AI Engineer (HYBRID - DALLAS, TX LOCAL ONLY)

Role: AI Engineer

Employment type: Contract

Experience:

• Bachelor’s degree in Computer Science, Data Science, Information Systems, or related field.
• 5–10 years experience in AI/ML engineering, NLP
• Experience building and deploying chatbots using LLMs, RAG, or conversational AI frameworks.
• Strong skills in Python, ReactJS, JavaScript/TypeScript, REST APIs, cloud platforms ( AWS).
• Experience with vector databases, prompt engineering, and ML frameworks (PyTorch, TensorFlow).
• Understanding of DevOps practices, CI/CD, version control, and automated testing.

Job Description:

The AI Engineer designs, develops, and deploys AI-powered solutions that enhance automation, decision-making, and user engagement across the organization. This role focuses heavily on building, training, and maintaining internal enterprise chatbots and external public-facing chatbots, integrating them into existing systems while ensuring security, reliability, and compliance.

Key Responsibilities:

Chatbot Development (Internal & External)

• Architect, build, and maintain internal chatbots that support employees, automate workflows, and integrate with enterprise systems (e.g., CRM, GIS, Snowflake, case management, content platforms ,etc).
• Design and deploy reusable internal and external/public facing chatbots to improve resident/customer experience, including informational assistants, service triage bots, and multilingual support.
• Implement Retrieval Augmented Generation (RAG), orchestration pipelines, prompt engineering, and guardrails for accuracy, compliance, and safe responses.
• Implement Data grounding, Observability and enable auditing within the chatbot as document the source of the data.
• Integrate chatbots with APIs, databases, enterprise apps, and cloud services using secure authentication patterns.

AI & Model Development

• Fine tune foundation models or train custom models for classification, summarization, conversational AI, and natural language processing.
• Evaluate models for bias, hallucination, safety, and performance; implement monitoring and observability dashboards.

System Integration

• Work across departments to identify use cases and integrate AI into business processes.
• Collaborate with developers, data engineers, and architects to build scalable AI pipelines and microservices.

MLOps & Deployment

• Develop CI/CD workflows for model deployment.
• Implement testing frameworks including:
  • AI language model integration testing
  • Inference policy guardrail validation
  • Load, performance, stress, and chaos testing

Data Management

• Support data preparation, labeling, feature engineering, and synthetic data creation for training conversational agents.
• Ensure compliance with PHI, PII, CJIS, data masking, and security policies.

Collaboration & Stakeholder Engagement

• Partner with cross functional teams, including Public Health, Community & other departments.
• Gather business requirements and translate them into technical solutions.

Documentation & Reporting

• Maintain documentation for architectures, workflows, prompts, policies, and testing procedures.
• Produce metrics dashboards on model quality, chatbot analytics, and performance.