GEN AI Engineer

Hello

Title : GEN AI Engineer

Contract : 12+ Months

Location : 5 days onsite in McLean, VA

Job Description :

• A GenAI Engineer in the US builds and deploys generative AI applications, models, and systems that create new content like text, images, or code. Responsibilities include fine-tuning large language models (LLMs), developing retrieval-augmented generation (RAG) pipelines, integrating vector databases, and working with cloud-based GenAI services.
• They often use frameworks such as LangChain, collaborate with cross-functional teams, and ensure the responsible deployment of AI solutions across various industries.

Required Skills :

• Model Development & Deployment: Design, develop, and deploy generative AI models and applications.
• LLM Optimization: Fine-tune and evaluate Large Language Models (LLMs) for performance and efficiency.
• Content Creation: Create new content such as text, images, and code using GenAI techniques like GANs or LLMs.
• RAG Pipeline Development: Build and integrate retrieval-augmented generation (RAG) pipelines with vector databases like Pinecone or FAISS.
• Prompt Engineering: Craft and optimize prompts for LLM-based applications.
• Data Preprocessing: Preprocess unstructured data (text, images, etc.) for LLM consumption.
• Cloud Integration: Integrate GenAI services from cloud platforms like AWS Bedrock, Azure OpenAI, or Google Cloud Vertex AI.
• Collaboration: Work with senior engineers, data scientists, and cross-functional teams to deliver solutions.
• Code Reviews & Documentation: Participate in code reviews and maintain documentation for GenAI models and applications.
• Troubleshooting: Identify and resolve issues related to generative AI models and implementations.

Essential Skills

• Programming: Strong software engineering skills, particularly in Python.
• Frameworks: Experience with GenAI frameworks like LangChain, LangGraph, or AutoGen.
• Cloud Platforms: Familiarity with cloud platforms such as AWS, Azure, or GCP.
• MLOps: Knowledge of MLOps tools and best practices for managing the AI lifecycle.
• APIs: Experience in developing and using APIs for model integration.
• Problem-Solving: Ability to solve ambiguous problems and navigate complex challenges

Thanks and Regards,

Naveen

US IT Recruiter

Conch Technologies Inc,

Direct: 901-317-3454

Email: [email protected]