Lead Gen AI Engineer

CCS INC; Plano (TX); On-site; Full time

Benefits offered by this job

Bonus based on performance

Dental insurance

Health insurance

Vision insurance

Job summary

A technology company in Plano, Texas seeks an experienced software engineer to design and deploy scalable GenAI applications. This role involves building robust architectures using LLMs, integrating GenAI capabilities into enterprise systems, and implementing responsible AI practices. Candidates should have over 8 years of experience in software engineering, strong programming skills in Python, and familiarity with cloud platforms like AWS. A competitive benefits package is offered including performance bonuses and health insurance.

Qualifications

• 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.

Responsibilities

• Design scalable and robust GenAI architectures using LLMs.
• Integrate GenAI capabilities into enterprise platforms with APIs.
• Monitor and optimize model performance, latency, and cost.

Skills

Software engineering

GenAI applications

Programming in Python

LLMs, embeddings, vector databases

Cloud platforms (AWS, Azure, GCP)

Containerization (Docker, Kubernetes)

CI/CD for ML workflows

AI/ML certifications

Education

AWS AI certification

Tools

Transformers

LangChain

Hugging Face

FAISS

Pinecone

Weaviate

MLflow

DVC

SageMaker

Bedrock

Job description

Benefits:

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

Qualifications:

• 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)
• 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.