AI Integration Developer

Tech Bay IT Solutions; Manama; On-site; BHD 18,000 - 28,000; Full time

Job summary

Unknown company is seeking an AI Integration Specialist to lead deployment of ML models, pharmacogenomics predictions, chatbots, and vector search for a national genomic dataset.

Responsibilities include building and deploying ML models with TensorFlow, PyTorch, and Scikit-learn; implementing RAG architectures; designing cloud-native AI pipelines with AWS; and integrating with .NET/ASP.NET Core in healthcare/genomics contexts.

Qualifications

• Bachelor's degree in IT, CS, AI, or related field.
• Proficient with TensorFlow, PyTorch, Python, Scikit-learn.
• Experience with AWS SageMaker, Bedrock, NextFlow; vector DBs.
• Able to design RESTful APIs and microservices in .NET/ASP.NET Core.
• Healthcare/genomics data workflows preferred; strong communication.

Responsibilities

• Build, fine-tune, and deploy ML/DL models.
• Implement production-grade RAG architectures and vector databases.
• Architect cloud-native AI pipelines using AWS services.
• Design RESTful APIs and integrate with .NET/ASP.NET Core.
• Process large structured/unstructured healthcare and genomic datasets.

Skills

TensorFlow

PyTorch

Python

Scikit-learn

AWS SageMaker

AWS Bedrock

NextFlow

Vector DBs

RESTful APIs

ASP.NET Core

Microservices

SQL/NoSQL

Docker

MLOps

Healthcare Genomics

Education

Bachelor’s degree in Information Technology, Computer Science, Artificial Intelligence, or related field

Tools

Pinecone

FAISS

Weaviate

GPT

Claude

SageMaker

Bedrock

NextFlow

Lambda

S3

IAM

Docker

Job description

Hiring: AI Integration Specialist (Healthcare & Genomics / AWS / RAG / .NET)

Location: On-site Bahrain

Experience: Minimum 3years

Contract Duration: 2-Year Full-Time Contract

Candidate should be available locally in Bahrain

About the Role

We are looking for an experienced AI Integration Specialist to lead the deployment of machine learning models, Pharmacogenomics predictions, conversational chatbots, and vector search systems for a large-scale national genomic dataset.

Key Responsibilities

• Build, fine-tune, and deploy ML/DL models (Classification, Regression, Clustering) using TensorFlow, PyTorch, and Scikit-learn.
• Implement production-grade RAG architectures, vector databases (Pinecone, FAISS, Weaviate), and LLM integrations (GPT, Claude).
• Architect cloud-native AI pipelines utilizing AWS SageMaker, AWS NextFlow, AWS Bedrock, Lambda, S3, and IAM.
• Design RESTful APIs and integrate backend services within .NET/ASP.NET Core enterprise environments.
• Clean, normalize, and process large structured/unstructured healthcare and genomic datasets.

Requirements & Qualifications

• Education: Bachelor’s degree in information technology, Computer Science, Artificial Intelligence, or a related field
• Core Technologies: TensorFlow, PyTorch, Python, Scikit‑learn, AWS Ecosystem (SageMaker, Bedrock, NextFlow), Vector DBs.
• Integration Capabilities: ASP.NET Core, RESTful APIs, Microservices, SQL/NoSQL, Git, Docker, MLOps.
• Domain Knowledge: Experience with healthcare, genomics, or large-scale clinical dataset workflows is highly preferred.
• Strong communication skills to articulate AI solutions to both technical and non-technical stakeholders.