AI Engineer (Advanced GenAI & Production AI Focus)

Position: AI Engineer (Advanced / GenAI & Production AI Focus)
Location: Dallas TX (On-site / Hybrid)
Type Contract
Job Description-:

We are looking for a highly skilled AI Engineer to design build and deploy production-grade AI

systems including LLM-powered applications predictive models and intelligent automationsolutions. This role focuses on technical execution scalability and performance optimization

working closely with FDEs and business stakeholders.

Key Responsibilities

1. AI/ML Model Development

• Develop models for:
• Forecasting (demand supply chain)
• Predictive maintenance
• Anomaly detection
• Optimization problems
• Implement deep learning using PyTorch / TensorFlow.

2. Generative AI & LLM Systems

• Build and deploy:

• RAG (Retrieval Augmented Generation) systems
• Embedding pipelines
• AI agents and copilots
• Integrate LLM APIs (OpenAI Azure OpenAI etc.)
• Optimize prompt engineering and inference pipelines.

3. Production Deployment (MLOps)

• Deploy models via:

• REST APIs
• Streaming pipelines
• Batch inference systems
• Implement CI/CD for ML pipelines
• Handle model versioning monitoring retraining

4. Data Engineering Collaboration

• Work with FDEs to integrate AI models into:

• Data pipelines
• Enterprise systems
• Process structured unstructured data efficiently

5. Real-Time AI Systems

• Build low-latency inference systems
• Optimize model serving for scalability and performance
• Support real-time decision systems

6. Domain-Focused AI Solutions

Develop AI for:

• Manufacturing optimization
• Supply chain forecasting
• Process automation
• Quality inspection (computer vision if required)

Technical Skills Required

AI/ML

• Strong ML fundamentals
• Deep learning (CNNs RNNs Transformers)
• Time-series analysis

GenAI

• LLMs embeddings vector DBs (FAISS Pinecone etc.)
• RAG pipelines and prompt engineering

Programming

• Python (advanced)
• NumPy Pandas Scikit-learn

• MLOps & Deployment
• Docker Kubernetes
• MLflow / Azure ML / SageMaker

Data & Systems

• SQL big data tools
• Spark / Kafka (good to have)

Experience Required

• 3 10 years (depending on level)
• Experience deploying production AI systems
• Exposure to real-time or enterprise AI solutions
• Success Metrics
• Model performance and accuracy
• Reliability and scalability of deployed systems
• Adoption of AI solutions in business workflows
• Speed of deployment (POC Production)