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ai engineering professional

Beyon

<div>
 
 
 Job objective
 
 
 
 Lead the implementation and scaling of AI-driven engineering tools, frameworks, and methodologies across the organisation. Drive adoption of AI-assisted development capabilities to improve productivity, software quality, and delivery velocity.
 
 
 
 
 
 
 Responsibilities
 
 
 
 Strategic:
 
 <ul>
 <li>
 Define the AI engineering enablement roadmap and ensure alignment with organisational digital strategy.
 </li>
 <li>
 Establish productivity and quality metrics to evaluate the impact of AI practices.
 </li>
 <li>
 Provide insights, recommendations, and ROI-driven justifications to senior leadership.
 </li>
 <li>
 Create enterprise-wide playbooks and guardrails for responsible and secure AI-assisted development.
 </li>
 <li>
 Guide long-term scaling strategy and integration of AI into standard engineering workflows.
 </li>
 </ul>
 
 Financial:
 
 <ul>
 <li>
 Define the financial impact of AI-assisted development through measurable productivity improvements and cost efficiencies.
 </li>
 <li>
 Conduct ROI analyses for pilots and scaled implementations.
 </li>
 <li>
 Ensure optimal utilisation of AI tooling investments and licensing.
 </li>
 <li>
 Support the business case for continued investment in AI tooling, training, and platform upgrades.
 </li>
 </ul>
 
 Operational:
 
 <ul>
 <li>
 Lead hands-on pilots with developer teams to evaluate and adopt AI-assisted coding, code review, testing, and quality assurance capabilities.
 </li>
 <li>
 Design and execute structured pilot plans with clear objectives, success criteria, and governance controls.
 </li>
 <li>
 Instrument engineering workflows to capture usage analytics, KPIs, and performance data.
 </li>
 <li>
 Create and maintain internal playbooks covering AI-assisted coding, test generation, refactoring, documentation, and quality automation.
 </li>
 <li>
 Curate reusable templates, examples, and engineering standards to support consistent adoption.
 </li>
 <li>
 Ensure seamless integration of AI capabilities with CI/CD pipelines, developer platforms, IDEs, DevOps toolchains, and security workflows.
 </li>
 <li>
 Collaborate with security, DevOps, and architecture teams to validate compliance, scalability, and performance.
 </li>
 <li>
 Troubleshoot technical issues and develop reference integrations.
 </li>
 <li>
 Execute rollout and onboarding plans following successful pilots, including adoption playbooks and enablement materials.
 </li>
 <li>
 Partner with training and documentation teams to support change enablement and developer upskilling.
 </li>
 </ul>
 
 People:
 
 <ul>
 <li>
 Ensure timely completion of PMR process
 </li>
 <li>
 Continuously share the knowledge and understanding of the technology industry and business trends
 </li>
 <li>
 Ensure active participation in employee engagement survey
 </li>
 <li>
 Mentor developers on effective use of AI tooling.
 </li>
 <li>
 Promote a culture of experimentation and continuous learning.
 </li>
 <li>
 Build partnerships with IT, DevOps, Security, and external vendors.
 </li>
 </ul>
 
 
 
 
 
 Required qualification &amp; experience
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Software Engineering, or related field.
 </li>
 <li>
 7&ndash;10 years of experience in software engineering, DevOps, or platform engineering.
 </li>
 <li>
 Experience with AI-assisted development tools.
 </li>
 <li>
 Familiarity with MLOps concepts.
 </li>
 <li>
 Strong coaching and technical enablement skills.
 </li>
 </ul>
</div>

AI Engineering Professional

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) - Banking

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

<div>
 
 
 Job Objective
 
 
 
 Drive organisation-wide adoption, engagement, and effective usage of AI-assisted development tools and practices. Enable developers through workshops, hands-on training, community building, and structured knowledge-sharing. Act as the bridge between engineering teams, platform owners, and AI tool providers to ensure continuous improvement and impactful utilisation of AI capabilities.
 
 
 
 
 
 
 Responsibilities
 
 
 
 Strategic
 
 <ul>
 <li>
 Drive organisation-wide adoption of AI engineering tools and practices through structured enablement.
 </li>
 <li>
 Shape and communicate a compelling narrative around the value and impact of AI-assisted development.
 </li>
 <li>
 Build and maintain a community of practice that strengthens internal capability and collaboration.
 </li>
 <li>
 Influence workflow optimisation and responsible AI use through best practices and education.
 </li>
 </ul>
 
 Financial
 
 <ul>
 <li>
 Support financial impact realisation by increasing usage and proficiency of AI tools across teams.
 </li>
 <li>
 Contribute to ROI assessments by collecting success stories, usage metrics, and improvement data.
 </li>
 <li>
 Reduce training and onboarding costs through reusable materials, knowledge bases, and scalable enablement assets.
 </li>
 </ul>
 
 Operational
 
 <ul>
 <li>
 Support onboarding of new teams during AI tooling expansion.
 </li>
 <li>
 Conduct workshops, instructor-led training, demos, and &ldquo;AI pair programming&rdquo; sessions with developers.
 </li>
 <li>
 Coordinate regular knowledge-sharing sessions, office hours, and drop-in support to assist developers with AI-assisted development.
 </li>
 <li>
 Build and maintain an internal community of practice focused on AI-assisted engineering.
 </li>
 <li>
 Produce educational materials, examples, coding templates, and video walkthroughs.
 </li>
 <li>
 Maintain, update, and expand the internal AI knowledge base and FAQ.
 </li>
 <li>
 Track participation, engagement, and effectiveness of training and enablement activities.
 </li>
 <li>
 Gather developer feedback, assess challenges, and document success stories.
 </li>
 <li>
 Identify recurring developer challenges and escalate insights and improvement opportunities to enablement leads and program management.
 </li>
 <li>
 Assist with evaluating new AI tools and features based on developer feedback.
 </li>
 <li>
 Collaborate with enablement, platform, and security teams to ensure training materials and guidance align with approved standards and policies.
 </li>
 </ul>
 
 People
 
 <ul>
 <li>
 Ensure timely completion of PMR process
 </li>
 <li>
 Continuously share the knowledge and understanding of the technology industry and business trends
 </li>
 <li>
 Ensure active participation in employee engagement survey
 </li>
 <li>
 Engage and support developers to encourage adoption of AI-enabled ways of working.
 </li>
 <li>
 Promote collaboration, knowledge sharing, and continuous learning across teams.
 </li>
 <li>
 Maintain positive relationships with stakeholders to support effective enablement and communication.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications and Experience
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Software Engineering, or equivalent.
 </li>
 <li>
 5&ndash;8 years of experience as a software engineer, developer relations specialist, or technical trainer.
 </li>
 <li>
 Strong storytelling, presentation, and communication skills.
 </li>
 <li>
 Practical hands-on experience using AI-assisted coding tools in real projects.
 </li>
 </ul>
</div>

AI Development Manager

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)

Jaikin

<div>
 
 
 Position type: Full-time | Permanent | Open to exceptional Freelance-to-Full-time paths
 
 
 
 
 
 
 We&rsquo;re looking for
 
 builders
 
 &mdash; engineers passionate about AI, automation, and intelligent systems &mdash; who want to design and deploy solutions that truly transform how companies operate.
 
 
 
 
 
 
 Your mission
 
 
 <ul>
 <li>
 Build advanced automation pipelines powered by AI/ML
 </li>
 <li>
 Design autonomous agents and intelligent workflows
 </li>
 <li>
 Improve and orchestrate complex processes through scripting &amp; engineering
 </li>
 <li>
 Work closely with product and business teams to detect high-value automation opportunities
 </li>
 </ul>
 
 
 
 
 
 You might be a great fit if you:
 
 
 <ul>
 <li>
 Have strong experience in software engineering (Python, JavaScript, or similar)
 </li>
 <li>
 Worked with AI frameworks (LangChain, OpenAI API, HuggingFace, RAG&hellip;)
 </li>
 <li>
 Built or deployed automation (n8n, Zapier, Airflow, custom orchestrators&hellip;)
 </li>
 <li>
 Love solving problems, thinking structurally, and shipping real-world systems
 </li>
 </ul>
 
 
 
 
 
 We also value:
 
 
 <ul>
 <li>
 Builders who have launched personal projects
 </li>
 <li>
 Freelancers with strong delivery track records
 </li>
 <li>
 Profiles coming from startups or innovation teams
 </li>
 <li>
 Engineers who learn fast rather than &ldquo;tick every box&rdquo;
 </li>
 </ul>
 
 
 
 
 
 What we offer
 
 
 <ul>
 <li>
 High-impact projects with real autonomy
 </li>
 <li>
 Work with international engineering talents
 </li>
 <li>
 Flexible work setup (remote / hybrid)
 </li>
 <li>
 Strong learning culture and fast progression
 </li>
 <li>
 Competitive compensation
 </li>
 </ul>
 
 
 
 
 If this sounds like you, send your CV, portfolio or GitHub to 📩
 
 victor@jaikin.eu
 
 
</div>

Software Engineer / AI Engineer – Automation Specialist

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

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