About The Opportunity
We are seeking a Senior AI/ML Developer to lead the technical development of an Industrial RAG (Retrieval-Augmented Generation) solution for a major US-based client. The project addresses a critical challenge: transitioning 25 years of historical lab reports from SharePoint into an intelligent, GenAI-powered knowledge retrieval system.
You will be responsible for building a two-phase solution, starting with a Proof of Concept (POC) for a Pricing Analyst Agent and evolving into a Production-Ready Conversational AI Agent. This role focuses on automating knowledge retrieval, preserving institutional expertise, and enhancing the accuracy of fluid design processes through scalable AWS architectures.
Responsibilities
* Develop and validate robust AI architectures leveraging AWS Infrastructure, specifically Amazon Bedrock and SageMaker.
* Create GenAI pipelines and multi-agent workflows using AWS Step Functions, Lambda, and EventBridge.
* Design platforms for processing massive volumes of unstructured data (text, image, audio, and video) integrated with RAG patterns.
* Build interactive front-ends and AI dashboards using Streamlit for demos and operational workflows.
* Implement best practices for AI governance, security, and observability using AWS IAM and CloudWatch.
* Fine-tune pricing normalization and data retrieval to reduce bid risk and improve decision accuracy.
Required Qualifications
* Good English communication skills (mandatory for direct collaboration with US stakeholders).
* Proven hands-on experience building real-world GenAI applications using commercial LLMs.
* Deep technical knowledge of the AWS ecosystem, including Serverless architectures and AI-specific services.
* Strong experience building intelligent pipelines and event-oriented architectures.
* Ability to design, test, and evaluate prompt engineering strategies and agentic frameworks.
* Experience handling complex, unstructured data sources at scale.
Nice to Have
* Experience with industrial-scale data migrations (SharePoint to Cloud).
* Background in data science, specifically related to pricing normalization or cost baselines.
* AWS Certified Machine Learning – Specialty or AWS Certified AI Practitioner certifications.