Lead Gen AI Engineer

Ccs • Plano, TX

3h • $85 - $110

About The Position

The company is passionate about CX. The collective experiences in leadership roles across firms enable CCS to bring passion, perspective, data-driven decision making to guide, advise, and support organizations throughout their CX journey. We are a “people” company. We are a flat organization. We believe the best idea win. We believe in radical truth. We attract strong-minded people with fierce intellect. Mission Statement: CCS is recognized as a leader in the Contact Center space. Our longstanding history and industry-leading position speak to our success in providing CX solutions centered around the leaders in contact center solutions and strategic technology partners that empower organizations to actualize ROI and sustain a truly competitive advantage in a fast-changing CX environment.

Requirements

• 8+ years of software engineering and development experience
• Proven experience in building and deploying GenAI applications in production.
• Strong programming skills in Python and familiarity with GenAI libraries (Transformers, LangChain, Hugging Face, etc.).
• Deep understanding of LLMs, embeddings, vector databases (e.g., FAISS, Pinecone, Weaviate).
• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Familiarity with CI/CD for ML workflows and versioning tools like MLflow or DVC.
• Hands-on experience designing and building cloud-native solutions (preferably on AWS)
• Exposure to GenAI tools and frameworks (e.g., LLMs, vector databases, prompt orchestration, LangChain, Bedrock)
• Familiarity with AWS AI/ML services (e.g., SageMaker, Bedrock, Comprehend, Lex)

Nice To Haves

• AWS AI certification

Responsibilities

• Design scalable and robust GenAI architectures using LLMs, multimodal models, and retrieval-augmented generation (RAG).
• Fine-tune foundation models using domain-specific data.
• Implement prompt engineering, instruction tuning, and reinforcement learning from human feedback (RLHF).
• Integrate GenAI capabilities into enterprise platforms using APIs, SDKs, and orchestration tools.
• Implement responsible AI practices including bias detection, hallucination mitigation, and explainability.
• Monitor and optimize model performance, latency, and cost.
• Use techniques like quantization, distillation, and caching to improve efficiency.

Benefits

• Bonus based on performance
• Dental insurance
• Health insurance
• Vision insurance

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed