AI /ML Engineer

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.

Required Skills

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 Cloud

•             AWS Bedrock

•             Amazon SageMaker

•             AWS Lambda

•             API Gateway

•             ECS/EKS

•             S3

•             DynamoDB

•             CloudWatch

•             IAM

Vector Databases

•             Pinecone

•             Weaviate

•             ChromaDB

•             OpenSearch Vector Engine

•             FAISS

•             Milvus

Programming

•             Python (Mandatory)

•             LangChain

•             LangGraph

•             LlamaIndex

•             FastAPI

•             REST APIs

Data & Integration

•             SQL

•             NoSQL Databases

•             ETL Pipelines

•             Data Modeling

•             API Integration

DevOps & MLOps

•             Docker

•             Kubernetes

•             CI/CD Pipelines

•             GitHub Actions

•             Terraform

•             Model Monitoring and Governance

Required Skills for candidate to Qualifiy:-

•             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.

Education

•             Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

Nice to Have

•             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.