Senior AI/ML Developer

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.