Jr. Software Engineer - AI/LLM Applications

MountainSeed Appraisal Management LLC•Atlanta, GA

3h•Hybrid

About The Position

The Junior Software Engineer will be responsible for developing, testing, installing, and maintaining application systems based on pre-defined requirements and designs. In addition to core software engineering responsibilities, this role will contribute to the development and support of an AI-powered platform, working alongside senior engineers to build and enhance intelligent features. The selected candidate is expected to take full ownership of their work in production — this is not a build-and-hand-off role. The Junior Software Engineer will actively participate in production support, including incident response and change management, and will be accountable for the quality and reliability of the systems they own. He/she will report to the Chief Technology Officer and be based in Atlanta, GA.

Requirements

1–3 years of software development experience
Strong proficiency in Python (required — primary language for AI components and pipeline development)
Experience working with APIs and backend systems
Strong analytical and problem-solving skills with ability to review and analyze requirements
Willingness to take ownership of systems in production; outstanding attention to detail and meticulous approach to work

Nice To Haves

Experience with C# / .NET (preferred — Augur’s backend includes C# components)
Exposure to Large Language Models (LLMs) or AI/ML concepts; familiarity with prompt engineering and agentic AI workflows
Understanding of embeddings, semantic search, or vector databases (pgvector experience a plus)
Experience with AWS or other cloud platforms (AWS Bedrock, S3, Kubernetes experience a plus)
Exposure to monitoring, logging, or incident management processes; knowledge of Git version control system
College degree and/or equivalent experience in software engineering, computer science, or Commercial Real Estate industry is preferred
Ownership mindset and accountability for production systems; strong focus on output quality and user impact
Curiosity about AI behavior and failure modes; ability to work with non-deterministic systems and maintain rigorous output quality standards
Strong desire and ability to learn and grow in AI and software engineering; excellent communication skills, both written and verbal

Responsibilities

Assist in development and integration of AI-powered features, including automated workflows and intelligent data processing capabilities
Develop and refine prompts and AI configurations to improve accuracy, consistency, and reliability of AI-generated outputs across platform features
Support implementation and maintenance of Retrieval-Augmented Generation (RAG) pipelines, including vector embeddings, semantic search, and context assembly for LLM-driven workflows
Build and maintain data pipelines integrating internal and external data sources, APIs, and third-party services to support platform functionality
Evaluate AI outputs and assist in improving reliability — identifying and troubleshooting hallucinations, inconsistencies, and failure modes across a multi-model AI architecture
Develop application code in Python aligned with business and technical requirements, coding standards, and SDLC processes; participate in code reviews, testing, and deployment activities
Take full ownership of assigned systems and features in production — this role is accountable for the health, performance, and reliability of what it builds, not just delivery
Actively participate in production support as a primary owner — respond to incidents, perform root cause analysis, drive defect resolution, and manage changes to application logic, configurations, and deployments
Improve monitoring, logging, and alerting for owned systems and AI components; ensure issues are detected proactively rather than reactively
Collaborate with cross-functional teams to deliver scalable, multi-tenant solutions; contribute to design, code review, and testing activities to maintain high quality standards
Submit software products for review of compliance with best practices, standards, and enterprise architecture (code review)
Evaluate outcomes, report results, and document findings according to current standards; contribute to test suite covering unit and functional coverage across the appraisal pipeline
Assist in design solutions for approved projects and change requests, converting requirements into infrastructure and application software structures
Learn, use, and gain experience with AI tooling, testing frameworks, and techniques relevant to non-deterministic system behavior