Ideal Candidate: A hands-on engineer who can take a Generative AI solution from concept to production, with strong expertise in LLMs, Prompt Engineering, RAG, Python, and cloud-based AI services . Work closely with data engineers, software developers, product teams, and business stakeholders to deliver AI solutions.
Numbers & Facts
Location
Plano, TX
Description
Role: Gen AI Engineer/ Architect
Location: PLano TX ( Only local candidat
Duration: 12 months plus
Key Responsibilities
Design, develop, and implement Generative AI solutions using LLMs and foundation models.
Build AI applications such as chatbots, virtual assistants, document intelligence, and automated content-generation solutions.
Develop and optimize prompts and prompt engineering strategies to improve model performance and accuracy.
Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases and enterprise data sources.
Integrate AI models through APIs and frameworks such as LangChain, LlamaIndex, or similar technologies.
Fine-tune, evaluate, and optimize machine learning and language models where required.
Work closely with data engineers, software developers, product teams, and business stakeholders to deliver AI solutions.
Develop scalable and secure AI applications and deploy them in cloud environments.
Monitor AI model performance, accuracy, reliability, and responsible AI considerations.
Stay updated with the latest advancements in Generative AI, LLMs, and machine learning technologies.
Required Skills & Qualifications
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
Strong programming experience in Python.
Hands-on experience with Generative AI and Large Language Models (LLMs).
Experience with Prompt Engineering and optimizing prompts for different use cases.
Knowledge of RAG architectures, embeddings, and vector databases.
Experience with frameworks such as LangChain, LlamaIndex, Hugging Face, or similar.
Understanding of machine learning and NLP concepts.
Experience integrating AI/ML models through APIs and microservices.
Knowledge of cloud platforms such as Azure, AWS, or Google Cloud.
Experience with databases, APIs, Git, and software development best practices.
Preferred Skills
Experience with OpenAI, Azure OpenAI, Anthropic, or open-source LLMs.
Knowledge of vector databases such as Pinecone, FAISS, Chroma, or Weaviate.
Experience with MLOps, Docker, Kubernetes, and CI/CD pipelines.
Knowledge of AI safety, responsible AI, and data privacy principles.
Experience deploying AI solutions in enterprise environments.
Key Competencies
Strong analytical and problem-solving skills.
Ability to translate business requirements into AI-driven technical solutions.
Excellent communication and collaboration skills.
Passion for exploring and implementing emerging AI technologies.
Ideal Candidate: A hands-on engineer who can take a Generative AI solution from concept to production, with strong expertise in LLMs, Prompt Engineering, RAG, Python, and cloud-based AI services.