Just Appraised

We streamline the change of ownership process for local government tax assessment offices.

Senior Software Engineer – AI

Full-stack EngineerSoftware EngineerFull TimeRemoteTeam 11-50H1B SponsorCompany SiteLinkedIn

Location

United States

Posted

31 days ago

Salary

Not specified

Bachelor Degree5 yrs expEnglishAWSCloudDockerPostgresPython

Job Description

• Build and evolve our Conversation Engine powering pre-drafted email, chat, and voice responses, including conversation state, memory, and high-quality response generation. • Own the RAG pipeline end-to-end : document ingestion, chunking strategies, embeddings, indexing, retrieval (hybrid/vector), reranking, and grounded response generation. • Implement AI Tooling / function calling to connect LLM workflows to internal systems (e.g., account lookup, case context retrieval, knowledge base queries ) with strong validation and safe execution patterns. • Design evaluation and quality systems for AI features: offline eval harnesses, golden datasets, human feedback loops, monitoring for hallucinations/grounding, and regression prevention. • Collaborate with cross-functional teams to define, design, and ship new features. • Work closely with business stakeholders and customers to translate requirements into technical specifications and documentation. • Mentor and support engineering team members, promoting team efficiency and growth. • Troubleshoot and debug complex issues, ensuring timely resolution and platform stability. • Optimize application performance, reliability, and scalability, and uphold high standards for clean, maintainable code. • Identify and proactively address technical debt and performance bottlenecks to drive iterative product improvement.

Job Requirements

  • 5+ years of professional experience in Python development.
  • 5+ years of experience with relational databases (e.g., PostgreSQL).
  • 2+ years of experience with cloud environments, particularly AWS.
  • Proven experience working with Large Language Models (LLMs) and building production-ready RAG pipelines.
  • Strong proficiency in API design, data modeling, relational database design, and testing methodologies.
  • Proficiency with modern DevOps practices: version control (Git), containerization (Docker), CI/CD (GitHub Actions), and automated testing frameworks.

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