Position : Agentic AI Engineer
Location: Reston Virginia
Direct Client Requirement
This is a mixed role where the resource will be operating a lot with Data, BI reporting, visualization as well as AI Agentic engineering. Will be creating reports and dashboards and developing AI models, chat bots and other AI products.
Looking for a resource with solid data engineering background along with BI reporting using either Power BI or tableau along with solid Python skills used for AI Agentic engineering.
Must have AWS cloud experience as well.
The resource must be at a technical lead level with over 10+ years of experience in Data engineering.
Must have 3+ years of AI experience with some agentic AI and other AI development skills.
Vector search, embeddings, and semantic retrieval concepts in practice
End-to-end RAG architecture and retrieval workflows
Depth in Python coding and implementation details.
3+ years of solid Python development skills.
10+ years of tableau and Power BI experience.
Required Skills:
AI & Software Engineering
3+ years of experience building production-level AI or ML systems, including LLMs, AI agents, or complex automation frameworks
3+ years of experience with Python and Python libraries such as Pandas, NumPy, and related data processing tools.
Experience with Large Language Models (LLMs), Machine Learning (ML), Deep Learning (DL), and Reinforcement Learning
Strong understanding and hands-on experience with Natural Language Processing (NLP).
Experience with AI agent frameworks and tools such as LangGraph, LangChain, TensorFlow, or PyTorch.
Experience optimizing workflows through intelligent automation and AI-driven solutions.
Experience integrating AI agents with APIs, cloud platforms, enterprise applications, and databases.[KN3.1]
Experience building and deploying AI pipelines on AWS SageMaker with Aurora PostgreSQL for data ingestion, analytics, and operational reporting.
Experience performing automated testing, troubleshooting, and application maintenance.
Experience with Software Development Lifecycle (SDLC) methodologies, including DevSecOps practices.
Experience with cloud platform - Amazon Web Services (AWS)
Experience developing RESTful services using Java and Spring Boot.
Experience managing CI/CD pipelines and containerized deployments using Kubernetes, Docker, Jenkins, or similar technologies.
Preferred experience using GitHub and collaborative development platforms.
Business Intelligence & Analytics
3+ years of experience designing and developing business intelligence solutions and enterprise reporting platforms.
Experience creating interactive dashboards and reports using tools such as Power BI, Tableau, or similar BI platforms
Hands-on expertise with SQL, data querying, and relational database concepts.
Experience developing data models, semantic layers, KPIs, scorecards, and performance metrics for business stakeholders.
Experience integrating and transforming data from multiple enterprise systems and APIs for reporting and analytics purposes.
Knowledge of data warehousing, ETL/ELT processes, data governance, and data quality management.
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