready improvements.
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