Software Engineer - Full Stack, Information Technology

ServiceLink•Plano, TX

About The Position

As we continue to transform the mortgage landscape, we are embracing an AI‑First mindset—leveraging artificial intelligence, automation, and intelligent systems to reimagine how our enterprise applications operate at scale. Your expertise will play a pivotal role in shaping this evolution, helping us integrate AI-driven insights, modern engineering practices, and innovative architectures into our products. If you are passionate about fostering a culture that empowers creative, collaborative problem‑solving—and are motivated by opportunities to apply emerging technologies to real‑world challenges—we encourage you to apply today. The ideal candidate is highly driven to be a key contributor in revolutionizing the industry. This is an exciting time to join us and help define the future of intelligent mortgage technology.

Requirements

1+ years of software engineering experience (or equivalent).
Proficiency in one or more languages: Python, C#, TypeScript/JavaScript, or similar.
Experience using or integrating AI development tools (e.g., LLM-based code assistants, automated testing tools, vector DBs, embedding models).
Strong understanding of distributed systems, APIs, microservices, or cloud-native development.
Familiarity with modern DevOps practices (Docker, Kubernetes, CI/CD pipelines).
Ability to work collaboratively in an agile, fast-paced environment.
Curiosity and a continuous learning mindset — especially around AI and automation.
Graduate degree (BS/MS/PhD) in Electrical Engineering, Computer Science, Mathematics, or related technical field
Experience with data structures, algorithm design, problem solving, and complexity analysis
Experience defining system architectures and exploring technical feasibility trade-offs

Nice To Haves

Experience fine‑tuning LLMs, building AI agents, or developing prompt‑driven applications.
Knowledge of MLOps, RAG systems, or multimodal AI integration.
Background in data engineering or applied machine learning.
Contributions to open-source projects or AI developer communities.

Responsibilities

Build high‑quality software solutions using modern engineering best practices, supported by AI-assisted development tools.
Apply AI copilots and automated agents to enhance coding, testing, debugging, documentation, and system design workflows.
Develop and maintain scalable services, APIs, and applications across our technology stack.
Create internal tools, scripts, and AI‑powered automations that improve engineering productivity and reduce operational overhead.
Translate product requirements and user needs into clear, elegant technical solutions.
Collaborate closely with product managers, designers, and cross‑functional engineering teams to deliver features from concept to production.
Use AI‑driven insights to explore solution trade-offs, improve development velocity, and validate architectural decisions.
Contribute to architectural reviews, technical design documents, and system-level decision-making.
Improve code quality, reliability, and performance through unit testing, AI‑enhanced test generation, and continuous integration pipelines.
Stay current on emerging AI tools, frameworks, and engineering trends—and help shape how our team adopts and operationalizes them.
Design, develop, and ship scalable, reliable, and high‑performance software solutions.
Leverage AI tools (e.g., GitHub Copilot, Cursor, Clause Code, M365 Copilot, Azure OpenAI, LLM-based agents) to enhance coding, design, testing, and documentation workflows.
Build internal tooling, agents, and automations that boost developer productivity and code quality.
Collaborate with product, design, and engineering teams to translate business requirements into technical solutions.
Implement modern software engineering best practices, including CI/CD, automated testing, and observability.
Analyze complex problems and use AI‑driven approaches to accelerate decision‑making and solution exploration.
Contribute to architectural discussions and drive continuous improvement across engineering processes.