ai engineer

Confidential

<figure class="table"><table><tbody><tr><td>Job Description:&nbsp;<ul><li>Build, deploy, and operate production AI systems and services.</li><li>Design and implement RAG pipelines across structured and unstructured data.</li><li>Develop AI-powered chatbots and automation workflows.</li><li>Integrate AI solutions with internal platforms, external data sources, and client systems.</li><li>Assist in fine-tuning LLMs and optimizing model performance.</li><li>Design data ingestion pipelines, including document processing and web data extraction.</li><li>Monitor AI systems and continuously optimize performance, reliability, and cost.</li><li>Collaborate with engineering, product, and operations teams to translate business requirements into AI solutions.</li><li>Ensure all AI systems comply with security, privacy, and reliability standards.</li></ul>&nbsp;Educational, Skills, and Experience:&nbsp;<ul><li>Bachelor’s degree in computer science, Engineering, Artificial Intelligence, or a related field.</li><li>3–5 years of professional experience in AI/ML engineering or applied AI development.</li><li>Strong problem-solving and analytical abilities.</li><li>Ability to translate business requirements into scalable technical solutions.</li></ul>&nbsp;Technical Skills:&nbsp;<ul><li>Advanced Python development and API integration.</li><li>Experience working with Large Language Models (LLMs).</li><li>Design and implementation of Retrieval-Augmented Generation (RAG) systems.</li><li>Vector databases, embeddings, and search architectures.</li><li>AI model optimization, evaluation, and performance monitoring.</li><li>Data ingestion pipelines and document processing systems.</li><li>Familiarity with fine-tuning techniques and open-source LLMs.</li><li>Understanding of AI security, privacy, and cost optimization strategies.</li></ul>&nbsp;Additional Eligibility Qualifications&nbsp;<ul><li>Ability to work independently and as part of a team.</li><li>Strong organizational and time management skills.</li><li>Willingness to continuously learn and adapt.</li><li>Ability to handle multiple projects in a fast-paced environment.</li><li>Strong sense of responsibility and ownership of deliverables.</li></ul></td></tr></tbody></table></figure>

AI Engineer

Penny Software

Join Our Team as an Intern - (Software Engineer &amp; AI Engineer) at Penny Software! Are you passionate about technology and eager to kickstart your career?This is your chance to be a part of an innovative team driving impactful projects!Overview of the Role: - Collaborate with experienced developers on exciting projects- Gain hands-on experience in software development and problem-solving- Contribute fresh ideas to enhance our technological solutionsIf you're ready to take your career to the next level and be part of an exciting journey, apply today! Let's build the future together.Apply here: https://lnkd.in/dTTuEkMiJob Types: Full-time, Internship Contract length: 3 months

Internship - (Software Engineer & AI Engineer)

VAM SYSTEMS

<div>Job Description 
VAM Systems is currently looking for AI/ML Specialists (Data Scientists/ ML Engineer) (On-Site) for our Bahrain operations with the following skillsets and terms &amp; conditions:
Years of Experience: 7 &ndash; 10 years
Qualification
Bachelor&rsquo;s Degree in Computer Science / Engineering 
Preferably BE Computer Science &amp; Engineering
Professional Training Required: Machine Learning, Deep Learning, MLOps, AI in Financial Services. 
Professional Qualification Required: Google Professional ML Engineer, Microsoft AI Engineer Associate Professional Licenses Required Not applicable. 
Professional Certifications Required: TensorFlow Developer Certificate, AWS Certified Machine Learning.
Must-Have:<ul><li>Proven hands-on delivery experience in banking, financial institutions, or insurance within Gen AI solutions such as chatbots, document analysis, etc., leveraging RAG and robust architecture with proper governance and security measures</li><li>Several years of ML experience with implemented use cases.</li><li>Hands-on work experience most of which in banking, financial institutions, or insurance industries.</li></ul>
Experience required:
Ability to build and deploy ML models using Python and relevant libraries. Understanding of supervised and unsupervised learning algorithms. 
Experience with model evaluation and performance metrics.
Familiarity with AI use cases in banking (e.g., fraud detection, personalization) Knowledge of data preprocessing and feature engineering. 
Ability to work with cloud-based ML platforms (e.g., Azure ML, AWS SageMaker). Understanding of MLOps and model lifecycle management. 
Ability to communicate insights and build explainable AI models. 
Joining time frame: (15 - 30 days)</div>

AI/ML Specialists (Data Scientists/ ML Engineer)

<div>Job Description 
VAM Systems is currently looking for Data Scientists - Banking for our Bahrain operations with the following skillsets and terms &amp; conditions:
Years of Experience: 7 &ndash; 10 years
Qualification
Bachelor&rsquo;s Degree in Computer Science / Engineering 
Preferably BE Computer Science &amp; Engineering
Professional Training Required: Machine Learning, Deep Learning, MLOps, AI in Financial Services. 
Professional Qualification Required: Google Professional ML Engineer, Microsoft AI Engineer Associate Professional Licenses Required Not applicable. 
Professional Certifications Required: TensorFlow Developer Certificate, AWS Certified Machine Learning.
Must-Have:<ul><li>Proven hands-on delivery experience in banking, financial institutions, or insurance within Gen AI solutions such as chatbots, document analysis, etc., leveraging RAG and robust architecture with proper governance and security measures</li><li>Several years of ML experience with implemented use cases.</li><li>Hands-on work experience most of which in banking, financial institutions, or insurance industries.</li></ul>
Experience required:
Ability to build and deploy ML models using Python and relevant libraries. Understanding of supervised and unsupervised learning algorithms. 
Experience with model evaluation and performance metrics.
Familiarity with AI use cases in banking (e.g., fraud detection, personalization) Knowledge of data preprocessing and feature engineering. 
Ability to work with cloud-based ML platforms (e.g., Azure ML, AWS SageMaker). Understanding of MLOps and model lifecycle management. 
Ability to communicate insights and build explainable AI models. 
 
 
Core AI / NLP Engineering<ul><li>Python (PyTorch, TensorFlow, LangChain, Hugging Face, OpenAI API, Anthropic Claude, etc.)</li><li>LLM fine-tuning (LoRA, PEFT, prompt tuning)</li><li>Retrieval-Augmented Generation (RAG), vector databases (Pinecone, FAISS, Weaviate, Chroma)</li><li>Prompt engineering and orchestration (LangChain, LlamaIndex, Semantic Kernel, DSPy)</li><li>Knowledge of embeddings, tokenization, and transformer architecture</li><li>Cloud AI tools: AWS Bedrock, Azure OpenAI, Vertex AI, OpenSearch, ElasticSearch</li><li>Model evaluation: hallucination detection, grounding, and benchmarking (BLEU, ROUGE, TruthfulQA, etc.)</li></ul>
 
Software Engineering &amp; Backend Integration<ul><li>RESTful and GraphQL APIs, webhooks</li><li>Containerization and deployment (Docker, Kubernetes, CI/CD)</li><li>Authentication and user/session management</li><li>Data pipelines and microservices</li><li>Knowledge of frameworks like FastAPI, Flask, NestJS, or Express</li><li>Integration with enterprise data (SharePoint, Salesforce, SQL, internal APIs)</li></ul>
Agent Orchestration &amp; Tooling
<ul><li>LangGraph, AutoGen, CrewAI, Flowise, or similar agent frameworks</li><li>Task-decomposition and reasoning chains</li><li>Function calling, tool use, and API chaining</li><li>Memory design (short-term vs long-term)</li><li>Context management and grounding strategies.</li></ul>
Joining time frame: (15 - 30 days)</div>

Data Scientists - Banking

TAT IT Technolgies

<div>
 
 Urgent requirement for Data Scientist (
 
 
 Core AI / NLP Engineering) is required for our client in Bahrain
 
 
 
 
 Design and develop machine learning models to support AI-driven banking solutions is MUST
 
 
 
 
 Python (PyTorch, TensorFlow, LangChain, Hugging Face, OpenAI API, Anthropic Claude, etc.) is MUST
 
 
 
 
 LangGraph, AutoGen, CrewAI, Flowise, or similar agent frameworks is MUST
 
 
 
 
 Prompt engineering and orchestration (LangChain, LlamaIndex, Semantic Kernel, DSPy) is MUST
 
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design and develop machine learning models to support AI-driven banking solutions
 </li>
 <li>
 Collaborate with data engineers to access and prepare data for modeling
 </li>
 <li>
 Apply statistical and ML techniques to solve business problems (e.g., churn prediction, credit
 </li>
 <li>
 scoring)
 </li>
 <li>
 Evaluate model performance and optimize for accuracy, precision, and recall
 </li>
 <li>
 Deploy models into production using MLOps frameworks and CI/CD pipelines
 </li>
 <li>
 Ensure models are explainable, auditable, and compliant with regulatory standards
 </li>
 <li>
 Work with business stakeholders to identify AI opportunities and define success metrics
 </li>
 <li>
 Document model assumptions, data sources, and performance benchmarks
 
 
 </li>
 </ul>
 Core AI / NLP Engineering
 
 
 <ul>
 <li>
 Python (PyTorch, TensorFlow, LangChain, Hugging Face, OpenAI API, Anthropic Claude, etc.)
 </li>
 <li>
 LLM fine-tuning (LoRA, PEFT, prompt tuning)
 </li>
 <li>
 Retrieval-Augmented Generation (RAG), vector databases (Pinecone, FAISS, Weaviate, Chroma)
 </li>
 <li>
 Prompt engineering and orchestration (LangChain, LlamaIndex, Semantic Kernel, DSPy)
 </li>
 <li>
 Knowledge of embeddings, tokenization, and transformer architecture
 </li>
 <li>
 Cloud AI tools: AWS Bedrock, Azure OpenAI, Vertex AI, OpenSearch, ElasticSearch
 </li>
 <li>
 Model evaluation: hallucination detection, grounding, and benchmarking (BLEU, ROUGE, TruthfulQA, etc.)
 
 
 </li>
 </ul>
 Software Engineering &amp; Backend Integration
 
 
 <ul>
 <li>
 RESTful and GraphQL APIs, webhooks
 </li>
 <li>
 Containerization and deployment (Docker, Kubernetes, CI/CD)
 </li>
 <li>
 Authentication and user/session management
 </li>
 <li>
 Data pipelines and microservices
 </li>
 <li>
 Knowledge of frameworks like FastAPI, Flask, NestJS, or Express
 </li>
 <li>
 Integration with enterprise data (SharePoint, Salesforce, SQL, internal APIs)
 
 
 </li>
 </ul>
 Agent Orchestration &amp; Tooling
 
 
 <ul>
 <li>
 LangGraph, AutoGen, CrewAI, Flowise, or similar agent frameworks
 </li>
 <li>
 Task-decomposition and reasoning chains
 </li>
 <li>
 Function calling, tool use, and API chaining
 </li>
 <li>
 Memory design (short-term vs long-term)
 </li>
 <li>
 Context management and grounding strategies
 
 
 </li>
 </ul>
 Conversational UX / Design
 
 
 <ul>
 <li>
 Conversation design frameworks (Google CCAI, Microsoft Bot Framework, Voiceflow, Botpress)
 </li>
 <li>
 Flow design and intent management (Dialogflow, Rasa, Cognigy)
 </li>
 <li>
 Tone, empathy, and personality design for AI personas
 </li>
 <li>
 A/B testing dialogue variants and measuring user satisfaction
 
 
 </li>
 </ul>
 Data &amp; Infrastructure
 
 
 <ul>
 <li>
 Data pipelines (Airflow, dbt, Kafka)
 </li>
 <li>
 Structured/unstructured data ingestion (PDFs, databases, APIs)
 </li>
 <li>
 Feature store and model registry management (MLflow, Kubeflow)
 </li>
 <li>
 Vector database deployment and optimization
 </li>
 <li>
 Monitoring, logging, and drift detection
 
 
 </li>
 </ul>
 Governance, Security &amp; Compliance
 
 
 <ul>
 <li>
 Model explainability (SHAP, LIME)
 </li>
 <li>
 Bias/fairness audits and data privacy
 </li>
 <li>
 Compliance with GDPR, ISO 42001, NIST AI RMF, and local banking regulations
 </li>
 <li>
 Secure prompt logging and audit trails
 
 
 </li>
 </ul>
 Products &amp; Strategy
 
 
 <ul>
 <li>
 Translating business problems into AI use cases
 </li>
 <li>
 Roadmapping and budget planning
 </li>
 <li>
 KPI design (accuracy, user satisfaction, automation ROI)
 </li>
 <li>
 Vendor management (OpenAI, Anthropic, AWS, etc.)
 </li>
 <li>
 Change management and user adoption
 
 
 </li>
 </ul>
 Skills: ai,design,nlp,data
</div>

Data Scientist (Core AI / NLP Engineering)

nineDots.io

<div>
 
 
 Full-Stack Engineer (Performance and Service Monitoring)
 
 
 
 Real-Time Systems - Reliability Engineering - AI Platform
 
 
 
 
 
 
 
 Join a fast-growing AI company helping global enterprises accelerate the adoption of applied AI. You will design and develop monitoring and performance systems that keep a high-usage platform stable, fast, and secure across demanding environments.
 
 
 
 
 
 
 
 
 The Role
 
 
 
 As a Full-Stack Engineer focused on performance and service monitoring, you will design, build, and evolve the systems that ensure uptime, reliability, and real-time responsiveness across the platform. You will work across engineering, product, and compliance to improve observability, build dashboards, and maintain high availability.
 
 
 
 
 
 
 
 This is a hands-on engineering role that blends full-stack development with real-time monitoring, performance optimisation, and reliable system behaviour.
 
 
 
 
 
 
 
 
 What You Will Be Doing
 
 
 <ul>
 <li>
 Designing and implementing performance monitoring systems across the platform.
 </li>
 <li>
 Building dashboards, alerting pipelines, and observability tooling.
 </li>
 <li>
 Developing performant frontend features using Next.js and React.
 </li>
 <li>
 Creating backend APIs and microservices using Node.js and Python.
 </li>
 <li>
 Implementing WebSocket and event-driven architectures for real-time data flow.
 </li>
 <li>
 Ensuring monitoring systems align with SOC 2, ISO 27001, and ISO 27018.
 </li>
 <li>
 Integrating notifications into tools like Slack and Microsoft Teams.
 </li>
 <li>
 Continuously improving system reliability, latency, and uptime.
 </li>
 </ul>
 
 
 
 
 
 
 
 What You Need To Succeed
 
 
 <ul>
 <li>
 Strong experience in full-stack engineering.
 </li>
 <li>
 Proficiency with Next.js, React, Node.js, and Python.
 </li>
 <li>
 Experience with monitoring, observability, or real-time systems.
 </li>
 <li>
 Familiarity with CloudWatch, Prometheus, Grafana, or similar stacks.
 </li>
 <li>
 Experience with WebSockets and event-driven architectures.
 </li>
 <li>
 Strong understanding of secure coding and compliance alignment.
 </li>
 <li>
 Comfortable working across cloud environments and CI/CD pipelines.
 </li>
 <li>
 Strong problem-solving skills with a focus on reliability and performance.
 </li>
 </ul>
 
 
 
 
 
 
 
 What&rsquo;s In It For You
 
 
 <ul>
 <li>
 Ownership of critical monitoring and reliability systems across a global AI platform.
 </li>
 <li>
 Modern tooling and real-time engineering challenges.
 </li>
 <li>
 Competitive salary and flexible work setup.
 </li>
 <li>
 Work with a fast-growing AI company supporting major enterprises.
 </li>
 <li>
 Equity potential and an environment that values technical excellence.
 </li>
 </ul>
 
 
 
 
 
 
 
 Next Steps
 
 
 
 If this role matches the type of engineering challenges you want to work on, we would like to hear from you. Send your CV or reach out in confidence for more details.
 
</div>

Full-Stack Engineer (Performance and Service Monitoring)

JPMorganChase

<div>
 
 Job Description
 
 
 
 Kick-start your software engineering career as an entry-level Software Engineer I. Be part of a team that is pushing the boundaries of what's possible.
 
 
 As a Software Engineer I at JPMorganChase within the Commercial and Investment Bank for Trade Finance business, you will be a part of an agile team that works to enhance, design, and deliver the software components to the firm&rsquo;s state-of-the-art technology products in a secure, stable, and scalable way. As an entry-level member of a software engineering team, you execute basic software solutions through the design, development, and troubleshooting of a single technical area within a business function, while gaining skills and experience to grow within your role.
 
 
 
 Job Responsibilities
 
 
 
 <ul>
 <li>
 Design, develop, and maintain microservices using Java and Spring Boot.
 </li>
 <li>
 Develop and maintain user interfaces using React, ensuring responsive and intuitive design.
 </li>
 <li>
 Implement cloud-native and cloud-hybrid solutions on Kubernetes container orchestration technology.
 </li>
 <li>
 Leverage AI-powered development tools such as GitHub Copilot or similar to enhance productivity, code quality, and accelerate development cycles.
 </li>
 <li>
 Collaborate with cross-functional teams to define, design, and ship new features in an agile environment.
 </li>
 <li>
 Utilize domain-driven design principles to architect scalable and maintainable systems and develop event-driven architectures to enhance system responsiveness and scalability.
 </li>
 <li>
 Work with SQL databases (e.g., Postgres) and NoSQL databases (e.g., MongoDB) to manage data effectively.
 
 
 </li>
 </ul>
 
 Required Qualifications, Capabilities, And Skills
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Engineering, or a related field with 1+ year of experience
 </li>
 <li>
 Experience in software development, with a focus on microservices architecture.
 </li>
 <li>
 Proficiency in Java and Spring Boot.
 </li>
 <li>
 Use AI-powered development tools such as GitHub Copilot.
 </li>
 <li>
 Stay informed about advancements in AI-assisted software engineering and proactively adopt best practices for AI-driven development.
 </li>
 <li>
 Hands-on experience in Microservices, RESTful Web services development in Java (Spring Boot), Spring Data JPA.
 </li>
 <li>
 Proficient in UTCs, Mutation testing, and API automation testing strategies.
 </li>
 <li>
 Experience with working with cloud platforms and strong understanding of domain-driven design and event-driven architecture.
 
 
 </li>
 </ul>
 
 Preferred Qualifications, Capabilities, And Skills
 
 
 
 <ul>
 <li>
 Experience with CI/CD pipelines and DevOps practices.
 </li>
 <li>
 Knowledge of containerization technologies like Docker.
 </li>
 <li>
 Familiarity with RESTful APIs and web services.
 </li>
 <li>
 Familiarity with prompt engineering and best practices for interacting with generative AI tools.
 </li>
 <li>
 Basic to intermediate proficiency in React for building and maintaining web user interfaces.
 
 
 </li>
 </ul>
 
 ABOUT US
 
 
 
 J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world&rsquo;s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
 
 
 We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants&rsquo; and employees&rsquo; religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
 
 
 
 About The Team
 
 
 
 J.P. Morgan&rsquo;s Commercial &amp; Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial &amp; Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.
</div>

Software Engineer I

Explore 69+ Ai engineer in Bahrain this January. Find roles across top companies and apply now to boost your career.