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Senior Databricks Developer Jobs in Mississippi (NOW HIRING)

Prophecy Technologies

Senior AI Engineer

Biloxi, MS · On-site

$93K - $127K/yr

The Senior AI Engineer is responsible for designing, developing, and deploying enterprise-grade ... Databricks. * Experience with RAG and vector databases. * Familiarity with LangChain or similar ...

Hancock Whitney Bank

Data Architect 2

Whitney, MS · On-site

$59.25 - $76.25/hr

Experience with Cloud Data storage technologies like Snowflake, Databricks, Azure, AWS or similar ... Determines and resolves problems with other systems analysts, programmers, and systems users.

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Senior AI Engineer

Prophecy Technologies

Biloxi, MS • On-site

$93K - $127K/yr

Full-time

Posted 6 days ago

Job description

Role Overview:
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 translates complex data and business problems into scalable AI-driven solutions, enabling measurable business value across the organization. The position involves close collaboration 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. This role is critical 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.
  • Act as a technical leader and mentor for AI best practices, promoting responsible and ethical use of AI.
  • Develop end-to-end AI pipelines from ingestion to deployment and build/optimize RAG architectures.
  • Establish monitoring frameworks for model performance and reliability.
  • Translate business problems into AI-driven solutions.

Required 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.
  • Hands-on experience with multiple LLM platforms and agent-based AI systems.
  • Experience deploying AI solutions in cloud environments and 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.
  • Strong problem-solving and communication skills.

Qualifications:
  • 5-8+ years of experience in software engineering or AI development.
  • Bachelor's degree in Computer Science, Data Science, Machine Learning, or related field required.
  • Master's degree preferred.
  • Relevant certifications in AI/ML or cloud platforms preferred.

Preferred Skills:
  • 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.

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