Software Engineer (AI Automation)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Software Engineer (AI Automation): Designing and building AI-powered systems and internal tools to drive operational efficiency with an accent on LLM integration, RAG pipelines, and intelligent automation. Focus on architecting scalable solutions within the Microsoft Azure ecosystem and integrating AI capabilities into mortgage technology platforms.
Location: Hybrid position; must be located within driving distance of a Flat Branch office in AR, FL, IA, KS, MI, MO, NE, OK, TN, or TX.
Company
is a mortgage lending company focused on leveraging technology to streamline business operations and improve service delivery.
What you will do
- Architect and implement AI-powered solutions including LLM integrations and RAG pipelines.
- Develop and maintain backend services, APIs, and data pipelines using Python.
- Manage automation workflows leveraging Microsoft Power Platform and Azure cloud services.
- Integrate AI capabilities with existing mortgage technology platforms like Encompass.
- Design and maintain cloud infrastructure on Azure with a focus on security and scalability.
- Collaborate with business stakeholders to identify high-impact automation opportunities.
Requirements
- 5+ years of professional software engineering experience.
- Proficiency in Python and frameworks such as FastAPI, Flask, or Django.
- Hands-on experience with LLM APIs and orchestration frameworks like LangChain or LlamaIndex.
- Experience implementing RAG pipelines and vector databases.
- Proficiency with Microsoft Azure cloud services and Power Platform.
- Must be located within driving distance of a Flat Branch office in AR, FL, IA, KS, MI, MO, NE, OK, TN, or TX.
Nice to have
- Experience in the mortgage, financial services, or fintech industry.
- Familiarity with Encompass LOS.
- Experience with prompt engineering, fine-tuning, or model evaluation.
Culture & Benefits
- Opportunity to work at the intersection of software engineering and applied AI.
- Collaborative environment working closely with business and technology leadership.
- Focus on engineering best practices including code reviews and documentation.
- Exposure to modern cloud infrastructure and automation tooling.
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