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AI Engineer

Thunderhawk Technology Partners LLC

  • Phoenix, AZ
  • 1 day ago

    Highlights

    Orchestration Frameworks: LangGraph| LangChain| Airflow| etc Integration of commercial and open-source LLMs into agentic workflows Agent and orchestration frameworks such as LangChain| Llama Index| Semantic Kernel| or CrewAI| with strong judgment about when to use frameworks versus building lighter-weight primitives Model-level work using PyTorch and the Hugging Face ecosystem (embeddings| fine-tuning| inference tooling)| with some exposure to TensorFlow Strong schema| validation| and state management practices using tools such as Pydantic Python and Zod TypeScript. Role Descriptions: Technical and Functional Skills 10 years of experience building large-scale distributed systems and strong experience with LLM systems| agentic workflows or advanced ML infrastructure AI engineers with recent NodeJS JavaScript Typescript experience.

    Numbers & Facts

    LocationPhoenix, AZ

    Description

    Job Title: AI Engineer
    Location: - Phoenix, AZ ( Need only local Candidate who is willing to come to in-person interview)
    Duration: 6 months

    AI Engineer – Agentic AI, Node JS

    Technical Skills:
    • 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, TensorFlow, Hugging Face.
    • Practical knowledge of model orchestration frameworks (e.g., LangChain, 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
    Key Responsibilities:
    • 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 trade-offs 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.
    Role Descriptions:
    • Technical and Functional Skills 10 years of experience building large-scale distributed systems and strong experience with LLM systems| agentic workflows or advanced ML infrastructure AI engineers with recent NodeJS JavaScript Typescript experience.
    • 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.
    • Comfort operating in ambiguous problem spaces and translating them into shipped| reliable autonomous systems.
    • Ability to influence technical direction and align teams without formal authority.
    • Experience in workflow engines| async processing| queues| and streaming systems.
    • Languages: NodeJS JavaScript Typescript Python| Go
    • APIs and services: REST| gRPC
    • Cloud and infrastructure: AWS and or GCP| Kubernetes
    • Distributed systems: event-driven architectures| including Kafka
    • Orchestration Frameworks: LangGraph| LangChain| Airflow| etc Integration of commercial and open-source LLMs into agentic workflows Agent and orchestration frameworks such as LangChain| Llama Index| Semantic Kernel| or CrewAI| with strong judgment about when to use frameworks versus building lighter-weight primitives Model-level work using PyTorch and the Hugging Face ecosystem (embeddings| fine-tuning| inference tooling)| with some exposure to TensorFlow Strong schema| validation| and state management practices using tools such as Pydantic Python and Zod TypeScript.
    • Experience building agentic systems in fintech or other regulated industries.
    • Experience as a founding engineer or early technical leader in AI-driven products.
    • Demonstrated success delivering technically complex autonomous systems that customers actively rely on. Meaningful contributions to open-source AI or agentic frameworks.
    • Familiarity with fine-tuning| model optimization and inference pipelines is a plus.

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