AI Engineer – Agentic AI, Node Js
Job in
Phoenix, Maricopa County, Arizona, 85001, USA
Listed on 2026-09-02
Listing for:
Artech
Full Time
position Listed on 2026-09-02
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Backend Developer
Job Description & How to Apply Below
AI Engineer – Agentic AI, Node Js
We are seeking a Senior AI Engineer with strong experience in Agentic AI, Generative AI, LLM systems, Type Script/Node.js, and Python to design, build, and operate production-grade autonomous AI systems. The ideal candidate will have a strong distributed-systems background combined with hands-on experience developing agentic workflows, LLM orchestration, RAG pipelines, tool use, memory, evaluation, and AI infrastructure.
Candidates without recent hands-on experience in Agentic AI, Generative AI, and Node.js/Type Script will not be considered.
Key Responsibilities- Drive technical direction for Agentic AI initiatives, including architecture, autonomy boundaries, orchestration, reliability, and scalability.
- Design, develop, deploy, and operate production-grade agentic AI systems across multiple products and teams.
- Build agent frameworks and orchestration layers supporting planning, tool use, memory, and multi-agent workflows.
- Design and implement RAG, retrieval, grounding, and vector search pipelines.
- Develop LLM infrastructure, inference services, model gateways, and integrations with commercial and open-source LLMs.
- Implement evaluation, observability, safety, and monitoring capabilities for autonomous AI systems.
- Build scalable backend services, APIs, data pipelines, workflow engines, and event-driven architectures.
- Work with asynchronous processing, queues, streaming systems, and distributed architectures.
- Lead technical design reviews and make architecture decisions balancing autonomy, safety, reliability, scalability, performance, and cost.
- Evaluate emerging LLM models, agentic patterns, frameworks, and techniques and translate them into enterprise-ready solutions.
- Collaborate with engineering, product, data, and business teams to deliver complex AI initiatives from concept through production.
- Influence technical direction and align cross-functional teams without requiring formal authority.
- 10+ years of experience building large-scale distributed systems and backend applications.
- Strong recent hands-on experience with Agentic AI, Generative AI, and LLM-based systems.
- Strong recent experience with Node.js, JavaScript, and Type Script.
- Advanced proficiency in Python.
- Experience with PyTorch, Hugging Face, and exposure to Tensor Flow.
- Hands-on experience with agent/orchestration frameworks such as Lang Graph, Lang Chain, Llama Index, Semantic Kernel, CrewAI.
- Strong understanding of agentic AI concepts, including planning, tool calling, memory, reasoning workflows, orchestration, and evaluation.
- Experience designing and implementing RAG and retrieval/grounding solutions.
- Experience with vector databases and embedding-based search.
- Strong experience with REST APIs and gRPC.
- Experience with AWS and/or GCP, preferably including Kubernetes.
- Experience with Kafka, event-driven architectures, workflow engines, queues, and streaming systems.
- Experience with Pydantic and/or Zod for schema validation and state management.
- Strong understanding of backend systems, data pipelines, cloud infrastructure, and distributed systems.
- Experience building agentic AI systems in fintech or other regulated industries.
- Experience with fine-tuning, model optimization, embeddings, and inference pipelines.
- Experience integrating both commercial and open-source LLMs into production agentic workflows.
- Experience as a founding engineer, early technical leader, or technical owner of AI-driven products.
- Demonstrated success delivering autonomous AI systems used by customers in production.
- Meaningful contributions to open-source AI or agentic AI frameworks.
- Strong understanding of AI-assisted and agentic software development workflows.
- Excellent problem-solving, communication, and cross-functional collaboration skills.
- Ability to explain complex AI concepts to non-technical stakeholders.
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