ai data engineer

MultiBank Group

<div>Welcome to MultiBank Group, a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.
Join our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US $35 billion. As a heavily regulated institution with oversight from 17+ financial regulators across 5 continents, and recipient of over 70 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.
Role Overview
We are seeking an experienced AI Data Engineer to design, develop, and deploy innovative data and machine learning solutions that drive customer engagement, retention, and lifetime value (LTV). This role will focus on building scalable data pipelines, predictive models, and GenAI-powered applications that enable more personalised trading experiences and support data-driven decision-making across the business.
Key Responsibilities<ul><li>
Collaborate with the wider marketing department to build meaningful datasets and a centralised data warehouse that will be used for reporting across numerous teams, focused on customer retention and LTV.</li><li>
Develop and own machine learning solutions that specialise in customer personalisation to increase engagement and coordinate with marketing teams towards their strategy and execution across multiple channels, especially around predictive modelling, churn prediction and customer segmentation.</li><li>
Explore the capabilities of Gen AI to develop new apps for our traders that make trading easier and more personalised based on their preferences.</li><li>
Maintain a commercial acumen and find opportunities where technology can be used to increase customer engagement or automate internal tasks.</li></ul>
Qualifications &amp; Requirements<ul><li>
Strong expertise in SQL, comfortable with raw data and multiple high-volume datasets such as customer journey, marketing performance or product behaviour.</li><li>
Comfortable creating pipelines and automations with Python to connect multiple endpoints and APIs such as first party databases, marketing platforms or other data collection platforms.</li><li>
Expertise in using Python todeploy machine learning solutions end to end, especially around predictive modelling and customer segmentation.</li><li>
Previous experience in finding customer insights through data analysis, communicating it to different stakeholders and strategizing on how to increase customer engagement and LTV.</li><li>
Capable of creating applications using LLMs that summarise high volumes of data and knowledge of the latest Gen AI use cases.</li><li>
Previous exposure to ETL tools (e.g., dbt, AWS Glue) and cloud environments (preferably AWS, SageMaker).</li><li>
Strong communication skills with the ability to present complex data insights to non-technical stakeholders and support business strategy.</li></ul>
Why Join Us?<ul><li>
Work with an industry-leading global financial institution.</li><li>
Competitive salary and comprehensive employee benefits.</li><li>
Opportunities for professional growth and career advancement.</li><li>
Collaborative, inclusive, and dynamic work environment.</li><li>
Commitment to innovation and professional excellence.</li></ul>
Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.
MultiBank Group combines prime liquidity, cutting-edge technology, and first-class service to deliver advanced trading platforms to clients worldwide.
Our mission is to provide exceptional products and services to our clients &mdash; and we continue to invest heavily in technology and regulation to benefit our customers and the financial industry as a whole.
As the most heavily regulated financial derivatives group, MultiBank Group maintains an unblemished regulatory record with all its regulators.
Positions available across our 25+ global offices &mdash; Dubai, Hong Kong, Singapore, London, Sydney, and more. Learn more: www.multibankgroup.com
MultiBank Group is an equal opportunity employer committed to diversity and inclusion. By submitting your application, you agree that your personal data will be processed in accordance with our Privacy Policy.</div>

AI Data Engineer

Honeywell

<div>As a Sr Data Engineer here at Honeywell, you will play a crucial role in designing and implementing advanced data solutions for AI solutions that drive business insights, enhance decision-making processes and empower AI solutions. Your expertise will help in critical data science development activities across all AI modalities (classic, Gen and agentic) and data types (structured and unstructured). 
 
You will report directly to our AI Director and you&rsquo;ll work out of our Phoenix, AZ or Charlotte, NC location on a Hybrid work schedule. 
In this role, you will impact the organization by leveraging your technical skills to develop innovative data solutions that support strategic initiatives and improve operational efficiency. 
KEY RESPONSIBILITIES
<ul><li>Support end‑to‑end data needs for all AI modalities , including classic ML, GenAI/LLMs, and agentic AI systems.
</li><li>Build robust, scalable data pipelines for structured, semi‑structured, and unstructured data , including text, documents, images, audio, video, and logs.
</li><li>Develop feature engineering pipelines for classic ML, including feature extraction, transformation, and feature store management.
</li><li>Build and optimize GenAI and LLM data pipelines , including embedding generation, vectorization, chunking, metadata extraction, and document enrichment for RAG and context retrieval.
</li><li>Develop data ingestion and orchestration workflows that support agentic AI , including memory stores, event-driven pipelines, tool-use data flows, and real-time retrieval services.
</li><li>Design and implement advanced data solutions using AWS (S3, Glue, Lambda, EMR, Kinesis), Databricks (Spark, Delta Lake, Vector Search), and Dataiku to enable intelligent systems at scale.
</li><li>Implement data governance, quality, lineage, monitoring, and observability to support high-performance, trustworthy AI.
</li><li>Partner with data scientists, ML engineers, and AI product teams to deliver datasets for model development, fine‑tuning, evaluation, and production inference.
</li><li>Optimize pipelines for latency, cost, reliability, and throughput, ensuring AI systems&mdash;from batch ML to real-time agents&mdash;have the data they need.</li></ul></div>

Sr AI Data Engineer

<div>As a Principal Data Engineer here at Honeywell, you will play a crucial role in designing and implementing advanced data solutions for AI solutions that drive business insights, enhance decision-making processes and empower AI solutions. Your expertise will help in critical data science development activities across all AI modalities (classic, Gen and agentic) and data types (structured and unstructured).
You will report directly to our AI Director and you&rsquo;ll work out of our Phoenix, AZ location on a Hybrid work schedule.
In this role, you will impact the organization by leveraging your technical skills to develop innovative data solutions that support strategic initiatives and improve operational efficiency.
At Honeywell, our people leaders play a critical role in developing and supporting our employees to help them perform at their best and drive change across the company. Help to build a strong, diverse team by recruiting talent, identifying and developing successors, driving retention and engagement, and fostering an inclusive culture.</div>

Principal AI Data Engineer

TechLabs London

<div>
 
 About TechLabs London:
 
 
 
 At TechLabs London, we build cutting-edge digital products that power smarter, more connected organizations. Our flagship solution is transforming housing management with modern cloud technology, intuitive design, and seamless integration. We are now embedding
 
 AI and intelligent automation
 
 across our platforms &mdash; and this role is at the center of that mission. We&rsquo;re looking for a driven and creative
 
 AI Engineer
 
 to lead this charge with us, to deliver production-ready AI features, predictive analytics, and computer vision tools that unlock real business value.
 
 
 
 Job Purpose:
 
 As an AI Engineer you&rsquo;ll be responsible for the development, deployment, and optimisation of advanced AI and ML capabilities within TechLabs London. You will collaborate with cross-functional teams to embed intelligent solutions into our existing product suite and shape the next generation of AI-powered features across our platforms. This role is perfect for someone who&rsquo;s passionate about building practical AI solutions and wants to see their work improve lives, save time, and power decisions. You&rsquo;ll help the business translate complex challenges into intelligent, scalable solutions.
 
 
 
 Responsibilities:
 
 
 
 <ul>
 <li>
 Design and build end-to-end AI pipelines across use cases such as predictive modelling, NLP, computer vision, and conversational AI.
 </li>
 <li>
 Design, develop and deploy conversational AI solutions using LLMs and agentic frameworks (e.g. LangChain, LangGraph), including RAG pipelines, intent classification, entity extraction, and multi-turn dialogue management.
 </li>
 <li>
 Apply computer vision to extract intelligence from images and videos for detection, classification, and automation.
 </li>
 <li>
 Develop time-series models that analyze behavior and generate predictive.
 </li>
 <li>
 Experiment with foundational models and fine-tune them for specific tasks relevant to our domain.
 </li>
 <li>
 Integrate models into production by working with our developers to deploy solutions into our products and beyond.
 </li>
 <li>
 Architect and build scalable, secure, and reusable ML APIs, workflows, and pipelines using modern MLOps practices and containerisation (Docker).
 </li>
 <li>
 Translate business problems into data-driven solutions, working closely with product, customer success, and engineering teams.
 </li>
 <li>
 Champion AI-first thinking across the company, supporting POCs, internal tooling, and customer-facing features.
 </li>
 <li>
 Collaborate with internal developers, product managers, domain experts, and external stakeholders to ensure solutions are feasible, maintainable, and impactful, as well as to define data strategies and model objectives.
 </li>
 <li>
 Conduct rigorous A/B testing and model evaluation.
 </li>
 <li>
 Support the integration of models into production systems using APIs and microservices.
 </li>
 <li>
 Stay abreast of advancements in AI/ML research and apply relevant breakthroughs to ongoing projects.
 
 
 
 </li>
 </ul>
 
 Skills and Experience:
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in information technology, Software Engineering, Computer Science, or related field.
 </li>
 <li>
 Proven experience building and deploying LLM-powered applications, including RAG pipelines and conversational agents.
 </li>
 <li>
 Hands-on experience with LangChain or similar agentic frameworks (LangGraph, AutoGen, or equivalent).
 </li>
 <li>
 Strong proficiency in Python and relevant ML libraries (e.g. pandas, scikit-learn, PyTorch, spaCy, Hugging Face, OpenCV etc.)
 </li>
 <li>
 Experience with cloud platforms &mdash; Azure is our primary platform (preferred); AWS or GCP also considered.
 </li>
 <li>
 Containerization and orchestration: Docker, Docker Compose.
 </li>
 <li>
 Solid understanding of data modelling, feature engineering, and data warehousing concepts.
 </li>
 <li>
 Strong knowledge of SQL and experience with relational and/or vector databases (e.g. pgvector, Pinecone, Weaviate).
 </li>
 <li>
 Proficiency in version control, CI/CD, and model deployment practices.
 </li>
 <li>
 Experience integrating AI models into web or mobile applications is highly valued.
 </li>
 <li>
 Experience with MLOps tools like MLflow, Airflow, DVC.
 </li>
 <li>
 Familiarity with MCP Server (Model Context Protocol) for building tool-augmented AI agents is a plus.
 
 
 
 </li>
 </ul>
 
 Mindset &amp; Soft Skills:
 
 
 
 <ul>
 <li>
 Strong problem-solving and analytical thinking &mdash; able to translate messy real-world data into measurable solutions.
 </li>
 <li>
 Pragmatic and delivery-oriented &mdash; capable of balancing technical innovation with business impact.
 </li>
 <li>
 Communicative and collaborative &mdash; comfortable working across teams and disciplines.
 </li>
 <li>
 Self-driven &mdash; able to manage time, priorities, and project ownership in a fast-moving team.
 </li>
 <li>
 Knowledge of data governance, bias mitigation, and explainable AI techniques.
 </li>
 </ul>
</div>

AI& Data Engineer (Hybrid)

Talent 360

<div>Wind Integrated Solutions, Oracle Partner in Egypt, KSA &amp; UAE is looking for &quot;AI &amp; Data Engineer&quot; with a strong foundation in data manipulation, machine learning, and natural language processing (NLP).
Wind Integrated Solutions is Software Development Company that provides technology services, business automation, and business digitalization.
Job Description:<ul><li>Lead technical discovery and data maturity assessments with enterprise customers across Saudi Arabia and Egypt</li><li>Design and present data platform architectures using modern tools (Microsoft Fabric, Azure Data Services, OpenMetadata, SQLMesh)</li><li>Create compelling business cases that connect data governance and AI capabilities to measurable business outcomes</li><li>Develop technical proposals, solution architectures, and pricing models for data and AI engagements</li><li>Deliver demonstrations of AI agent workflows, agentic automation, and conversational data access patterns</li><li>Support Microsoft co-sell motions for Azure AI, Microsoft Fabric, and Copilot-related opportunities</li><li>Collaborate with the Product Developer to align presales demonstrations with current product capabilities</li><li>Contribute to thought leadership content: whitepapers, case studies, and technical blog posts</li><li>Track competitive landscape across data governance and AI platforms (Informatica, Collibra, Databricks, Coalesce)</li></ul> 
 
 
Requirements<ul><li> 
BSc in Computer Science, Engineering or relevant field.</li><li>3-5 years of hands-on experience in data engineering, data architecture, or AI/ML presales.</li><li>Understanding of modern data stack: data warehouses, data lakes, ETL/ELT pipelines, data governance</li><li>Familier with data services (Azure Data Factory, Synapse, Microsoft Fabric, Purview or similar )</li><li>Familiarity with AI/ML concepts and practical applications in enterprise settings</li><li>Experience creating data architecture diagrams and technical documentation</li><li>Excellent presentation and storytelling skills, capable of translating technical concepts for executive audiences</li><li>English and Arabic fluency</li></ul> 
Benefits 
Company Industry: Information Technology Services
Company website: https://www.wind-is.com
Location: Maadi - Cairo
Working Hours: 9:00 AM to 5:00 PM.
Working Days: From Sun to Thu.
Benefits: Attractive salary - Social &amp; Medical insurance - Friendly Environment - Learning &amp; Development Opportunities - Other benefits
Apply now to drive innovation and growth with our dynamic team!</div>

Senior AI Data Fabric Engineer

Fractal

<div>
 
 
 AI and Data Platform Engineer
 
 
 
 Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets; an ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work&reg; Institute and recognized as a &lsquo;Cool Vendor&rsquo; and a &lsquo;Vendor to Watch&rsquo; by Gartner.
 
 
 Please visit
 
 Fractal | Intelligence for Imagination
 
 for more information about Fractal.
 
 
 
 
 We are looking for a strong AI Engineer who thrives at the intersection of AI assisted development, data platform engineering, and high velocity delivery.
 
 
 This role focuses on delivering high‑quality, scalable, and governed data assets through spec‑driven development, AI‑enabled engineering workflows, and standardized data patterns. You will work closely with platform, DevOps, SRE, and analytics consumers to enable self‑service analytics while reducing operational toil through automation and reuse.
 
 
 This is a hands‑on engineering role for someone who enjoys modern data engineering, high engineering rigor, and rapid, AI‑accelerated delivery. You may need to work with PST overlapping hours.
 
 
 
 
 
 
 
 Responsibilities:
 
 
 
 
 
 Spec‑Driven &amp; AI‑Accelerated Data Engineering
 
 
 <ul>
 <li>
 Deliver high‑quality data ingestion, transformation, and modeling solutions using Fabric and associated Azure services through spec‑driven development.
 </li>
 <li>
 Apply AI‑enabled development workflows using tools such as GitHub Copilot and LLM‑assisted coding to maximize development velocity without compromising quality.
 </li>
 <li>
 Translate business and analytics requirements into clear technical specifications, schemas, transformations, and acceptance criteria.
 </li>
 <li>
 Participate actively in automated reviews, AI‑assisted refactoring, and iterative improvements.
 </li>
 </ul>
 
 
 Data Pipelines &amp; Modeling
 
 
 <ul>
 <li>
 Build modular, reusable, and testable pipeline components aligned with standardized data patterns.
 </li>
 <li>
 Design and implement ingestion and transformation pipelines using Fabric‑native constructs (Lakehouse, Warehouse, Notebooks, Dataflows Gen2).
 </li>
 <li>
 Optimize transformations for scale, performance, and cost efficiency.
 </li>
 <li>
 Ensure pipelines are dependency‑aware, well‑orchestrated, and production‑ready.
 </li>
 </ul>
 
 
 
 
 
 Self‑Service Analytics Enablement
 
 
 <ul>
 <li>
 Produce consumer‑ready, tested, and governed datasets to enable self‑service analytics for business and analytics users.
 </li>
 <li>
 Apply strong data modeling practices (relational, dimensional, and analytical models) to support reporting and insights.
 </li>
 <li>
 Ensure data quality through validation checks, reconciliations, and automated testing.
 </li>
 <li>
 Platform Collaboration &amp; Production Readiness
 </li>
 <li>
 Collaborate closely with DevOps, SRE, and QA engineers to ensure production readiness and operational reliability.
 </li>
 <li>
 Follow consistent CI/CD, testing, and release practices across environments.
 </li>
 <li>
 Support investigation and resolution of data issues by improving pipeline robustness and observability.
 </li>
 </ul>
 
 
 Engineering Excellence &amp; Automation
 
 
 <ul>
 <li>
 Participate in code and design reviews, upholding engineering standards for quality, performance, and maintainability.
 </li>
 <li>
 Build reusable data assets and automated workflows to reduce manual data support and operational effort.
 </li>
 <li>
 Continuously improve reliability, reusability, and maintainability of data solutions.
 </li>
 </ul>
 
 
 
 Qualifications &amp; Experience
 
 : Core Requirements
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or master&rsquo;s degree in computer science, Engineering, or related field
 </li>
 <li>
 4+ years of professional software, data, or AI engineering experience
 </li>
 <li>
 Strong hands-on experience with:
 </li>
 <li>
 SQL (advanced querying and optimization)
 </li>
 <li>
 Data modeling (relational, dimensional, and analytical models)
 </li>
 <li>
 Distributed data processing concepts
 </li>
 <li>
 AI Engineering &amp; Development Velocity
 </li>
 <li>
 Demonstrated experience using AI assisted development / vibe coding to accelerate delivery
 </li>
 <li>
 Comfort working from detailed specifications rather than exploratory coding alone
 </li>
 <li>
 Strong engineering discipline: clean code, modular design, automated testing
 </li>
 <li>
 Fabric &amp; Azure (Required / Strongly Preferred)
 </li>
 </ul>
 
 
 Experience with strong exposure to:
 
 
 <ul>
 <li>
 Lakehouse, Warehouse, Notebooks, Dataflows Gen2
 </li>
 <li>
 OneLake concepts
 </li>
 </ul>
 
 
 Prior experience with:
 
 
 <ul>
 <li>
 Databricks (Spark, notebooks, pipelines)
 </li>
 <li>
 Azure services such as ADLS, Azure SQL, Synapse
 </li>
 <li>
 Ability to translate Databricks patterns into Fabric native implementations
 </li>
 </ul>
 
 
 
 Personal Attributes
 
 
 
 <ul>
 <li>
 Forward thinking, self-starter mindset
 </li>
 <li>
 Strong problem solving and systems thinking skills
 </li>
 <li>
 Comfortable operating in ambiguity with clear specifications as the stabilizing force
 </li>
 <li>
 Passion for building end to end, production grade AI and data platforms
 </li>
 </ul>
 
 
 
 
 
 Pay
 
 
 
 The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Fractal, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is: $110,000 - $120,000. In addition, for the current performance period, you may be eligible for a discretionary bonus.
 
 
 
 
 
 
 Benefits:
 
 
 
 As a full-time employee of the company or as an hourly employee working more than 30 hours per week, you will be eligible to participate in the health, dental, vision, life insurance, and disability plans in accordance with the plan documents, which may be amended from time to time. You will be eligible for benefits on the first day of employment with the Company. In addition, you are eligible to participate in the Company 401(k) Plan after 30 days of employment, in accordance with the applicable plan terms. The Company provides 11 paid holidays and 12 weeks of Parental Leave. We also follow a &ldquo;free time&rdquo; PTO policy, allowing you the flexibility to take the time needed for either sick time or vacation.
 
 
 
 
 
 
 Fractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
 
 
 
 
</div>

AI Data Platform Engineer

Seeka Technology

<div>Company Description 
We believe strong early career roles should do more than give someone a job title. They should help people grow into the kind of professionals they want to become. At SEEKA Technologies, we give junior team members meaningful work that builds real capability, sharpens problem-solving, and develops practical experience in fast-moving business and technology environments. Our goal is to help emerging talent strengthen their skills, expand their potential, and prepare for a future shaped by constant innovation across business and IT.
SEEKA Technologies (Not Seeka Limited) is a project under its parent organisation, called Fresh Futures Australia, which is an education consultant based in both Australia and Malaysia. We are developing and creating a platform that utilises A.I. to help match students and job seekers to the right opportunities relevant to them from Kindergarten up to the University, along with vocational training centres and language schools, and of course to businesses and companies who need the right candidates. Our mission is to make it easier for anyone to find, filter and apply to educational institutions and companies in a more seamless manner.
We are currently looking to hire a junior Backend AI &amp; Data Pipeline Engineer who wants to build real-world experience in backend systems, data processing, scraping, retrieval, and cloud-based infrastructure. This role is ideal for someone who already has hands-on technical experience and wants to grow further by working on meaningful engineering challenges that support Yuzee&rsquo;s intelligent matching platform. You will contribute to the systems that process data, power search and matching, and improve the efficiency, reliability, and scalability of our platform.
Below are the important details you will need to take note of:<ul><li>
English is the primary language used in the role</li><li>
This is a full-time remote/work-from-home position</li><li>
We welcome both local and international candidates</li><li>
Candidates should have a degree or proven practical experience relevant to the role</li></ul> 

Job Description 
About the role
We are looking for a Backend AI &amp; Data Pipeline Engineer to own the end-to-end data processing infrastructure that powers Yuzee's intelligent course and job matching platform. You will design and maintain scalable, event-driven pipelines that process tens of thousands of daily records, generate semantic embeddings, and feed a growing knowledge graph used for personalised career pathway recommendations.
What you'll do<ul><li>
Design and maintain three distinct processing pipelines &mdash; scheduled job ingestion, event-driven course processing, and a periodic knowledge graph builder &mdash; each with independent trigger logic and cost controls</li><li>
Generate and manage semantic embeddings via Amazon Bedrock (Titan v2), index them in MongoDB Atlas Vector Search, and calibrate similarity thresholds to ensure match accuracy</li><li>
Build and maintain a knowledge graph linking jobs, courses, skills, and industries using FP-Growth association rules and archetype-to-SOC code mapping</li><li>
Build and improve a two-stage discovery and matching API on AWS Lambda &mdash; vector retrieval first, then deep eligibility scoring with LLM re-ranking</li><li>
Right-size Fargate Spot instances and design resumable processing loops that tolerate interruption, keeping infrastructure costs under control as data volume scales</li><li>
Maintain and improve daily job scrapers across multiple sources and build institution data scrapers with robust HTML cleaning pipelines</li></ul>
What we're looking for<ul><li>
1+ years of backend engineering experience focused on data pipelines, ML infrastructure, or search systems</li><li>
Hands-on experience with AWS serverless and container services &mdash; Lambda, ECS Fargate, EventBridge, and Step Functions</li><li>
Strong Python skills &mdash; Pandas, async processing, bulk database operations, and text cleaning</li><li>
Familiarity with vector databases and semantic similarity search; MongoDB Atlas Vector Search experience is a strong plus</li><li>
Cost-conscious infrastructure mindset &mdash; you think in per-record compute costs, free tiers, Spot resilience, and right-sizing</li><li>
Ability to document and communicate complex architecture clearly to both technical and non-technical stakeholders</li></ul>
Nice to have<ul><li>
Experience with knowledge graphs or association rule mining (FP-Growth, Apriori)</li><li>
Experience using LLMs for re-ranking or eligibility assessment on top of vector retrieval results</li><li>
Background in edtech, jobtech, or recommendation/matching systems</li></ul> 

Qualifications 
Degree or existing proven experience 
Additional Information 
Use this instead:
Benefits<ul><li>
Fully remote / work-from-home role</li><li>
Flexible working hours within the team&rsquo;s expected schedule and business needs</li><li>
Opportunity to work on real backend, data, and AI infrastructure projects</li><li>
Exposure to practical engineering challenges in scraping, pipelines, retrieval, and cloud systems</li><li>
Ongoing growth and development within a fast-moving technology environment</li><li>
Opportunity to build long-term value and grow with the company based on performance, including progression and increased responsibility over time</li></ul>
A slightly more polished version:
Benefits<ul><li>
Fully remote / work-from-home position</li><li>
Some flexibility in working hours, depending on team requirements and deliverables</li><li>
Hands-on experience working on meaningful backend, data pipeline, and AI-related systems</li><li>
Opportunity to contribute to a growing platform with real product and engineering challenges</li><li>
Professional growth in a practical, fast-paced environment</li><li>
Strong potential for long-term progression based on performance, regardless of location</li></ul>
If you want it to sound more attractive for hiring, the strongest version would be to add things like:<ul><li>
ownership</li><li>
real product impact</li><li>
career growth</li><li>
direct exposure to architecture and scaling decisions</li></ul></div>

Backend AI & Data Pipeline Engineer

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