Senior AI Systems Analyst

Systems EngineerSystems EngineerFull TimeRemoteTeam 5,001-10,000H1B SponsorCompany SiteLinkedIn

Location

Kansas + 1 moreAll locations: Kansas, Missouri

Posted

58 days ago

Salary

$110K - $130K / year

Bachelor Degree7 yrs expEnglishCloudDockerKubernetesPy Torch

Job Description

• Collaborate with stakeholders to understand business needs and translate them into detailed requirements and agent specifications. • Analyze and document existing process to identify areas for improvement and automation. • Create and maintain comprehensive documentation, including requirements, system design, and user manuals. • Design, develop, and deploy basic autonomous AI agents using generative AI tools and frameworks such as Gemini Enterprise and Copilot. • Integrate AI agents with existing business software, tools, and APIs. • Review test plans to ensure the quality and reliability of AI agent outputs against expected business outcomes. • Coordinate with users to conduct User Acceptance Testing (UAT) and obtain sign-off for deployment. • Oversee the rollout and deployment of AI agents into production environments. • Act as the primary point of contact for stakeholders, providing regular updates on project progress. • Communicate complex concepts, process and solutions to both technical and non-technical audiences. • Manage stakeholder expectations and ensure that the final solution meets their needs. • Collaborate with development team to translate business needs to requirements. • Foster a culture of innovation, collaboration, and continuous learning within the team. • Stay up-to-date with the latest advancements in generative AI, machine learning, and related technologies.

Job Requirements

  • 5+ years of experience as a Systems Analyst and a 2+ years focus as an AI Developer.
  • Proficiency in AI tools and frameworks such as Gemini Enterprise and Copilot.
  • Experience fine-tuning transformer models using frameworks such as PyTorch.
  • Familiarity with vector databases (e.g., Pinecone, FAISS, Weaviate, Chroma) and RAG pipelines.
  • Strong grasp of prompt engineering, model evaluation, and RLHF or feedback learning methods.
  • Understanding of cloud-native ML deployment (Docker, Kubernetes, Vertex AI pipelines).

Benefits

  • Health insurance
  • Professional development opportunities

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