Role: Oracle DBA
Work Location: Alpharetta, GA 30004
Contract duration: 12months
Work Location: Alpharetta, GA 30004
Contract duration: 12months
Must Have Skills
Oracle DB
Database Architect
Good Communication
Oracle DB
Database Architect
Good Communication
Nice to have skills
Communication
Leadership
Detailed Job Description
Required skills Informatica Powercenter, Oracle, SQL, Unix Shell Scripting Very strong skill set in determining root cause and solution with regard to data reconciliation Detailed understanding and vast experience with the Reporting system Subject matter expert in the current ETL application Lead developer in designing new functionality to meet business requirements DesignDevelop Oracle database table structures, packages, procedures ETL applications using Informatica Power Center, PLSQL and
Top 3 responsibilities you would expect the Subcon to shoulder and execute
Individual contributor
on time delivery
Zero Escalations
Position 2
Role: GEN AI Engineer
Work: Dallas, TX or Charlotte, NC
Hybrid. Will consider candidates willing to relocate to client’s location
Contract duration: 6+ Must Have Skills:
⦁ GEN AI
⦁ Agentic AI
⦁ ML Ops
⦁ Python
⦁ ML
⦁ Data Science
⦁ RAG
⦁ LLM
Nice to Have Skills:
⦁ GCP
⦁ Prompt Engineering
Detailed Job Description:
Key Responsibilities:
⦁ Design and implement Generative AI models for text, image, or multimodal applications.
⦁ Develop prompt engineering strategies and embedding-based retrieval systems.
⦁ Integrate Gen AI capabilities into web applications and enterprise workflows.
⦁ Build agentic AI applications with context engineering and MCP tools.
Required Skills & Qualifications:
⦁ 10+ years of hands-on experience in AI, Data science, ML, GEN AI.
⦁ Strong hands on experience designing and deploying Retrieval-Augmented Generation (RAG) pipelines
⦁ Strong MLOps/LLMOps experience with CI/CD automation,
⦁ Extensive experience with LangChain, LangGraph, and agentic AI patterns including routing, memory, multi-agent orchestration, guardrails, and failure recovery.
⦁ Experience in Cloud-native engineering across AWS (SageMaker, Lambda, ECS/Fargate, S3, API Gateway, Step Functions) and GCP (Vertex AI) for scalable AI delivery
⦁ Experience in Developing microservices and API development using FastAPI, REST APIs, Pydantic/JSON schemas, Docker, and Kubernetes for low-latency serving.
⦁ Strong Hands-on experience with vector databases and semantic search technologies including Pinecone, FAISS, ChromaDB, and embedding lifecycle management
⦁ Strong proficiency in Python and AI/ML frameworks (PyTorch, TensorFlow).
⦁ Hands on experience using session and memory for building multi-agent systems along with using MCP tools.
⦁ Hands-on experience with LLMs, transformers, and Hugging Face ecosystem.
⦁ Knowledge and experience with vector databases and RAG technique for semantic search.
⦁ Familiarity with cloud AI services (AWS SageMaker, Azure OpenAI, GCP Vertex AI).
⦁ Understanding of MLOps practices for scalable AI deployment.
⦁ Strong experience in working with LLM fine-tuning with LoRA, QLoRA, PEFT,
⦁ Strong experience in Architected advanced RAG systems using Pinecone, FAISS, Weaviate, Chroma, hybrid retrieval, and custom embeddings,
⦁ Strong experience in Designing end-to-end LLMOps/MLOps pipelines using MLflow, DVC, SageMaker Pipelines, Vertex AI Pipelines, and GitHub Actions
⦁ Experience in using cloud-native AI systems on AWS (SageMaker, Lambda, EKS, EC2, Step Functions, S3, Glue) and GCP Vertex AI, supporting high-volume inference and secure enterprise operations
⦁ Experience in developing multi-agent orchestration workflows using LangGraph and CrewAI for tool-calling, validation agents, automated reasoning, and workflow supervision
Top 3 responsibilities you would expect the Subcon to shoulder and execute:
⦁ Strong experience in GEN AI, LLM, RAG,ML, DL,ML Ops, LLMOps, Cloud platform,Model servicing optimization, Python
⦁ Strong communication skills
⦁ Strong programming skills
Work: Dallas, TX or Charlotte, NC
Hybrid. Will consider candidates willing to relocate to client’s location
Contract duration: 6+ Must Have Skills:
⦁ GEN AI
⦁ Agentic AI
⦁ ML Ops
⦁ Python
⦁ ML
⦁ Data Science
⦁ RAG
⦁ LLM
Nice to Have Skills:
⦁ GCP
⦁ Prompt Engineering
Detailed Job Description:
Key Responsibilities:
⦁ Design and implement Generative AI models for text, image, or multimodal applications.
⦁ Develop prompt engineering strategies and embedding-based retrieval systems.
⦁ Integrate Gen AI capabilities into web applications and enterprise workflows.
⦁ Build agentic AI applications with context engineering and MCP tools.
Required Skills & Qualifications:
⦁ 10+ years of hands-on experience in AI, Data science, ML, GEN AI.
⦁ Strong hands on experience designing and deploying Retrieval-Augmented Generation (RAG) pipelines
⦁ Strong MLOps/LLMOps experience with CI/CD automation,
⦁ Extensive experience with LangChain, LangGraph, and agentic AI patterns including routing, memory, multi-agent orchestration, guardrails, and failure recovery.
⦁ Experience in Cloud-native engineering across AWS (SageMaker, Lambda, ECS/Fargate, S3, API Gateway, Step Functions) and GCP (Vertex AI) for scalable AI delivery
⦁ Experience in Developing microservices and API development using FastAPI, REST APIs, Pydantic/JSON schemas, Docker, and Kubernetes for low-latency serving.
⦁ Strong Hands-on experience with vector databases and semantic search technologies including Pinecone, FAISS, ChromaDB, and embedding lifecycle management
⦁ Strong proficiency in Python and AI/ML frameworks (PyTorch, TensorFlow).
⦁ Hands on experience using session and memory for building multi-agent systems along with using MCP tools.
⦁ Hands-on experience with LLMs, transformers, and Hugging Face ecosystem.
⦁ Knowledge and experience with vector databases and RAG technique for semantic search.
⦁ Familiarity with cloud AI services (AWS SageMaker, Azure OpenAI, GCP Vertex AI).
⦁ Understanding of MLOps practices for scalable AI deployment.
⦁ Strong experience in working with LLM fine-tuning with LoRA, QLoRA, PEFT,
⦁ Strong experience in Architected advanced RAG systems using Pinecone, FAISS, Weaviate, Chroma, hybrid retrieval, and custom embeddings,
⦁ Strong experience in Designing end-to-end LLMOps/MLOps pipelines using MLflow, DVC, SageMaker Pipelines, Vertex AI Pipelines, and GitHub Actions
⦁ Experience in using cloud-native AI systems on AWS (SageMaker, Lambda, EKS, EC2, Step Functions, S3, Glue) and GCP Vertex AI, supporting high-volume inference and secure enterprise operations
⦁ Experience in developing multi-agent orchestration workflows using LangGraph and CrewAI for tool-calling, validation agents, automated reasoning, and workflow supervision
Top 3 responsibilities you would expect the Subcon to shoulder and execute:
⦁ Strong experience in GEN AI, LLM, RAG,ML, DL,ML Ops, LLMOps, Cloud platform,Model servicing optimization, Python
⦁ Strong communication skills
⦁ Strong programming skills
