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senior full stack engineer

senior ai engineer

Finaira

<div>
 The Senior AI Engineer is a senior individual contributor with deep expertise in a specific domain of AI/ML, responsible for tackling the most complex technical challenges, driving architectural decisions for critical AI components, and setting technical standards. This role requires a blend of advanced research understanding and robust engineering skills to bring cutting-edge AI innovations into production.
 
 
 
 The difference you will make
 
 
 
 <ul>
 <li>
 Act as a subject matter expert in one or more specialized AI/ML domains (e.g., Generative AI, Explainable AI, Large Language Models, Reinforcement Learning, Real-time Anomaly Detection).
 </li>
 <li>
 Lead the design and implementation of highly scalable, fault-tolerant, and high-performance AI systems and infrastructure.
 </li>
 <li>
 Evaluate and integrate new AI/ML research, algorithms, and technologies into product development.
 </li>
 <li>
 Drive continuous improvement in MLOps, model monitoring, and model governance frameworks.
 </li>
 <li>
 Provide expert technical guidance and mentorship to other AI Engineer 1s and Associates.
 </li>
 <li>
 Conduct complex performance tuning, optimization, and debugging of AI/ML models and pipelines.
 </li>
 <li>
 Participate in strategic planning for AI initiatives, identifying opportunities for technological advancement.
 </li>
 <li>
 Influence technical direction and architecture discussions within the AI/ML team and across engineering.
 </li>
 <li>
 Lead code reviews for critical components, ensuring architectural integrity, performance, and maintainability
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 Education:
 
 
 Bachelor's degree or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a closely related quantitative field.
 
 
 Experience:
 
 
 <ul>
 <li>
 5+ years of progressive experience in AI/ML engineering, with a proven track record of designing and deploying complex AI systems into production.
 </li>
 <li>
 Demonstrated deep expertise in a specific AI sub-field
 
 
 </li>
 </ul>
 Technical Skills:
 
 
 <ul>
 <li>
 Expert-level proficiency in Python and advanced ML/DL frameworks (e.g., PyTorch, TensorFlow, JAX).
 </li>
 <li>
 Extensive experience with cloud-native AI/ML services and distributed computing frameworks (e.g., Spark, Ray).
 </li>
 <li>
 Deep understanding and hands-on experience with MLOps best practices, including CI/CD, model serving, and monitoring in production environments.
 </li>
 <li>
 Strong architectural design skills for complex data pipelines and scalable AI inference systems.
 </li>
 <li>
 Proficiency in system design, distributed systems, and performance optimization.
 </li>
 <li>
 Ability to critically evaluate and apply academic research to real-world problems
 
 
 </li>
 </ul>
 Soft Skills:
 
 
 <ul>
 <li>
 Strong ownership and accountability for assigned work.
 </li>
 <li>
 Clear and professional verbal and written communication.
 </li>
 <li>
 Effective time management and task prioritization. o Analytical thinking and problem-solving skills.
 </li>
 <li>
 Ability to work independently, collaborate effectively and mentor junior team members.
 </li>
 <li>
 Ability to actively listen to customers and accurately understand their needs, expectations, and challenges.
 </li>
 <li>
 Adaptability and learning agility in a fast-paced environment.
 </li>
 <li>
 Strong attention to detail and a commitment to quality.
 </li>
 <li>
 Receptiveness to feedback and continuous improvement mindset
 </li>
 </ul>
</div>

Senior AI Engineer

<div>
 
 The Senior AI Engineer is a senior individual contributor with deep expertise in a specific domain of AI/ML, responsible for tackling the most complex technical challenges, driving architectural decisions for critical AI components, and setting technical standards. This role requires a blend of advanced research understanding and robust engineering skills to bring cutting-edge AI innovations into production.
 
 
 
 
 
 The difference you will make:
 
 <ul>
 <li>
 Act as a subject matter expert in one or more specialized AI/ML domains (e.g., Generative AI, Explainable AI, Large Language Models, Reinforcement Learning, Real-time Anomaly Detection).
 </li>
 <li>
 Lead the design and implementation of highly scalable, fault-tolerant, and high-performance AI systems and infrastructure.
 </li>
 <li>
 Evaluate and integrate new AI/ML research, algorithms, and technologies into product development.
 </li>
 <li>
 Drive continuous improvement in MLOps, model monitoring, and model governance frameworks.
 </li>
 <li>
 Provide expert technical guidance and mentorship to other AI Engineer 1s and Associates. &bull; Conduct complex performance tuning, optimization, and debugging of AI/ML models and pipelines.
 </li>
 <li>
 Participate in strategic planning for AI initiatives, identifying opportunities for technological advancement.
 </li>
 <li>
 Influence technical direction and architecture discussions within the AI/ML team and across engineering.
 </li>
 <li>
 Lead code reviews for critical components, ensuring architectural integrity, performance, and maintainability.
 </li>
 </ul>
 
 
 
 
 What you will bring to the role:
 
 
 
 Education:
 
 Bachelor&rsquo;s degree or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a closely related quantitative field.
 
 
 
 
 
 
 Experience:
 
 
 <ul>
 <li>
 5+ years of progressive experience in AI/ML engineering, with a proven track record of designing and deploying complex AI systems into production. Demonstrated deep expertise in a specific AI sub-field.
 </li>
 </ul>
 
 
 Technical Skills:
 
 
 <ul>
 <li>
 Expert-level proficiency in Python and advanced ML/DL frameworks (e.g., PyTorch, TensorFlow, JAX).
 </li>
 <li>
 Extensive experience with cloud-native AI/ML services and distributed computing frameworks (e.g., Spark, Ray).
 </li>
 <li>
 Deep understanding and hands-on experience with MLOps best practices, including CI/CD, model serving, and monitoring in production environments.
 </li>
 <li>
 Strong architectural design skills for complex data pipelines and scalable AI inference systems.
 </li>
 <li>
 Proficiency in system design, distributed systems, and performance optimization. o Ability to critically evaluate and apply academic research to real-world problems.
 </li>
 </ul>
 
 
 Soft Skills:
 
 
 <ul>
 <li>
 Strong ownership and accountability for assigned work.
 </li>
 <li>
 Clear and professional verbal and written communication.
 </li>
 <li>
 Effective time management and task prioritization.
 </li>
 <li>
 Analytical thinking and problem-solving skills.
 </li>
 <li>
 Ability to work independently, collaborate effectively and mentor junior team members.
 </li>
 <li>
 Ability to actively listen to customers and accurately understand their needs, expectations, and challenges.
 </li>
 <li>
 Adaptability and learning agility in a fast-paced environment.
 </li>
 <li>
 Strong attention to detail and a commitment to quality.
 </li>
 <li>
 Receptiveness to feedback and continuous improvement mindset
 </li>
 </ul>
 
 
 
</div>

Valeo

<div>
 
 You will be joining the
 
 AI4ALL
 
 initiative within our Group IS Application Center (GISACC). This agile team is dedicated to revolutionizing our products and internal tools by harnessing the power of cutting-edge
 
 Generative AI
 
 . We aim to build scalable, serverless, and intelligent applications that seamlessly integrate into Valeo&rsquo;s workflow.
 
 
 
 
 
 Mission
 
 
 
 
 
 As a
 
 Senior AI Data Engineer
 
 , you will bridge the gap between raw enterprise data and our Generative AI ecosystem. You will architect the "nervous system" of our AI models, ensuring our LLMs have access to high-quality, real-time, and contextually relevant data to power the next generation of Valeo&rsquo;s Software Defined Vehicle (SDV) tools and internal processes.
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 <ul>
 <li>
 Advanced RAG Architecture: Design and implement end-to-end pipelines for Retrieval-Augmented Generation (RAG), including advanced retrieval techniques, Graph RAG, Agentic RAG, and multimodal RAG.
 </li>
 <li>
 Vector Database Management: Architect and optimize vector stores (e.g., Qdrant, Pinecone) to handle high-dimensional embeddings and ensure low-latency similarity searches.
 </li>
 <li>
 Data Connectivity: Design, develop, and maintain secure data connectors to pull information from various external tools, SaaS platforms, and internal databases.
 </li>
 <li>
 Data Pre-processing for Gen-AI: Develop cleaning and normalization workflows specifically for unstructured data (PDFs, HTML, Markdown) to ensure optimal LLM performance.
 </li>
 <li>
 Orchestration: Use tools like LangChain, LlamaIndex, or Haystack to orchestrate complex data flows between storage, embedding models, and LLM endpoints.
 </li>
 <li>
 Monitoring &amp; Evaluation: Implement "RAG-as-a-service" monitoring to track retrieval quality (faithfulness, relevancy) and data drift in production.
 
 
 </li>
 </ul>
 
 
 Candidate Profile
 
 
 
 
 <ul>
 <li>
 Education: B.Sc. or M.Sc. in Computer Science, Data Engineering, or a related field.
 </li>
 <li>
 Experience: 5+ years in Data Engineering with a recent focus on AI/ML pipelines.
 </li>
 <li>
 Technical Skills:
 </li>
 <ul>
 <li>
 Languages: Expert proficiency in Python and SQL; knowledge of Java or Go is a plus.
 </li>
 <li>
 Data Tools: Experience with Spark, Kafka, Airflow/Prefect, and dbt.
 </li>
 <li>
 AI Frameworks: Hands-on experience with LangChain, LlamaIndex, OpenAI API, Hugging Face, MCP, A2A, and ADK.
 </li>
 <li>
 Vector DBs: Proficiency with Qdrant, Pinecone, Chroma, Weaviate, or pgvector.
 </li>
 <li>
 Cloud/DevOps: Knowledge of GCP/AWS, Docker, and Kubernetes.
 </li>
 </ul>
 <li>
 Preferred: Deep understanding of embedding models, chunking strategies, and unstructured data extraction tools (e.g., Unstructured.io, PyMuPDF).
 </li>
 </ul>
</div>

Senior AI Data Engineer, AI4ALL

700apps

<div>
 We are looking for a highly skilled
 
 Senior AI Engineer / AI Architect
 
 to lead the design, development, and deployment of scalable AI solutions.
 
 
 In this role, you will combine hands-on model development with high-level system architecture to help shape our AI strategy and deliver production-ready intelligent systems.
 
 
 You will work closely with engineering, product, and leadership teams to transform business needs into powerful AI-driven solutions.
 
 
 
 Key Responsibilities
 
 
 
 AI Architecture &amp; System Design
 
 
 <ul>
 <li>
 Design end-to-end AI/ML system architecture from data ingestion to deployment and monitoring.
 </li>
 <li>
 Define scalable and reliable ML pipelines.
 </li>
 <li>
 Select the appropriate tools, frameworks, and infrastructure.
 </li>
 <li>
 Ensure performance, security, scalability, and maintainability of AI systems.
 </li>
 <li>
 Design APIs and AI services for integration with products and platforms.
 
 
 </li>
 </ul>
 Model Development
 
 
 <ul>
 <li>
 Develop, train, and fine-tune machine learning and deep learning models.
 </li>
 <li>
 Work on advanced AI solutions such as LLMs, NLP systems, or computer vision models.
 </li>
 <li>
 Optimize models for accuracy, speed, and cost efficiency.
 </li>
 <li>
 Conduct experiments and evaluate model performance using best practices.
 
 
 </li>
 </ul>
 MLOps &amp; Deployment
 
 
 <ul>
 <li>
 Build and maintain CI/CD pipelines for machine learning workflows.
 </li>
 <li>
 Deploy models to production using containers and cloud services.
 </li>
 <li>
 Implement monitoring, logging, and automated retraining processes.
 </li>
 <li>
 Manage model lifecycle, versioning, and performance tracking.
 
 
 </li>
 </ul>
 Technical Leadership
 
 
 <ul>
 <li>
 Provide technical leadership to AI engineers and data scientists.
 </li>
 <li>
 Review code and guide best practices in AI development.
 </li>
 <li>
 Collaborate with cross-functional teams to align AI solutions with business goals.
 </li>
 <li>
 Contribute to technical strategy and AI roadmap planning.
 
 
 </li>
 </ul>
 
 Required Qualifications
 
 
 
 <ul>
 <li>
 7+ years of experience in AI / Machine Learning engineering.
 </li>
 <li>
 Strong programming skills in Python.
 </li>
 <li>
 Hands-on experience with PyTorch or TensorFlow.
 </li>
 <li>
 Experience working with LLMs and modern AI frameworks.
 </li>
 <li>
 Strong understanding of system design and scalable architectures.
 </li>
 <li>
 Experience with cloud platforms such as AWS, GCP, or Azure.
 </li>
 <li>
 Experience with Docker and Kubernetes.
 </li>
 <li>
 Familiarity with MLOps tools such as MLflow, Airflow, or similar.
 </li>
 <li>
 Solid understanding of data pipelines and data engineering concepts.
 </li>
 </ul>
</div>

AI Architect

Siemens

<div>
 
 About Brightly
 
 
 
 Brightly is a global leader in intelligent, cloud‑based asset lifecycle management, empowering 12,000+ clients with predictive insights to optimize maintenance, energy, and capital planning&mdash;backed by Siemens. Our products help schools, hospitals, cities, and manufacturers keep critical infrastructure running efficiently and sustainably.
 
 
 
 The Opportunity
 
 
 
 We&rsquo;re looking for a Senior Machine Learning Engineer to lead LLM‑powered application development&mdash;from prototype to production&mdash;on AWS. You&rsquo;ll design robust ML/LLM services that power search, recommendations, copilots, and workflow automation in Brightly&rsquo;s platform, partnering closely with product, data, and engineering teams. Responsibilities and skill expectations reflect current industry practice for senior ML/LLM engineers, including end‑to‑end model lifecycle ownership, production‑grade code, and MLOps.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Build LLM applications: Design and implement RAG pipelines, prompt orchestration, tools/agents, safety/guardrails, and evaluation harnesses; instrument for latency, cost, and quality. (Guided by current LLM engineer role practices.)
 </li>
 <li>
 Own the ML lifecycle: Data curation, feature engineering, training/fine‑tuning (LoRA/QLoRA), A/B testing, deployment, monitoring, and continuous improvement of models and prompts.
 </li>
 <li>
 Productionize on AWS: Ship scalable services on EKS/ECS/Lambda; leverage SageMaker, Bedrock, EMR, MSK, Step Functions; apply observability (CloudWatch/OpenTelemetry) and cost controls. (Duties aligned to modern AWS ML roles.)
 </li>
 <li>
 Scale training &amp; inference: Use distributed training (FSDP/DeepSpeed), quantization, caching, vector databases, and GPU/Inferentia for performance and efficiency.
 </li>
 <li>
 MLOps &amp; governance: Establish CI/CD for models (MLflow/Kedro/SageMaker Pipelines), model/version registries, data and prompt lineage, evaluation gates, and responsible‑AI controls. (Aligned with contemporary MLOps templates.)
 </li>
 <li>
 Partner across Brightly: Translate asset‑management use cases into ML/LLM solutions; collaborate with product managers and UX to ship customer‑visible features that measurably improve reliability, safety, and sustainability.
 </li>
 <li>
 Mentor &amp; lead: Provide technical leadership, review designs/PRs, and raise the bar on ML engineering excellence across the team. (Common senior ML expectations.)
 </li>
 <li>
 Perform Exploratory Data Analysis (EDA) on structured, semi‑structured, and unstructured datasets to identify patterns, correlations, feature importance, and data quality issues.
 
 
 </li>
 </ul>
 (Consistent with ML engineer responsibilities to analyze data before model development.)
 
 
 <ul>
 <li>
 Conduct deep research on asset-related, operational, and domain-specific datasets to understand root causes, trends, and predictive signals.
 
 
 </li>
 </ul>
 
 What You&rsquo;ll Bring
 
 
 
 
 Required experience
 
 
 
 <ul>
 <li>
 5&ndash;7 years total software/ML engineering experience, with 3+ years building and operating ML systems in production.
 </li>
 <li>
 1+ years hands‑on LLM application development (e.g., RAG, fine‑tuning, prompt engineering, evaluators/guardrails, agentic workflows) using packages such as Langchain and Langgraph.
 </li>
 <li>
 AWS proficiency (3+ years): Strong with core services (EKS/ECS, Lambda, S3, DynamoDB/RDS, Step Functions, IAM) and ML stack (SageMaker, Bedrock or HF on AWS). (Representative AWS ML role skills.)
 </li>
 <li>
 Modeling &amp; frameworks: Python, PyTorch, Hugging Face ecosystem; vector stores (e.g., OpenSearch, PGVector, Pinecone), embeddings, retrieval, and evaluation metrics for NLP/LLMs. (In line with senior LLM roles.)
 </li>
 <li>
 MLOps: CI/CD for ML, model registries, experiment tracking, telemetry/monitoring, automated retraining; Docker/Kubernetes, GitHub Actions/GitLab CI. (Current MLOps expectations.)
 </li>
 <li>
 Data engineering fluency: ETL/ELT, streaming/batch (Spark/Flink), data quality and governance controls for ML.
 
 
 </li>
 </ul>
 
 Nice to have
 
 
 
 <ul>
 <li>
 Experience with distributed training (FSDP, DeepSpeed), RLHF, or Inferentia/Trainium optimization.
 </li>
 <li>
 Exposure to sustainability/asset/intelligent operations domains.
 </li>
 <li>
 Familiarity with security &amp; compliance for ML systems in enterprise environments. (Frequently included in senior ML roles.)
 
 
 </li>
 </ul>
 How you&rsquo;ll work
 
 
 <ul>
 <li>
 Pragmatic and product‑oriented: You bias to measurable outcomes and iterate quickly with stakeholders. (Modern senior ML role framing.)
 </li>
 <li>
 Engineering excellence: You write production‑quality Python, design reliable APIs/services, and uphold testing/observability standards. (Common duties in senior templates.)
 </li>
 <li>
 Collaborative leadership: You mentor peers and influence architecture across teams. (Industry‑standard senior expectations.)
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s in CS/EE/Math or related field (Master&rsquo;s preferred) or equivalent practical experience. (Typical for senior ML roles.)
 
 
 </li>
 </ul>
 Join a mission‑driven team building technology that keeps communities running&mdash;safer, greener, and more resilient&mdash;at global scale. You&rsquo;ll pair startup‑speed product work with the reach and rigor of Siemens.
 
 
 
 The Brightly culture
 
 
 
 We&rsquo;re guided by a vision of community that serves the ambitions and wellbeing of all people, and our professional communities are no exception. We model that ideal every day by being supportive, collaborative partners to one another, conscientiously making space for our colleagues to grow and thrive. Our passionate team is driven to create a future where smarter infrastructure protects the environments that shape and connect us all. That brighter future starts with us.
</div>

Senior Machine Learning Engineer

Arrow Electronics

<div>
 
 Position
 
 
 
 Senior Java Software Engineer
 
 
 
 Job Description
 
 
 
 
 Senior Java Software Engineer
 
 
 
 
 Job Summary
 
 
 
 We are looking for a Senior Java Software Engineer to build, enhance, and maintain scalable backend systems. You will work across the software development lifecycle, contribute to solution design, and deliver reliable, high-quality software that directly impacts business outcomes.
 
 
 This role focuses on strong Java engineering fundamentals, with exposure to modern cloud, DevOps, data, and AI-enabled integrations.
 
 
 
 Core Responsibilities
 
 
 
 <ul>
 <li>
 Design, develop, and maintain Java-based backend services across multiple releases.
 </li>
 <li>
 Implement new features, handle change requests, and resolve production defects.
 </li>
 <li>
 Estimate tasks accurately and deliver within agreed timelines.
 </li>
 <li>
 Write clean, maintainable, and well-documented code following clean code principles.
 </li>
 <li>
 Debug and troubleshoot complex issues to identify root causes efficiently.
 </li>
 <li>
 Write unit tests using JUnit and follow test-driven development (TDD) practices.
 </li>
 <li>
 Participate in solution and technical design discussions, applying appropriate design patterns.
 </li>
 <li>
 Develop and maintain RESTful APIs.
 </li>
 <li>
 Collaborate closely with team members and cross-functional teams (QA, DevOps).
 </li>
 <li>
 Contribute to CI/CD pipelines and deployment processes using existing DevOps tooling.
 </li>
 <li>
 Continuously learn and adopt new technologies relevant to backend engineering.
 
 
 </li>
 </ul>
 
 DevOps &amp; Deployment (Expected Exposure, Not Ownership)
 
 
 
 <ul>
 <li>
 Work with Docker-based deployments across different environments.
 </li>
 <li>
 Integrate applications into existing CI/CD pipelines (Jenkins, Kubernetes).
 </li>
 <li>
 Support smooth releases and environment stability in collaboration with DevOps teams.
 
 
 </li>
 </ul>
 
 Security &amp; Quality
 
 
 
 <ul>
 <li>
 Apply secure coding practices and follow OWASP Top 10 guidelines.
 </li>
 <li>
 Implement authentication and authorization using JWT / OAuth2.
 </li>
 <li>
 Ensure high code quality through reviews, testing, and automation.
 
 
 </li>
 </ul>
 
 Required Qualifications
 
 
 
 
 Experience &amp; Education
 
 
 
 <ul>
 <li>
 5+ years of professional experience in Java software development.
 </li>
 <li>
 Bachelor&rsquo;s degree in Computer Science or equivalent practical experience.
 
 
 </li>
 </ul>
 
 Core Technical Skills (Must-Have)
 
 
 
 <ul>
 <li>
 Java: Java 17 or Java 21
 </li>
 <li>
 Spring Ecosystem: Spring, Spring Boot, Spring Data, Spring Security, Spring Cloud
 </li>
 <li>
 Architecture: OOP principles, design patterns, clean code
 </li>
 <li>
 Databases: Oracle or MySQL, database design, ERD
 </li>
 <li>
 ORM: JPA / Hibernate
 </li>
 <li>
 Testing: JUnit and unit testing practices
 </li>
 <li>
 APIs: RESTful web services
 </li>
 <li>
 Messaging: Apache Kafka
 </li>
 <li>
 Build &amp; Version Control: Maven, Git
 </li>
 <li>
 Developer Productivity Tools: Windsurf
 </li>
 <li>
 Experience integrating Generative AI or LLM APIs into backend systems.
 </li>
 <li>
 Interest in applying AI to improve automation, data processing, or developer productivity is highly valued.
 
 
 </li>
 </ul>
 
 Nice-to-Have
 
 
 
 
 
 (Experience in these areas is a plus, not a requirement)
 
 
 
 
 <ul>
 <li>
 Search &amp; Indexing: Elasticsearch
 </li>
 <li>
 Monitoring &amp; Observability: Prometheus, Grafana
 </li>
 <li>
 Big Data: Apache Spark.
 </li>
 <li>
 Cloud Platforms: AWS
 
 
 </li>
 </ul>
 
 What We Offer
 
 
 
 <ul>
 <li>
 Opportunity to work on impactful systems with real business value.
 </li>
 <li>
 Exposure to modern backend architecture, cloud-native tools, and AI-enabled solutions.
 </li>
 <li>
 Collaborative engineering culture with strong technical ownership.
 </li>
 <li>
 Continuous learning and professional growth.
 
 
 </li>
 </ul>
 
 Location:
 
 
 
 EG-Cairo, Egypt (Al Emdad &amp; Al Tamween)
 
 
 
 Time Type
 
 
 
 Full time
 
 
 
 Job Category
 
 
 
 Information Technology
</div>

Senior Java Software Engineer

Support Plus 360

<div>
 
 
 Senior Full-Stack Engineer (Omni-Channel / SaaS / Distributed Systems)
 
 
 
 
 
 
 We are expanding our engineering team and looking for a Senior Full-Stack Engineer to work directly across multiple high-scale platform projects.
 
 
 
 
 
 This is not a feature-delivery role.
 
 
 
 
 
 We are building complex, multi-tenant systems including:
 
 
 
 
 
 Omni-channel messaging platforms (WhatsApp / FB / IG)
 
 
 
 
 
 CRM and automation engines
 
 
 
 
 
 AI-assisted workflow systems
 
 
 
 
 
 High-concurrency backend services
 
 
 
 
 
 SaaS-ready distributed architectures
 
 
 
 
 
 You will work closely on architecture decisions, scalability design, infrastructure strategy, and production reliability.
 
 
 
 
 
 We are looking for someone who has already built systems like this &mdash; not someone learning them for the first time.
 
 
 
 
 
 
 Required experience:
 
 
 
 
 
 
 Strong TypeScript across backend and frontend
 
 
 
 
 
 Node.js (NestJS / Express / Fastify)
 
 
 
 
 
 Next.js (App Router preferred)
 
 
 
 
 
 PostgreSQL (indexing, performance tuning, schema design)
 
 
 
 
 
 Redis (queues, caching, distributed coordination)
 
 
 
 
 
 Queue systems (BullMQ, SQS, or similar)
 
 
 
 
 
 Webhook ingestion at scale
 
 
 
 
 
 Idempotency patterns
 
 
 
 
 
 JWT and advanced RBAC design
 
 
 
 
 
 Multi-tenant SaaS architecture
 
 
 
 
 
 Docker and AWS fundamentals
 
 
 
 
 
 Understanding of horizontal scalability and worker-based systems
 
 
 
 
 
 You should be comfortable discussing:
 
 
 
 
 
 Isolation strategies
 
 
 
 
 
 Concurrency handling
 
 
 
 
 
 Background processing
 
 
 
 
 
 Rate limiting
 
 
 
 
 
 Distributed system trade-offs
 
 
 
 
 
 Production monitoring and observability
 
 
 
 
 
 This role involves working alongside a senior architect on multiple projects, contributing to system design and long-term platform direction.
 
 
 
 
 
 If you have built real-world, high-traffic systems and enjoy solving architectural challenges &mdash; we would like to speak with you.
 
 
 
 
 
 
 How To Apply
 
 
 
 
 
 
 Send:
 
 
 
 
 
 Resume, GitHub
 
 
 
 
 
 Describe a scalable system you built
 
 
 
 
 
 Explain how you would architect an omnichannel SaaS platform
 
 
 
 
 
 Please apply only if you have hands-on production experience with similar systems.
 
 
 
 
 
 Apply through:
 
 
 Hr@supportplusco.com
 
 
 
 
 
 and write on title : " Senior Full stack engineer"
 
 
 
 
</div>

Full Stack Engineer

Explore 407+ Senior ai engineer in Cairo Egypt this March. Find roles across top companies and apply now to boost your career.

407 senior ai engineer jobs In Cairo Egypt

Senior AI Engineer

Senior AI Engineer

Senior AI Data Engineer, AI4ALL

AI Architect

Senior Machine Learning Engineer

Senior Java Software Engineer

Full Stack Engineer