Unknown Company

Product Solutions Engineer

austin, tx • Posted 4 days ago
Onsite Full Time Other

Responsibilities

  • Collaborate with product managers and engineers (PED) to define and prioritize product requirements, ensuring technical feasibility and alignment with user needs.
  • Capture, document, and communicate client requirements with the core team while adhering to the agreed upon format to convey priority.
  • Proactively identify and manage risks and dependencies across cross-functional teams, advocating for solutions and driving efficient execution.
  • Develop, utilize, and perform effective test strategies to ensure quality and performance of implemented features.
  • Document technical specifications and maintain clear communication with stakeholders throughout the development process.
  • Contribute to the continuous improvement of our development processes and tools, promoting a culture of innovation and agility.
  • Stay abreast of emerging technologies and industry trends, proactively suggesting opportunities for product enhancement.
  • Technical Support and Troubleshooting.
  • Client Training and Education on Ready Software tools.
  • Work closely with engineering, product, and operations teams to optimize AI utilization, flag risks/blockers, and drive continuous improvement in workflows.

Qualifications

  • Bachelor's degree with an emphasis on computer science, engineering, or similar technical field.
  • 2-3 years experience working in an engineering role.
  • Strong understanding of Agile development methodologies and experience working in cross-functional teams.
  • Ability to write clean, maintainable, and efficient code in at least one relevant programming language (e.g., React, Python etc).
  • Demonstrated understanding of user experience (UX) principles and practices.
  • Strong analytical and data-driven approach to problem-solving.
  • Basic understanding of web technologies such as HTML5, CSS3, and web APIs.
  • Experience with AWS Bedrock, Python (including SQL knowledge), CI/CD (Docker, AWS), MLflow + Airflow (good to have), and Langchain or Pydantic-AI.
  • Knowledge of LLM model evaluation, RAG architectures, LLM MCP servers, and LLM prompt engineering & function calls.

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