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.