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senior automation engineer

ai platform application engineer

Nagarro

<div>Job Description 
Build and implement production-ready AI solutions including LLM pipelines, RAG systems, Conversational AI, and ML services on Azure. Ensure reliability, scalability, and continuous improvement across AI workloads.
Key Responsibilities:<ul><li>
Develop modular Python code for LLM, RAG, and ML components.</li><li>
Build APIs, orchestration scripts, and integration layers for enterprise apps.</li><li>
Implement RAG workflows, vector DB configurations, and prompt engineering.</li><li>
Deploy and monitor AI models using containerization and CI/CD pipelines.</li><li>
Collaborate with architects and product teams to refine designs and deliverables.</li></ul>
Must-Have Skills:<ul><li>
Data Science on Azure, Generative AI Fundamentals, Machine Learning Solution Design</li><li>
Python (Strong) and advanced RAG Workflow experience</li><li>
Hands-on with agentic GenAI components and ML pipelines</li></ul>
Arabic proficiency is a plus.</div>

AI Platform & Application Engineer

Sage Care

<div>
 
 
 Job Title: Partner Engineer &ndash; Health Tech AI (UAE)
 
 
 
 
 Location: Abu Dhabi, UAE
 
 
 
 
 
 
 
 About Us
 
 
 
 
 Sage Care
 
 &nbsp;is a fast-growing Series A healthcare technology startup founded by leaders from Apple, Uber, and Carbon Health. We recently emerged from stealth with $20 million in funding led by Yosemite, and investors including General Catalyst, Metrodora Ventures (co-founded by Chelsea Clinton),&nbsp;OVTR.VC, SV Angel, Liquid 2 Ventures, Seven Stars, Refract Ventures, AME Cloud Ventures, and Apolo Ohno.
 
 
 
 
 
 Our founding story and vision were recently profiled in&nbsp;
 
 
 Forbes
 
 
 , highlighting Sage Care&rsquo;s mission to build an &ldquo;air-traffic-control system for healthcare.&rdquo;
 
 
 
 
 
 With a strong customer pipeline, Sage Care is transforming healthcare by simplifying care navigation. Our platform makes it easier for patients to find the right doctor, helps providers focus on those who need them most, and ensures faster access to care. By harnessing clinically grounded AI and real-time optimization, we improve operational efficiency, increase system capacity, and deliver better patient outcomes at scale.
 
 
 
 
 
 
 Building on our successful collaborations with health systems across the U.S., we have expanded internationally to the MENA region. We are now partnering with health systems there to deploy our AI-powered care navigation platform.
 
 
 
 
 
 
 
 About the role
 
 
 
 We're seeking a passionate and skilled Partner Engineer to help health systems in the MENA region unlock the full potential of our AI-powered solutions for care navigation. In this role, you&rsquo;ll act as both a technical expert and a trusted partner&mdash;leading seamless implementations, ensuring long-term success, and building strong collaborations with our healthcare partners. Your work will directly shape how patients connect to care, empower providers, and redefine healthcare access at scale.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 Partner Integration &amp; Technical Support:
 
 
 <ul>
 <li>
 Act as the primary technical contact for our MENA based health system partners.
 </li>
 <li>
 Collaborate closely with partners to integrate our AI platform with their systems (EHRs, EMRs, etc.), ensuring smooth, secure, and efficient deployment.
 </li>
 <li>
 Troubleshoot and resolve technical issues promptly, ensuring the success of ongoing implementations.
 </li>
 </ul>
 
 
 Solution Design &amp; Customization:
 
 
 <ul>
 <li>
 Design and implement AI solutions tailored to partners&rsquo; unique clinical and business needs.
 </li>
 <li>
 Develop integration processes, workflows, and data mappings to ensure seamless adoption of our platform by partners.
 </li>
 <li>
 Provide guidance to partners on how to best use our AI tools to enhance their operational workflows.
 </li>
 </ul>
 
 
 Communication &amp; Problem-Solving:
 
 
 <ul>
 <li>
 Strong communication skills are critical in engaging with partners to uncover their pain points and translate them into clear, actionable solutions.
 </li>
 <li>
 Collaborate with partners to brainstorm and develop technical solutions to their challenges, ensuring alignment with their business goals and technical requirements.
 </li>
 </ul>
 
 
 Client-Facing and Technical Support:
 
 
 <ul>
 <li>
 Lead client interactions to understand their unique challenges, providing technical support and guidance throughout the implementation process.
 </li>
 <li>
 Ensure our technology integrates smoothly with clients' existing call-center infrastructure, optimizing system interoperability and enhancing efficiency.
 </li>
 </ul>
 
 
 Decision Trees, Annotation Workflows, and Integration:
 
 
 <ul>
 <li>
 Create decision trees and annotation workflows using internal tools, aligning them with partners' Standard Operating Procedures (SOPs).
 </li>
 <li>
 Ensure seamless integration of our solutions with customer technologies, ensuring interoperability with existing infrastructure.
 </li>
 </ul>
 
 
 Prototype Development &amp; Simulations:
 
 
 <ul>
 <li>
 Help build prototypes and run simulations once the technology is up to speed. Prototypes play an important role in winning customer relationships and showcasing the potential of our solutions.
 </li>
 </ul>
 
 
 Continuous Improvement:
 
 
 <ul>
 <li>
 Collect and analyze technical feedback from partners and monitor system performance.
 </li>
 <li>
 Recommend system enhancements and stay updated on industry trends and regulatory changes to ensure ongoing success.
 </li>
 </ul>
 
 
 Collaboration with Internal Teams:
 
 
 <ul>
 <li>
 Work closely with Product and Engineering teams to relay partner feedback, influencing product improvements and ensuring alignment with partner needs.
 </li>
 </ul>
 
 
 
 
 
 Qualifications:
 
 
 <ul>
 <li>
 Strong Communication Skills:&nbsp;Ability to ask insightful questions, engage with partners to understand their pain points, and translate those into actionable technical solutions.
 </li>
 <li>
 5+ years in a technical role (Engineering, Solutions Engineering, Partner Engineering, Integration Engineering, Technical Consulting, or similar). A transition to sales is a plus!
 </li>
 <li>
 Technical Background:&nbsp;Solid engineering experience with a deep understanding of integration, APIs, cloud technologies (AWS, Azure), and data mapping.
 </li>
 <li>
 Sales Acumen:&nbsp;Comfortable engaging with clients, understanding their needs, and translating technical requirements into effective solutions.
 </li>
 </ul>
 
 
 
 
 
 Nice to Have:
 
 
 <ul>
 <li>
 Healthcare Industry Knowledge:&nbsp;Familiarity with healthcare systems, clinical workflows, and regulatory standards (e.g., HIPAA).
 </li>
 <li>
 Call Center Logistics Background:&nbsp;Strong experience in call center logistics, including infrastructure, workflow optimization, system integrations, and familiarity with platforms such as RingCentral, Microsoft Teams, Cisco Finesse, Cisco Jabber, and Twilio.
 </li>
 <li>
 Experience building prototypes or running simulations
 </li>
 </ul>
</div>

Partner Engineer - Health Tech AI (UAE)

<div>Title:
Digitalization and Artificial Intelligence Engineer
Belong, Connect, Grow, with KBR!
The KBR team of teams delivers future-forward science, technology and engineering solutions and mission-critical services that help governments and companies around the world accomplish their most important objectives, while also helping achieve their sustainability goals.
KBR Sustainable Technology Solutions provides holistic and value-added solutions across the entire asset life cycle. These include world-class licensed process technologies, differentiated advisory services, deep technical domain expertise, energy transition solutions, high-end design and engineering capabilities, and smart solutions to optimize planned and operating assets.
We are urgently seeking a Digitalization and Artificial Intelligence Engineer to be based in Spain Location in the EPC contractor&rsquo;s office for an Offshore client.
Job Title: Digitalization and Artificial Intelligence Engineer
Location: Madrid, Spain 
Project: LZ LTDP-1 
Department: Engineering / Digital Transformation 
Reports To: Project Manager<div></div>
Job Description:
Review the Asset Design with respect to Digital and AI gaps. The engineering design review includes whole asset from Well downhole to facilities and to oil export. Digital and AI review shall include all domains from production to operations, maintenance, integrity, HSE, logistics etc. AI design review includes the review of instrumentation at assets, closed loops at process facilities, process optimization, edge computing, autonomous operations, predictive maintenance, automated data QC validation, robotics, drones, smart HSE protocols etc. Identify the AI use cases and provide recommendations to deploy AI enabled technologies at wellheads and facilities. Ensure the recommendations are implemented by Contractors and vendors. Lead the Digital and AI design thinking workshops and provide the recommendations Evaluation of AI technologies provided by OEMs and vendors. Evaluate the value realization from those technologies and ensure the compliance as per Autonomous operations requirements. Work with all business units within ADNOC to ensure the AI technologies add value to their day-to-day operations Liaise with Instrumentation and control OEMs to ensure the integration of new AI apps with existing systems Liaise with IT and OT teams to deploy the AI enabled technologies and their integration keeping compliance with Cybersecurity protocols.
Key Responsibilities:
Design &amp; Engineering<ul><li>
Develop and maintain the Digital and AI Design Philosophy and Design Basis in alignment with ADNOC standards.</li><li>
Prepare and issue digital design documentation including specifications, data sheets, and functional requirement catalogues.</li><li>
Identify and select appropriate digital and AI technologies for implementation.</li></ul>
Integration &amp; Implementation<ul><li>
Define and implement integration strategies with existing ADNOC systems such as Panorama.</li><li>
Ensure seamless integration of various digital solutions into a common user-friendly platform.</li><li>
Design plant facilities to accommodate selected digital and AI technologies.</li></ul>
Infrastructure &amp; Compliance<ul><li>
Identify required IT infrastructure and ensure compliance with:<ul><li>
Wireless Infrastructure (AGES-SP-12-003)</li><li>
Wireless Instrumentation System (AGES-SP-04-019)</li></ul></li><li>
Ensure cybersecurity compliance for autonomous operations with Cyber Security Design (CSD).</li></ul>
Execution &amp; Commissioning<ul><li>
Oversee procurement, installation, testing, and commissioning of digital and AI solutions.</li><li>
Prepare and manage detailed implementation schedules including PO placements, FAT/SAT, and site installation timelines.</li></ul>
Technology &amp; Innovation<ul><li>
Promote adoption of edge computing and autonomous operation programs.</li><li>
Interface with AIQ products, RoboWell (AWC), ESP, AR360, Machinery Lab, and Neuron Project.</li><li>
Integrate drones and robotics as part of the digitalization scope.</li></ul>
Guidelines &amp; Standards<ul><li>
Ensure adherence to ADNOC&rsquo;s AI P5 Guidelines and instrumentation standards:<ul><li>
Wells &amp; Surface Facilities Instrumentation</li><li>
Real-time Data Mapping</li><li>
Domain Data Requirements</li><li>
Collaborative Working Environment</li><li>
Change Management &amp; Communication</li><li>
Telecommunication Infrastructure</li></ul></li></ul><div></div>
Qualifications &amp; Experience:<ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Engineering, Computer Science, or related field.</li><li>
Minimum 8 years of experience in digitalization, AI integration, or smart plant technologies within oil &amp; gas or industrial sectors.</li><li>
Proven experience in EPC project environments and multi-disciplinary coordination.</li><li>
Strong knowledge of industrial automation, edge computing, and AI platforms.</li><li>
Familiarity with ADNOC systems and standards is highly desirable.</li></ul><div></div>
Skills &amp; Competencies:<ul><li>
Strong analytical and problem-solving skills.</li><li>
Excellent communication and documentation abilities.</li><li>
Project management and scheduling expertise.</li><li>
Ability to work collaboratively across disciplines and with subcontractors.</li><li>
Cybersecurity awareness and data governance understanding.</li></ul></div>

Digitalization and Artificial Intelligence Engineer

<div>Job Description 
We are seeking an AI Architecture Leader to design and govern enterprise-scale AI ecosystems for major UAE clients. This role combines technical leadership, solution design, and strategic advisory, focusing on Generative AI, agentic systems, and cloud-native engineering.
Key Responsibilities:<ul><li>
Define enterprise AI operating models, governance, and architectural standards.</li><li>
Lead multi-year AI transformation roadmaps and platform modernization.</li><li>
Architect end-to-end AI ecosystems: LLM agents, RAG workflows, multimodal AI, RLHF.</li><li>
Establish modular, reusable patterns for scalable and compliant AI platforms.</li><li>
Partner with business and tech leaders to shape AI strategy and value propositions.</li><li>
Conduct technical workshops, pre-sales reviews, and solution design sessions.</li></ul>
Must-Have Skills:<ul><li>
AI Application Solution Design (Strong)</li><li>
Cloud-Native GenAI Development (Strong)</li><li>
Data Science on Azure (Strong)</li><li>
Machine Learning Solution Design (Strong)</li><li>
Advanced RAG Workflow Design (Strong)</li><li>
Hands-on Python and experience with agentic GenAI systems.</li></ul>
Nice-to-Have:<ul><li>
Experience with Compass AI services.</li><li>
Arabic language proficiency (verbal &amp; written).</li></ul>
Join us to shape enterprise AI architecture and accelerate digital transformation across the UAE.</div>

Enterprise AI Architect

D4 Insight

<div>Position: Senior Cloud DevOps Engineer &ndash; Azure &amp; AI Solutions 
Location: Abu Dhabi
<h3 class="jobSectionHeader">
Role Overview</h3>

We are seeking a highly skilled Senior Cloud DevOps Engineer with strong expertise in Azure and AI platforms to design, deploy, and manage scalable cloud and MLOps solutions. This role will drive automation, governance, security, and end-to-end AI infrastructure delivery.
<h3 class="jobSectionHeader">
Key Responsibilities</h3>
<ul>
<li>Architect and deploy scalable AI and cloud platforms using Azure VMs, AKS, and Azure Functions
</li>
<li>Administer Azure Subscriptions and Resource Groups with strong governance using Azure Policy, Blueprints, and RBAC
</li>
<li>Automate infrastructure using Terraform through reusable modules, secure state management, and CI/CD integration
</li>
<li>Implement secure networking using Azure Firewall, VNets, NSGs, and Private Endpoints
</li>
<li>Monitor and optimize cloud resources using Azure Advisor, Cost Management, and AWS CloudWatch for hybrid setups
</li>
<li>Deploy and manage ML models using Azure Machine Learning, MLflow, and Azure ML Endpoints
</li>
<li>Build and operate robust MLOps pipelines using Azure DevOps, GitHub Actions, and Terraform
</li>
<li>Containerize and deploy models using AKS, ACI, and optionally Amazon SageMaker
</li>
<li>Track model performance and data drift using Azure Monitor, Application Insights, and Log Analytics
</li>
<li>Integrate Azure Cognitive Services, Azure OpenAI, and optionally AWS Rekognition or Comprehend
</li>
<li>Apply Generative AI engineering principles to build scalable and modular AI solutions
</li>
<li>Collaborate closely with AI, Data Science, UI/UX, and engineering teams for end-to-end delivery
</li>
<li>Create documentation standards and reusable templates for AI and infrastructure projects
</li>
<li>Apply DevOps best practices using Docker, CI/CD pipelines, and Infrastructure as Code
</li>
<li>Ensure compliance with enterprise policies, security standards, and service guidelines
</li>
</ul><h3 class="jobSectionHeader">Ideal Candidate Profile</h3>
<ul>
<li>5+ years of hands-on experience in Azure-based cloud and AI solution delivery
</li>
<li>Strong expertise in Terraform, including module development, remote state management, and CI/CD integration
</li>
<li>Proven experience in cloud infrastructure, MLOps, containerization, and DevOps automation
</li>
<li>Bachelor&rsquo;s degree in Computer Science, AI, Software Engineering, Statistics, or related field (Master&rsquo;s preferred)
</li>
<li>Azure certifications such as AZ-104, AZ-305, or DP-100 are a strong advantage
</li>
<li>Exposure to both Azure and AWS environments
</li>
<li>Strong skills in data preparation, feature engineering, and large-scale dataset handling
</li>
<li>Ability to convert technical insights into clear business value
</li>
<li>Experience working cross-functionally with engineering, product, and business teams
</li>
</ul> Interested candidates can share their resume at: [email protected]</div>

Senior Cloud DevOps Engineer – Azure & AI Solutions

Deeplight

<div>DeepLight AI is a specialist AI and data consultancy with extensive experience implementing intelligent enterprise systems across multiple industries, with particular depth in financial services and banking. Our team combines deep expertise in data science, statistical modeling, AI/ML technologies, workflow automation, and systems integration with a practical understanding of complex business operations.
The Project Lead drives the design, delivery, and operational rollout of an internal AI-powered text-to-SQL query platform that enables natural language access to enterprise data across multiple BI systems. This role sits at the intersection of LLM engineering, semantic data modeling, BI metadata management, and pragmatic delivery leadership.
The role leads a focused 5&ndash;7 person team to deliver a production-ready conversational query layer in a fast-paced window. This role requires an individual who thrives on execution, cuts through complexity, and knows how to ship working AI solutions quickly and safely.
Key Responsibilities of the role include:
AI &amp; Data Delivery<ul><li>
Lead end-to-end delivery of an internal conversational AI interface that converts natural language questions into SQL queries.</li><li>
Drive the evaluation and implementation of semantic model generation approaches (vendor-based and in-house custom development).</li><li>
Build and operationalize a query stack hosted inside the company&rsquo;s VPC.</li></ul>
Semantic Layer &amp; BI Integration<ul><li>
Design, refine, and implement a semantic layer that supports accurate text-to-SQL translation.</li><li>
Integrate the solution across existing BI platforms (MicroStrategy, Power BI, Tableau) without requiring tool migration.</li><li>
Ensure alignment with enterprise data governance and the company&rsquo;s &ldquo;Data for AI&rdquo; initiative.</li></ul>
Vendor &amp; Tooling Strategy<ul><li>
Assess capabilities of MicroStrategy&rsquo;s AI features, Microsoft Azure-native tools, and emerging startup solutions.</li><li>
Provide a balanced BI tooling recommendation based on operational needs and platform capabilities.</li><li>
Mitigate vendor lock-in by evaluating multiple options and architecting flexible solutions.</li></ul>
Cross-Functional Leadership<ul><li>
Work with domain SMEs in Finance and Retail to incorporate business context into the semantic layer.</li><li>
Collaborate with internal data, BI, and AI engineering teams.</li><li>
Provide clear, actionable updates to senior leadership with a bias toward rapid decision-making.</li></ul>
Requirements<ul><li>
7&ndash;12+ years in Data Engineering, ML Engineering, Data Architecture, or Applied AI.</li><li>
Hands-on experience with:</li><li><ul><li>
Text-to-SQL or NL-to-query systems</li></ul></li><li><ul><li>
Conversational AI (LLMs, prompt engineering, fine-tuning)</li></ul></li><li><ul><li>
Semantic modeling, MDM concepts, ontologies, or BI metadata layers</li></ul></li></ul><ul>
<li><ul><li>SQL and BI ecosystems (Power BI, Tableau, MicroStrategy)</li></ul></li>
<li><ul><li>Comfortable integrating LLMs with data warehouses, APIs, and enterprise cloud environments.</li></ul></li>
<li><ul><li>Demonstrated success delivering complex AI/data projects under compressed timelines.</li></ul></li>
<li><ul><li>Fast, pragmatic decision-maker who avoids analysis paralysis.</li></ul></li>
<li><ul><li>Strong cross-functional communication and stakeholder management skills.</li></ul></li>
<li><ul><li>Experience leading small, high-performance engineering teams.</li></ul></li>
</ul>
It would be great if you also have;<ul><li>
A background in Microsoft Azure ecosystem or Azure OpenAI.</li><li>
Previous exposure to Microsoft Fabric, dbt, semantic modeling tools, or metadata automation platforms.</li><li>
Previous experience building internal copilots or enterprise LLM applications.</li></ul>
Please note: This is a 6 month Fixed term contractually initially, with the potential to extend.
Benefits
Benefits &amp; Growth Opportunities:<ul><li>Competitive salary and performance bonuses</li><li>Comprehensive health insurance</li><li>Professional development and certification support</li><li>Opportunity to work on cutting-edge AI projects</li><li>Flexible working arrangements</li><li>Career advancement opportunities in a rapidly growing AI company</li></ul>
This position offers a unique opportunity to shape the future of AI implementation while working with a talented team of professionals at the forefront of technological innovation. The successful candidate will play a crucial role in driving our company's success in delivering transformative AI solutions to our clients.
At DeepLight AI, we recognise that diversity drives innovation. We are committed to fostering an inclusive environment where individuals with different thinking styles can thrive and contribute their unique strengths to our specialised AI and data solutions.
Our goal is to ensure our application and interview process is accessible, predictable, and fair for all candidates.
If you require any specific adjustments to the application process, or if you require any reasonable adjustments should you be successful in being processed to the interview stage, please do let us know. This information will be kept strictly confidential and will not impact hiring decisions.</div>

Project Lead (AI Text-to-SQL & Semantic Layer)

Deeplight AI

<div>
 DeepLight AI is a specialist AI and data consultancy with extensive experience implementing intelligent enterprise systems across multiple industries, with particular depth in financial services and banking. Our team combines deep expertise in data science, statistical modeling, AI/ML technologies, workflow automation, and systems integration with a practical understanding of complex business operations.
 
 
 The Data Engineer is responsible for designing, implementing, and optimising data pipelines and infrastructure to support our cutting-edge AI systems. The Data Engineer collaborates closely with our multidisciplinary team to ensure the efficient collection, storage, processing, and analysis of large-scale data, enabling us to unlock valuable insights and drive innovation across various domains.
 
 
 
 Responsibilities of the role:
 
 
 
 <ul>
 <li>
 Design, build, and optimise scalable data solutions, primarily utilising the Lakehouse architecture to unify data warehousing and data lake capabilities. Advise stakeholders on the strategic choice between Data Warehouse, Data Lake, and Lakehouse architectures based on specific business needs, cost, and latency requirements.
 </li>
 <li>
 Design, develop, and maintain scalable and reliable data pipelines to ingest, transform, and load diverse datasets from various sources, including structured and unstructured data, streaming data, and real-time feeds.
 </li>
 <li>
 Implement standards and tooling to ensure ACID properties, schema evolution, and high data quality within the Lakehouse environment. Implement robust data governance frameworks (security, privacy, integrity, compliance, auditing).
 </li>
 <li>
 Continuously optimize data storage, compute resources, and query performance across the data platform to reduce costs and improve latency for both BI and ML workloads, leveraging techniques such as indexing, partitioning, and parallel processing.
 </li>
 <li>
 Develop and maintain CI/CD pipelines to automate the entire machine learning lifecycle, from data validation and model training to deployment and infrastructure provisioning.
 </li>
 <li>
 Deploy, manage, and scale machine learning models into production environments, utilizing MLOps principles for reliable and repeatable operations.
 </li>
 <li>
 Establish and manage monitoring systems to track model performance metrics, detect data drift (changes in input data), and model decay (degradation in prediction accuracy).
 </li>
 <li>
 Ensure rigorous version control and tracking for all components: code, datasets, and trained model artifacts (using tools like MLflow or similar).
 </li>
 <li>
 Create comprehensive documentation, including technical specifications, data flow diagrams, and operational procedures, to facilitate understanding, collaboration, and knowledge sharing
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Proven practical experience in designing, building, and optimising solutions using Data Lakehouse architectures (e.g., Databricks, Delta Lake).
 </li>
 <li>
 Strong hands-on experience with managing data ingestion, schema enforcement, ACID properties, and utilizing big data technologies/frameworks like Spark and Kafka.
 </li>
 <li>
 Expertise in data modeling, ETL/ELT processes, and data warehousing concepts. Proficiency in SQL and scripting languages (e.g., Python, Scala).
 </li>
 <li>
 Demonstrated practical experience implementing MLOps pipelines for production systems. This includes a solid understanding and implementation experience with MLOps principles: automation, governance, and monitoring of ML models throughout the entire lifecycle.
 </li>
 <li>
 Experience with CI/CD tools, containerization/orchestration technologies (e.g., Docker, Kubernetes), model serving frameworks (e.g., TensorFlow Serving, Sagemaker), and experiment tracking (e.g., MLflow).
 </li>
 <li>
 Experience with production monitoring tools to detect data drift or model decay.
 </li>
 <li>
 Strong hands-on experience with major cloud platforms (e.g., AWS, Azure, GCP) and familiarity with DevOps practices.
 </li>
 <li>
 Excellent analytical, problem-solving, and communication skills, with the ability to translate complex technical concepts into clear and actionable insights.
 </li>
 <li>
 Proven ability to work effectively in a fast-paced, collaborative environment, with a passion for innovation and continuous learning
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 
 Benefits &amp; Growth Opportunities:
 
 
 
 <ul>
 <li>
 Competitive salary and performance bonuses
 </li>
 <li>
 Comprehensive health insurance
 </li>
 <li>
 Professional development and certification support
 </li>
 <li>
 Opportunity to work on cutting-edge AI projects
 </li>
 <li>
 Flexible working arrangements
 </li>
 <li>
 Career advancement opportunities in a rapidly growing AI company
 
 
 </li>
 </ul>
 This position offers a unique opportunity to shape the future of AI implementation while working with a talented team of professionals at the forefront of technological innovation. The successful candidate will play a crucial role in driving our company's success in delivering transformative AI solutions to our clients.
</div>

Data Engineer

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