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Senior AI Engineer

Q1 Technologies, Inc

  • Biloxi, MS
  • Today

    Highlights

    The Senior AI Engineer is responsible for designing, developing, and deploying enterprise-grade artificial intelligence solutions, with a strong focus on large language models (LLMs), machine learning, and applied AI use cases. This position will work closely with Data & Analytics, Enterprise Applications, Product Management, and business units to deliver capabilities such as intelligent automation, AI-powered member experiences, predictive modeling, and decision support systems.
    Q1 Technologies, Inc

    Numbers & Facts

    LocationBiloxi, MS
    IndustryComputer/IT Services
    Company Size500 to 999 employees
    Year Founded1990
    Websitehttp://q1tech.com/

    Description

    Job Description: Bill Rate: MAX CONFIRMED $75
    Location: ONSITE- Biloxi, MS
    Duration: 6 months

    Role: Senior AI Engineer

    Descriptions:

    Summary
    The Senior AI Engineer is responsible for designing, developing, and deploying enterprise-grade artificial intelligence solutions, with a strong focus on large language models (LLMs), machine learning, and applied AI use cases. This role enables measurable business value by translating complex data and business problems into scalable AI-driven solutions across the organization.
    This position will work closely with Data & Analytics, Enterprise Applications, Product Management, and business units to deliver capabilities such as intelligent automation, AI-powered member experiences, predictive modeling, and decision support systems. The Senior AI Engineer plays a critical role in advancing the credit union's AI strategy, ensuring solutions are secure, scalable, and aligned with enterprise governance and regulatory expectations.
    Key Responsibilities
    • Design, develop, and deploy AI/ML solutions, including LLM-powered applications and intelligent automation
    • Evaluate and integrate leading LLM platforms (e.g., GPT, Claude, Gemini, LLaMA, Mistral)
    • Build and optimize prompt engineering, RAG, and fine-tuning strategies
    • Develop scalable APIs and AI-enabled services integrated with enterprise systems
    • Partner with Data & Analytics teams to leverage enterprise data platforms
    • Implement vector databases, embeddings, and semantic search capabilities
    • Ensure AI solutions meet enterprise standards for security, compliance, and scalability
    • Collaborate with Product Managers and engineering teams within pod structures
    • Monitor and optimize model performance, cost, latency, and accuracy
    • Stay current with advancements in AI and LLM ecosystems
    Leadership Responsibilities
    • Lead with integrity, accountability, and ownership
    • Act as a technical leader and mentor for AI best practices
    • Influence cross-functional teams without authority
    • Promote responsible and ethical use of AI
    • Support adoption of AI capabilities across the organization
    Essential Functions
    • Design and implement AI/ML models including LLM-based solutions
    • Develop end-to-end AI pipelines from ingestion to deployment
    • Build and optimize RAG architectures using enterprise data
    • Collaborate with architects on scalability and integration patterns
    • Develop reusable AI services and frameworks
    • Integrate AI capabilities into core platforms
    • Establish monitoring frameworks for model performance and reliability
    • Ensure compliance with governance and regulatory requirements
    • Translate business problems into AI-driven solutions
    Knowledge and Skills
    • Strong understanding of LLMs, prompt engineering, and model behavior
    • Experience with ML frameworks such as PyTorch or TensorFlow
    • Knowledge of RAG architectures and vector search
    • Experience with APIs, microservices, and distributed systems
    • Familiarity with MLOps and CI/CD pipelines
    • Strong programming skills in Python and SQL
    • Ability to evaluate build vs buy vs integrate decisions
    • Strong problem-solving and communication skills
    Education
    Bachelor's degree in Computer Science, Data Science, Machine Learning, or related field required. Master's degree preferred.
    Experience and Other Requirements
    • 5–8+ years of experience in software engineering or AI development
    • Hands-on experience with multiple LLM platforms
    • Experience with agent-based AI systems
    • Experience deploying AI solutions in cloud environments
    • Experience with enterprise data platforms such as Databricks
    • Experience with RAG and vector databases
    • Familiarity with LangChain or similar frameworks
    • Experience working in Agile/Kanban environments
    • Strong understanding of data privacy and security
    Preferred Qualifications
    • Experience fine-tuning transformer-based models

    • Familiarity with financial services or credit unions
    • Experience integrating AI into core banking platforms
    • Exposure to multi-modal AI
    • Experience with implementing AI solutions within the financial industry (banks or credit unions).
    Interpersonal Skills
    Strong interpersonal and influencing skills. Ability to collaborate across teams and communicate effectively.
    Certificates, Licenses and Registrations Relevant certifications in AI/ML or cloud platforms preferred.


    Keyword:
    Skills: Digital : Application Programming Interface (API)~Digital : Natural Language Processing (NLP)~Digital : Artificial Intelligence(AI)~Compliance : Data Privacy~Agile Specialisation Experience Required: 6-8

    About Company

    Q1 consists of experienced and recognized experts providing the capability to respond to market demand in order to provide professional services for our clients including Enterprise software implementations, application integration and technical / functional support.

    Q1 has steadily grown into a Quality IT services and solutions organization with the average experience of our team being over 10 years. We have continuously met or exceeded client expectations by delivering professional services and project implementations on time and under budget to help clients truly recognize return on investment.

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