GenAI Data Engineer (Offshore)

Company Description YemPover Inc. is a global leader in digital transformation and consulting, supported by industry professionals with decades of experience helping clients realize their full potential and accelerate growth. The company’s certified experts bring deep knowledge across diverse industry verticals, enabling tailored solutions for complex business challenges. YemPover is recognized for its ability to staff quickly and deliver high-quality support and services on demand. This focus on excellence and agility creates a dynamic environment for professionals who want to work on impactful projects with international clients.
Role Description The GenAI Data Engineer (Offshore) role is a remote, contract position focused on building and maintaining data pipelines and infrastructure to support generative AI solutions. Day-to-day responsibilities include designing and implementing scalable data workflows, performing data modeling for AI and analytics use cases, and developing robust ETL processes to integrate data from multiple sources. The role involves managing and optimizing data warehousing environments, collaborating with data scientists and AI engineers to ensure data availability and quality, and contributing to data analytics initiatives that improve model performance and business insights. The engineer will also participate in code reviews, documentation, and best practices for data governance, security, and reliability in a distributed team setting.
Must Have
5+ years of Data Engineering experience, with 2+ years in GenAI/LLM solutions
Strong Python and SQL skills
Hands-on experience with AWS Bedrock or equivalent GenAI platforms
Experience building RAG pipelines, embeddings, and vector search
Experience with LangChain or LlamaIndex
Strong AWS data engineering experience with AWS Glue, Lambda, Kinesis, or Step Functions
Experience with at least one vector database: Pinecone, FAISS, Chroma, or OpenSearch
Experience integrating LLMs/APIs with enterprise data and applications
Strong understanding of data pipelines, orchestration, data modeling, and MLOps
Experience with at least one modern data platform: Snowflake, Databricks, or Redshift
Nice to Have
Experience with Amazon SageMaker, Bedrock Agents, or Vertex AI
Experience with Anthropic Claude, Amazon Titan, OpenAI GPT, or Llama
Knowledge of LlamaIndex, AutoGen, CrewAI, or Semantic Kernel
Experience with Airflow, Prefect, GitHub Actions, or AWS CodePipeline
Knowledge of Docker and Kubernetes
Experience with data observability tools such as Monte Carlo, DataHub, or Marquez
Experience with LLM evaluation, prompt optimization, model monitoring, and hallucination reduction
Knowledge of Responsible AI, data governance, SOC2, GDPR, or CCPA
AI/ML certifications such as AWS ML Specialty or DeepLearning.AI GenAI
Experience working with unstructured data such as documents, images, text, and logs

Work arrangement
No