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Role: AI /ML Engineer
Location: Fort Mill SC or New York NY
Experience: 8–12 Years
Job Summary
We are seeking a highly skilled AI Engineer with expertise in Generative AI, AWS Bedrock, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Vector Databases. The ideal candidate will be responsible for designing, developing, and deploying enterprise-grade AI solutions leveraging AWS AI services and modern data architectures.
This role requires hands-on experience in building scalable AI applications, integrating foundation models, implementing RAG frameworks, and deploying production-ready GenAI solutions.
Key Responsibilities
Generative AI
Role: AI /ML Engineer
Location: Fort Mill SC or New York NY
Experience: 8–12 Years
Job Summary
We are seeking a highly skilled AI Engineer with expertise in Generative AI, AWS Bedrock, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Vector Databases. The ideal candidate will be responsible for designing, developing, and deploying enterprise-grade AI solutions leveraging AWS AI services and modern data architectures.
This role requires hands-on experience in building scalable AI applications, integrating foundation models, implementing RAG frameworks, and deploying production-ready GenAI solutions.
Key Responsibilities
- Design and develop Generative AI solutions using AWS Bedrock and foundation models.
- Build and optimize RAG (Retrieval-Augmented Generation) pipelines using vector databases.
- Develop AI-powered applications including chatbots, virtual assistants, document intelligence, and agentic AI solutions.
- Integrate LLMs with enterprise applications, APIs, and data platforms.
- Design and maintain vector search architectures using Pinecone, Weaviate, OpenSearch, ChromaDB, or similar platforms.
- Develop scalable data ingestion, embedding, indexing, and retrieval pipelines.
- Implement prompt engineering, model evaluation, fine-tuning, and guardrails.
- Collaborate with Data Engineers, Solution Architects, and Product teams to deliver AI-driven solutions.
- Ensure security, scalability, observability, and governance of AI applications.
- Monitor model performance and continuously improve AI solution accuracy and efficiency.
- Stay current with emerging AI technologies, LLM frameworks, and cloud-native AI services.
Generative AI
- Strong understanding of LLMs and Generative AI concepts.
- Experience with RAG architecture and Agentic AI frameworks.
- Prompt Engineering and Model Evaluation.
- Fine-tuning and model optimization techniques.
- AWS Bedrock
- Amazon SageMaker
- AWS Lambda
- API Gateway
- ECS/EKS
- S3
- DynamoDB
- CloudWatch
- IAM
- Pinecone
- Weaviate
- ChromaDB
- OpenSearch Vector Engine
- FAISS
- Milvus
- Python (Mandatory)
- LangChain
- LangGraph
- LlamaIndex
- FastAPI
- REST APIs
- SQL
- NoSQL Databases
- ETL Pipelines
- Data Modeling
- API Integration
- Docker
- Kubernetes
- CI/CD Pipelines
- GitHub Actions
- Terraform
- Model Monitoring and Governance
- Experience with, Financial Services, or Life Sciences domains.
- Experience deploying AI solutions in production environments.
- AWS Certified Machine Learning Engineer or AWS Solutions Architect certification.
- Experience with multi-agent frameworks and autonomous AI systems.
- Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
- Knowledge of Anthropic Claude, Amazon Nova, Llama, Mistral, and OpenAI models.
- Experience with Knowledge Graphs.
- Experience with Databricks and Snowflake.
- Experience with Agentic AI and AI Orchestration frameworks.