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senior machine learning engineer Jobs in Cairo

senior machine learning engineer

software engineer - model based development, power Jobs in Cairo

ai engineer model training fine tuning

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

YO IT Consulting

<div>
 
 Job Description
 
 
 
 
 Job Title:
 
 AI Engineer
 
 
 
 Job Type:
 
 Contract
 
 
 
 Location:
 
 Remote
 
 
 
 Job Summary:
 
 In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required &mdash; your domain knowledge is what matters.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design, build, and optimize robust machine learning models for production environments.
 </li>
 <li>
 Implement and automate end-to-end ML pipelines using CI/CD best practices.
 </li>
 <li>
 Leverage AWS services for scalable AI infrastructure and model deployment.
 </li>
 <li>
 Orchestrate containerized workloads using Kubernetes to ensure high availability and seamless scalability.
 </li>
 <li>
 Collaborate with data scientists, engineers, and researchers to translate complex business problems into actionable ML solutions.
 </li>
 <li>
 Evaluate, preprocess, and frame real-world data problems for effective machine learning applications.
 </li>
 <li>
 Document and communicate findings, solution approaches, and technical decisions with clarity and precision.
 
 
 </li>
 </ul>
 
 Required Skills And Qualifications
 
 
 
 <ul>
 <li>
 Proven expertise in machine learning algorithms, model development, and deployment.
 </li>
 <li>
 Strong programming skills, ideally in Python or Java, with experience in large-scale software engineering projects.
 </li>
 <li>
 In-depth experience with CI/CD workflows and automation tools.
 </li>
 <li>
 Hands-on expertise with AWS cloud services for ML applications and data pipelines.
 </li>
 <li>
 Advanced knowledge of Kubernetes for orchestrating containerized ML workloads.
 </li>
 <li>
 Exceptional written and verbal communication skills, with a focus on clear technical documentation and team collaboration.
 </li>
 <li>
 Demonstrated ability to scope, structure, and solve complex, real-world data challenges.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Familiarity with deep learning frameworks such as TensorFlow or PyTorch.
 </li>
 <li>
 Experience working in high-growth or startup environments.
 </li>
 <li>
 Strong publication record or contributions to open-source AI projects.
 </li>
 </ul>
</div>

AI Engineer - Remote

Infomineo

<div>
 
 
 About us
 
 
 
 Infomineo is a pioneering global AI-enhanced research company that transforms how businesses access, analyze, and act on critical intelligence. We&rsquo;ve evolved from traditional business research outsourcing to become the strategic partner that combines cutting-edge artificial intelligence with deep human expertise. We offer 3 services to our global clients (leading consulting companies, Fortune 500 companies, and government entities): AI and Data Advisory, Next-Gen Insights and Resource Scaling. This is made possible by relying on 3 pillars of excellence:
 
 
 
 
 <ol>
 <li>
 350+ industry experts spread across 5 offices (Cairo, Casablanca, Mexico City, Dubai, Barcelona).
 </li>
 <li>
 Our proprietary AI orchestrator.
 </li>
 <li>
 Extensive knowledge assets combining 500,000+ delivered case studies and database subscriptions.
 </li>
 </ol>
 
 
 
 
 Ready to kick start your career with us?
 
 
 
 Why Infomineo? Here&rsquo;s what sets us apart:
 
 
 <ul>
 <li>
 
 Shape the Future of Business Insights:
 
 You will be at the forefront, leading the design and implementation of AI-driven solutions that automate tasks and drive efficiency across our entire service spectrum (Business Research, Content, Design, and Data Analytics).
 </li>
 <li>
 
 Work with Global Leaders:
 
 Our clients are industry leaders &mdash; Fortune 500s, top consultancies, governments, and NGOs. You will take ownership of delivering technical solutions that directly support their success.
 </li>
 <li>
 
 Lead in AI &amp; Technology:
 
 We foster continuous learning and technical excellence. You will stay ahead of the latest advancements in AI and software engineering, and actively drive innovation across the team.
 </li>
 <li>
 
 Thrive in a Collaborative Culture:
 
 We value intellectual curiosity, leadership, and a can-do attitude. You will be encouraged to mentor others, contribute strategic ideas, and make a lasting impact on the company&rsquo;s growth.
 </li>
 </ul>
 
 
 
 
 
 About this role:
 
 
 
 We are seeking an experienced and technically strong individual to join us as
 
 Senior AI Software Engineer.
 
 In this role, you will take ownership of designing, developing, and deploying AI-powered data products and analytical applications that serve our internal teams and global clients. You will lead data science and AI initiatives, define best practices for applied AI and analytical solution development, and collaborate closely with engineering, product, and business stakeholders. While the role is primarily data science and AI-focused, you will also leverage your full-stack development background to build production-ready applications, integrate AI capabilities, and support cloud-based deployment.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 Data Science, AI &amp; Applied R&amp;D:
 
 
 <ul>
 <li>
 Lead the design and development of AI-powered analytical solutions, data products, and intelligent applications that solve complex business problems.
 </li>
 <li>
 Translate business and client requirements into data science approaches, AI workflows, and scalable technical solutions.
 </li>
 <li>
 Design, prototype, and productionize machine learning, LLM, and generative AI solutions with a focus on business value, reliability, and usability.
 </li>
 <li>
 Own the architecture of Retrieval-Augmented Generation (RAG) pipelines, including document processing, vectorization, semantic search, evaluation, and query optimization for enterprise use cases.
 </li>
 <li>
 Design and implement complex AI-powered features by integrating LLM APIs and services using frameworks such as LangChain or equivalent, with a focus on reliability, accuracy, and performance in production.
 </li>
 <li>
 Design, implement, and maintain Model Context Protocol (MCP) integrations to connect AI models with external tools, APIs, and data sources, enabling context-aware and extensible AI solutions.
 </li>
 <li>
 Develop evaluation frameworks, monitoring approaches, and observability practices for LLM-powered systems to ensure quality, transparency, and continuous improvement.
 </li>
 <li>
 Apply advanced prompt engineering, embedding strategies, and vector database management techniques to improve the performance of AI solutions.
 </li>
 <li>
 Integrate AI outputs into analytical workflows, dashboards, reporting tools, and client delivery pipelines.
 </li>
 </ul>
 
 
 
 
 
 Full-Stack Application Development:
 
 
 <ul>
 <li>
 Design and contribute to the development of production-grade AI and data applications, primarily using Python and backend frameworks such as FastAPI.
 </li>
 <li>
 Build or support frontend interfaces using modern frameworks such as React, Next.js, or Vue to make AI and data products accessible to business users and clients.
 </li>
 <li>
 Collaborate with software engineers to define scalable application architectures, API standards, and integration patterns.
 </li>
 <li>
 Develop and maintain REST API integrations with third-party AI services, enterprise SaaS platforms, internal tools, and external data sources.
 </li>
 <li>
 Ensure that data science prototypes are translated into maintainable, secure, and scalable production solutions.
 </li>
 <li>
 Participate in code reviews, define technical best practices, and contribute to a high-quality engineering and data science culture.
 </li>
 </ul>
 
 
 
 
 
 Cloud, Deployment &amp; MLOps:
 
 
 <ul>
 <li>
 Support the containerization and cloud deployment of AI and data applications, preferably on Google Cloud Platform using GKE and Artifact Registry, while remaining adaptable to other cloud environments.
 </li>
 <li>
 Design and maintain CI/CD pipelines using GitHub Actions or equivalent tools to ensure reliable and repeatable releases.
 </li>
 <li>
 Apply MLOps and LLMOps practices to manage experimentation, deployment, monitoring, and continuous improvement of AI systems.
 </li>
 <li>
 Collaborate with engineering and infrastructure teams to ensure the reliability, scalability, and performance of production environments.
 </li>
 <li>
 Proactively identify performance bottlenecks in AI workflows, data pipelines, application layers, and infrastructure.
 </li>
 </ul>
 
 
 
 
 
 Technical Leadership &amp; Collaboration:
 
 
 <ul>
 <li>
 Lead applied AI and data science initiatives from discovery and prototyping through production deployment.
 </li>
 <li>
 Mentor junior data scientists, AI engineers, and developers on data science methods, AI integration, coding practices, and production readiness.
 </li>
 <li>
 Work closely with product teams, consultants, analysts, and non-technical stakeholders to ensure solutions are aligned with business needs.
 </li>
 <li>
 Define standards and best practices for AI solution design, evaluation, documentation, and delivery.
 </li>
 <li>
 Communicate complex technical concepts clearly to both technical and non-technical audiences.
 </li>
 </ul>
 
 
 
 
 
 Qualifications:
 
 
 <ul>
 <li>
 4 to 6 years of experience in data science, AI development, applied machine learning, or related technical roles, with hands-on experience delivering production-grade AI or data products.
 </li>
 <li>
 Strong proficiency in Python, with experience using data science, machine learning, and AI libraries and frameworks.
 </li>
 <li>
 Solid full-stack development background, including experience with backend frameworks such as FastAPI and modern frontend frameworks such as React, Next.js, or Vue.
 </li>
 <li>
 Deep understanding of LLMs, RAG architectures, generative AI workflows, and production-grade AI service integration, including tools such as OpenAI, Gemini, LangChain, or equivalent.
 </li>
 <li>
 Proven experience designing and implementing Model Context Protocol (MCP) integrations to connect AI models with external tools, APIs, and enterprise data sources.
 </li>
 <li>
 Experience building analytical workflows, dashboards, data pipelines, or AI-powered decision-support tools in a client delivery or enterprise context.
 </li>
 <li>
 Hands-on experience with Docker and cloud deployment on at least one major cloud platform such as GCP, AWS, Azure, or equivalent.
 </li>
 <li>
 Familiarity with container orchestration, artifact management, CI/CD pipelines, GitHub Actions, GitOps workflows, and branching strategies.
 </li>
 <li>
 Strong understanding of LLM observability, AI evaluation, performance monitoring, and production reliability practices.
 </li>
 <li>
 Demonstrated ability to lead technical initiatives, mentor junior team members, and collaborate effectively with product teams and business stakeholders.
 </li>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Computer Science, Software Engineering, Statistics, Applied Mathematics, or a related field.
 </li>
 </ul>
 
 
 
 
 
 Preferred Skills:
 
 
 <ul>
 <li>
 Experience with agentic AI frameworks such as LangGraph or similar orchestration tools for building multi-step AI workflows.
 </li>
 <li>
 Knowledge of advanced prompt engineering, vector database management, embedding model optimization, and AI evaluation techniques.
 </li>
 <li>
 Experience with MLOps or LLMOps practices, including experiment tracking, model monitoring, and AI quality evaluation.
 </li>
 <li>
 Experience with Infrastructure as Code tools such as Terraform or Pulumi.
 </li>
 <li>
 Experience designing data models, analytical pipelines, or BI/dashboard solutions.
 </li>
 <li>
 Relevant certifications such as Google Cloud Professional Data Engineer, Google Cloud Professional Machine Learning Engineer, Google Cloud Professional Developer, or similar cloud and AI credentials.
 </li>
 </ul>
 
 
 
 
 
 What we offer:
 
 
 <ul>
 <li>
 A competitive compensation and benefits package.
 </li>
 <li>
 The opportunity to lead AI and technology initiatives with real global impact.
 </li>
 <li>
 A dynamic and supportive work environment that values leadership, innovation, and your contributions.
 </li>
 <li>
 Continuous learning and professional development opportunities to propel your career forward in AI and software engineering.
 </li>
 </ul>
 
 
 
 
 
 Application Process:
 
 
 
 Candidates are invited to submit a resume, cover letter, and any relevant portfolio or GitHub links showcasing their experience in web application development, AI integration, and cloud deployment. Shortlisted candidates will undergo a technical assessment and interview to demonstrate their skills and technical leadership capabilities.
 
 
 
 
 
 
 Infomineo: Where brilliant minds meet to shape the future of business.
 
 
 
 
</div>

AI & Analytics - Sr. Software Engineer with AI Background - Cairo

Valeo

<div>
 Valeo est une entreprise mondiale de haute technologie qui con&ccedil;oit des solutions r&eacute;volutionnaires pour r&eacute;inventer la mobilit&eacute;. Nous sommes un &eacute;quipementier partenaire des constructeurs automobiles et des acteurs de la nouvelle mobilit&eacute; dans le monde entier. Notre vision ? Inventer une mobilit&eacute; plus verte et plus s&ucirc;re, gr&acirc;ce &agrave; des solutions ax&eacute;es sur la conduite intuitive et la r&eacute;duction des &eacute;missions de CO2. Nous sommes leaders dans nos domaines d'activit&eacute; et reconnus comme l'une des plus grandes entreprises innovantes au monde.
 
 
 
 Mission
 
 
 
 The SysOps/SRE Lead is responsible for the implementation, architectural reliability, scalability, and operational health of the R&amp;D infrastructure worldwide. You will bridge the gap between development and operations by defining and applying engineering practices to system administration.
 
 
 As a Lead, you are the owner of the platform&rsquo;s and the architect of the team&rsquo;s operational excellence, ensuring that our global toolchain remains resilient under pressure. while Also planning, organizing, leading and controlling SRE Teams Implementation timeline and standards adherence.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Operational Excellence~ Define and manage the On-Call schedules and rotations, ensuring global coverage models are sustainable, fair, and optimized for rapid incident response.
 </li>
 <li>
 Incident Leadership~ Serve as the primary escalation point for critical infrastructure and critical applications production incidents. Lead "Blameless Post-Mortems" to identify root causes and ensure permanent remediation, also manage and investigate normal Application incidents according to the defined SLA/SLO.
 </li>
 <li>
 Health Oversight~ Define, implement and Maintain daily oversight of system health monitors and error budgets. You are expected to identify systemic weaknesses and performance regressions before they impact the end-user.
 </li>
 <li>
 Documentations~ Ensure Excellent documentation of implementations, runbooks, and best practices.
 </li>
 <li>
 Planning~ Drive the definition and planning and implementation of Program Increment (PI) related infrastructure activities. You will translate business requirements into technical roadmaps and ensure the team remains aligned with organizational milestones.
 </li>
 <li>
 Delivery Excellence~ Ensure the team meets defined schedules and technical benchmarks. You will balance the "50/50" SRE split&mdash;ensuring that at least half of the team&rsquo;s capacity is dedicated to engineering improvements rather than reactive toil.
 </li>
 <li>
 Standards &amp; Compliance~ Define and enforce standards for Cloud Center, security patching, and infrastructure-as-code (IaC). You hold the final approval for production readiness.
 </li>
 <li>
 Infrastructure Evolution~ Oversee the design of secure, multi-region AWS environments, focusing on high availability and cost-optimization. by fine tuning Systems/applications/infrastructure resources for best performance, while keeping cost lower
 </li>
 <li>
 Observability Framework~ Standardize our monitoring stack (Prometheus, Grafana, ELK) to move from basic alerting to proactive, functional observability.
 </li>
 <li>
 Mentorship~ Provide technical mentorship to junior and mid-level engineers, fostering a culture of automation, documentation, and continuous improvement.
 </li>
 <li>
 Reporting and Governance~ Define and report KPIs to asses platform health and service level End-2-End.
 
 
 </li>
 </ul>
 
 Qualifications/Technical Skills Required
 
 
 
 <ul>
 <li>
 Excellent knowledge in Windows/Linux Administration
 </li>
 <li>
 Excellent knowledge in AWS Preferred (Or any similar Cloud Providers)
 </li>
 <li>
 Excellent knowledge in Terraform and Ansible
 </li>
 <li>
 Excellent knowledge in Docker or any containerization technology
 </li>
 <li>
 Excellent knowledge in Jenkins
 </li>
 <li>
 Excellent knowledge in Kubernetes
 </li>
 <li>
 Excellent knowledge in observability tools
 </li>
 <li>
 Excellent knowledge in Git (Source control tools)
 </li>
 <li>
 Very Good knowledge in any scripting language for automations
 </li>
 <li>
 very good knowledge in SAFe/agile Methedologies
 </li>
 <li>
 English Language is a must
 </li>
 <li>
 Professional Experience of 8+ years is required
 
 
 </li>
 </ul>
 
 Position~
 
 
 
 R&amp;D Engineer
 
 
 
 D&eacute;partement~
 
 
 
 R&amp;D DSIS Applications Technical
 
 
 
 Schedule~
 
 
 
 Temps plein
 
 
 
 Employee Status~
 
 
 
 CDI
 
 
 
 Type de contrat~
 
 
 
 
 Job Posting Date~
 
 
 
 2025-06-01
 
 
 
 Join Us !
 
 
 Being part of our team, you will join~
 
 
 <ul>
 <li>
 one of the largest global innovative companies, with more than 20,000 engineers working in Research &amp; Development
 </li>
 <li>
 a multi-cultural environment that values diversity and international collaboration
 </li>
 <li>
 more than 100,000 colleagues in 31 countries... which make a lot of opportunity for career growth
 </li>
 <li>
 a business highly committed to limiting the environmental impact if its activities and ranked by Corporate Knights as the number one company in the automotive sector in terms of sustainable development
 
 
 </li>
 </ul>
 More information on Valeo~ https~//www.valeo.com
 
</div>

SysOps/SRE Lead, GISACC

Intellias

<div>
 
 
 Tech Lead Engineer &ndash; AI Registry &amp; Discovery Platform (AWS AgentCore)
 
 
 
 
 About the Role
 
 
 
 
 
 
 We are looking for a
 
 Tech Lead Engineer
 
 to design and lead the implementation of an enterprise-grade
 
 AI Registry and Discovery Platform
 
 for AI agents, tools, and MCP services. This role focuses on service registration, metadata governance, semantic discovery, identity mapping, lifecycle management, and integration with the AWS AgentCore ecosystem.
 
 
 As a technical leader, you will drive the architecture and development of a scalable platform that enables secure discovery, governance, and lifecycle management of AI capabilities across the enterprise. You will collaborate with platform, security, and AI engineering teams to establish engineering standards, governance processes, and best practices for enterprise AI platforms.
 
 
 The ideal candidate has strong platform engineering expertise, experience building large-scale registry or catalog systems, and a deep understanding of cloud-native architectures, API security, metadata management, and distributed systems.
 
 
 
 
 
 
 Project Overview
 
 
 
 Our customer is a multinational corporation with more than a century of history and operations in over 180 countries. One of its key strategic initiatives is the development and adoption of a new generation of Reduced-Risk Products (RRPs), targeting more than one billion consumers worldwide.
 
 
 Intellia partners with the customer to engineer a comprehensive software ecosystem supporting innovative IoT products, digital commerce, and enterprise platforms. Our engineering teams develop core platform components powering best-in-class eCommerce, Digital Marketing, and IoT solutions.
 
 
 As a
 
 Tech Lead Engineer
 
 , you will become part of the
 
 Core Architecture Team
 
 , contributing to the design and implementation of a modern Digital Engineering Enterprise Platform.
 
 
 The platform provides engineering teams with reusable services, cloud technologies, governance standards, and operational best practices that accelerate software delivery across more than 700 enterprise applications.
 
 
 
 
 
 
 Responsibilities
 
 
 <ul>
 <li>
 Lead the architecture, design, and implementation of an enterprise AI Registry and Discovery Platform.
 </li>
 <li>
 Design and maintain metadata schemas for MCP servers, AI tools, and agent capabilities aligned with Canonical Contract standards.
 </li>
 <li>
 Build scalable backend services using Python, FastAPI, DynamoDB, and AWS-native technologies.
 </li>
 <li>
 Develop registration, discovery, approval, certification, and lifecycle management workflows for AI agents and MCP services.
 </li>
 <li>
 Design semantic discovery capabilities using vector search, embeddings, and relevance-ranking techniques.
 </li>
 <li>
 Integrate enterprise identity systems and implement Entra Agent ID mapping across AI ecosystems.
 </li>
 <li>
 Implement secure authentication and authorization using OAuth 2.0, JWT, and enterprise identity providers.
 </li>
 <li>
 Design governance processes for onboarding, approval, certification, versioning, deprecation, and retirement of AI services.
 </li>
 <li>
 Develop APIs supporting registry operations, metadata management, discovery services, and governance workflows.
 </li>
 <li>
 Implement secure credential and secret management using HashiCorp Vault and cloud-native security controls.
 </li>
 <li>
 Design observability, auditing, compliance, and operational monitoring capabilities across the registry platform.
 </li>
 <li>
 Collaborate with AI, platform, cloud, and security teams to establish registry standards, governance policies, and engineering best practices.
 </li>
 <li>
 Mentor engineers, provide technical leadership, and support architectural decision-making across the platform.
 </li>
 <li>
 Produce architecture documentation, implementation standards, and technical governance guidelines.
 </li>
 </ul>
 
 
 
 
 
 Requirements
 
 
 <ul>
 <li>
 Bachelor's degree in computer science, Software Engineering, or a related field.
 </li>
 <li>
 5+ years of backend or platform engineering experience.
 </li>
 <li>
 Experience designing and building enterprise-scale registry, catalog, metadata management, or discovery platforms.
 </li>
 <li>
 Strong Python development experience, including Fast API and backend service development.
 </li>
 <li>
 Experience with AWS services, including AWS Agent Core Registry, Gateway, DynamoDB, and related cloud-native technologies.
 </li>
 <li>
 Experience designing metadata schemas and service registration models.
 </li>
 <li>
 Knowledge of semantic search technologies, vector databases, embeddings, and AI-powered discovery.
 </li>
 <li>
 Experience implementing secure API authentication and authorization using OAuth 2.0 and JWT.
 </li>
 <li>
 Experience integrating governance workflows, approval processes, and lifecycle management into enterprise platforms.
 </li>
 <li>
 Experience integrating enterprise identity providers and identity mapping solutions.
 </li>
 <li>
 Strong understanding of cloud-native architecture, distributed systems, API design, and platform engineering.
 </li>
 <li>
 Excellent leadership, communication, mentoring, and stakeholder management skills.
 </li>
 </ul>
 
 
 
 
 
 Nice to Have
 
 
 <ul>
 <li>
 Hands-on experience with AWS AgentCore Registry and Gateway.
 </li>
 <li>
 Experience with vector databases such as pgvector, OpenSearch, or similar semantic search technologies.
 </li>
 <li>
 Experience with HashiCorp Vault or enterprise secrets management platforms.
 </li>
 <li>
 Familiarity with MCP (Model Context Protocol) standards and Canonical Contract schema design.
 </li>
 <li>
 Experience implementing observability and distributed tracing solutions.
 </li>
 <li>
 Knowledge of CI/CD pipelines, Infrastructure as Code (IaC), and cloud security best practices.
 </li>
 </ul>
 
 Why Join Us
 
 <ul>
 <li>
 Lead the development of an enterprise AI Registry and Discovery Platform supporting next-generation AI applications.
 </li>
 <li>
 Work with cutting-edge AWS AgentCore technologies, semantic search, and cloud-native architectures.
 </li>
 <li>
 Drive engineering standards, governance, and technical strategy for enterprise AI platforms.
 </li>
 <li>
 Collaborate with experienced AI, platform, and cloud engineering teams on innovative global-scale solutions.
 </li>
 <li>
 Make a significant impact by shaping the future of AI service discovery, governance, and lifecycle management across a large enterprise.
 </li>
 </ul>
 
 
 
</div>

Python Team Lead – AI Registry & Discovery Platform (AWS AgentCore)

Decima International

<div>
 Decima International is a professional services company, providing project management and controls services to clients in the United States and the Middle East. Our mission is to become the premier professional services provider across all industry sectors we are engaged in. To accomplish this, Decima International's founders established a simple yet powerful formula:
 
 
 Approach each client engagement as a
 
 partnership
 
 , create an environment that attracts the
 
 most talented professionals
 
 and allows them to flourish, and regulate
 
 growth
 
 to maintain
 
 excellence
 
 in our service standards.
 
 
 
 Decima International
 
 is a professional services company, providing project management and controls services to clients in the United States and the Middle East. Our mission is to become the premier professional services provider across all industry sectors we are engaged in. To accomplish this, Decima International's founders established a simple yet powerful formula:
 
 
 Approach each client engagement as a partnership, create an environment that attracts the most talented professionals and allows them to flourish, and regulate growth to maintain excellence in our service standards.
 
 
 We are looking for a driven and capable
 
 Mid-Level AI Engineer/Agentic Systems Developer
 
 to support the development of internal technology products. This role will write, configure, test, and maintain a growing library of autonomous AI agents designed to automate complex business workflows.
 
 
 Working under technical and product leadership, the successful candidate will translate functional workflow specifications into individual agents, tool integrations, data connections, and reliable automated processes. The ideal candidate has strong backend development capabilities and practical experience working with large language models, agentic frameworks, APIs, and retrieval-augmented generation pipelines.
 
 
 This is a highly hands-on development role focused on clean code execution, secure systems integration, continuous testing, effective debugging, and rapid iteration.
 
 
 We are looking to bring in dedicated individuals with a passion for innovation and talent for multitasking in a fast-paced environment. We will help you grow, pursue, and fulfill what inspires you so we can make big impacts on the world, together.
 
 
 
 RESPONSIBILITIES
 
 
 
 <ul>
 <li>
 Build and configure autonomous agent roles, task nodes, workflows, and conditional edges using frameworks such as LangGraph, CrewAI, and LlamaIndex.
 </li>
 <li>
 Integrate AI agents securely with internal databases and third-party platforms, including Slack, HubSpot, Salesforce, and Google Workspace, through APIs and function calling.
 </li>
 <li>
 Develop and refine retrieval-augmented generation pipelines, including data ingestion, text chunking, embedding generation, and vector database population.
 </li>
 <li>
 Diagnose and resolve agent failures involving context loss, malformed structured or JSON outputs, and incomplete multi-step tasks.
 </li>
 <li>
 Write automated unit tests for custom tools and monitor execution traces to identify and resolve edge-case failures.
 </li>
 <li>
 Maintain clean, reliable, and well-structured code while supporting continuous testing and rapid product iteration.
 
 
 </li>
 </ul>
 
 QUALIFICATIONS
 
 
 
 
 Required Qualifications:
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Information Technology, or related fields.
 </li>
 <li>
 
 2 to 4 years
 
 of professional experience in backend software development.
 </li>
 <li>
 
 At least 1 year
 
 of practical experience working directly with large language model APIs and prompt construction.
 </li>
 <li>
 Strong familiarity with agentic AI frameworks such as LangGraph, CrewAI, or LlamaIndex.
 </li>
 <li>
 Solid understanding of structural prompt design, including generating reliable JSON and other structured outputs.
 </li>
 <li>
 High proficiency in Python, including a practical understanding of asynchronous programming concepts.
 </li>
 <li>
 Experience developing and integrating RESTful APIs using FastAPI, Flask, or similar frameworks.
 </li>
 <li>
 Proficiency in version control and collaborative software development using Git.
 </li>
 <li>
 Working knowledge of relational databases, preferably PostgreSQL.
 </li>
 <li>
 Foundational experience using vector databases or stores such as Chroma or Pinecone for data retrieval.
 </li>
 <li>
 Experience integrating software applications with databases, APIs, and third-party platforms.
 </li>
 <li>
 Strong debugging, analytical, testing, documentation, and problem-solving skills.
 </li>
 <li>
 Ability to translate functional workflow requirements into reliable technical implementations.
 </li>
 <li>
 Ability to work independently, manage development priorities, and iterate quickly in a fast-paced environment.
 
 
 </li>
 </ul>
 
 Preferred Qualifications:
 
 
 
 <ul>
 <li>
 Experience developing autonomous agents or multi-agent workflows for practical business use cases.
 </li>
 <li>
 Experience implementing retrieval-augmented generation applications and data-ingestion pipelines.
 </li>
 <li>
 Experience with secure function calling and integrations involving business platforms such as Slack, HubSpot, Salesforce, or Google Workspace.
 </li>
 <li>
 Experience testing, tracing, and monitoring multi-step AI workflows in development or production environments.
 </li>
 <li>
 Familiarity with prompt evaluation, structured-output validation, and common large language model failure patterns.
 </li>
 <li>
 Experience contributing to the development of internal technology products or workflow-automation solutions.
 
 
 </li>
 </ul>
 
 POSITION DETAILS
 
 
 
 <ul>
 <li>
 
 Primary Location (Office-based):
 
 Heliopolis, Cairo, Egypt
 </li>
 <li>
 
 Position:
 
 Mid-Level AI Engineer/Agentic Systems Developer
 </li>
 <li>
 
 Position Classification:
 
 Salary-based full-time hours
 
 
 </li>
 </ul>
 
 PRODUCTIVITY TOOLS
 
 
 
 <ul>
 <li>
 Python
 </li>
 <li>
 LangGraph
 </li>
 <li>
 CrewAI
 </li>
 <li>
 LlamaIndex
 </li>
 <li>
 FastAPI
 </li>
 <li>
 Flask
 </li>
 <li>
 Git
 </li>
 <li>
 PostgreSQL
 </li>
 <li>
 Chroma
 </li>
 <li>
 Pinecone
 </li>
 <li>
 Microsoft Office
 </li>
 <li>
 Microsoft 365
 
 
 </li>
 </ul>
 Decima International is an Equal Opportunity Employer that is committed to the safety and well-being of all. All qualified applicants will receive consideration for employment without regard to race, religion, creed, color, national origin, ancestry, sex (including pregnancy, childbirth, breastfeeding, or medical conditions related to pregnancy, childbirth, or breastfeeding), age, medical condition, marital or domestic partner status, sexual orientation, gender, gender identity, gender expression and transgender status, mental disability or physical disability, genetic information, military or veteran status, citizenship, low-income status or any other status or characteristic protected by applicable law.
</div>

Mid-Level AI Engineer/Agentic Systems Developer (On-site) - Cairo, Egypt

<div>
 
 
 About us
 
 
 
 Infomineo is a pioneering global AI-enhanced research company that transforms how businesses access, analyze, and act on critical intelligence. We&rsquo;ve evolved from traditional business research outsourcing to become the strategic partner that combines cutting-edge artificial intelligence with deep human expertise. We offer 3 services to our global clients (leading consulting companies, Fortune 500 companies, and government entities): AI and Data Advisory, Next-Gen Insights and Resource Scaling. This is made possible by relying on 3 pillars of excellence:
 
 
 
 
 <ol>
 <li>
 350+ industry experts spread across 5 offices (Cairo, Casablanca, Mexico City, Dubai, Barcelona).
 </li>
 <li>
 Our proprietary AI orchestrator.
 </li>
 <li>
 Extensive knowledge assets combining 500,000+ delivered case studies and database subscriptions.
 </li>
 </ol>
 
 
 
 
 Ready to kick start your career with us?
 
 
 
 
 
 
 Why Infomineo? Here&rsquo;s what sets us apart:
 
 
 <ul>
 <li>
 
 Shape the Future of Business Insights:
 
 You will be at the forefront, leading the design and implementation of AI-driven solutions that automate tasks and drive efficiency across our entire service spectrum (Business Research, Content, Design, and Data Analytics).
 </li>
 <li>
 
 Work with Global Leaders:
 
 Our clients are industry leaders &mdash; Fortune 500s, top consultancies, governments, and NGOs. You will take ownership of delivering technical solutions that directly support their success.
 </li>
 <li>
 
 Lead in AI &amp; Technology:
 
 We foster continuous learning and technical excellence. You will stay ahead of the latest advancements in AI and software engineering, and actively drive innovation across the team.
 </li>
 <li>
 
 Thrive in a Collaborative Culture:
 
 We value intellectual curiosity, leadership, and a can-do attitude. You will be encouraged to mentor others, contribute strategic ideas, and make a lasting impact on the company&rsquo;s growth.
 </li>
 </ul>
 
 
 
 
 
 About this role:
 
 
 
 We are seeking an experienced and technically strong individual to join us as a
 
 Senior AI Software Engineer
 
 . In this role, you will take ownership of the design, development, and deployment of AI-powered web applications that serve our internal teams and global clients. You will lead technical initiatives, define architectural standards, and mentor junior engineers, while working across the full stack from application code to AI integration and cloud infrastructure.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 Application Development:
 
 
 <ul>
 <li>
 Architect and lead the development of scalable, production-grade web applications, primarily using Python (FastAPI) for the backend and React, Next.js, or Vue for the frontend, while remaining adaptable to other technologies based on project scope and requirements.
 </li>
 <li>
 Define and enforce coding standards, design patterns, and architectural best practices across the engineering team to ensure maintainability and scalability.
 </li>
 <li>
 Lead code reviews, provide technical feedback to junior engineers, and actively contribute to building a high-quality engineering culture.
 </li>
 <li>
 Collaborate with stakeholders and product teams to translate business requirements into robust technical solutions, owning features end-to-end.
 </li>
 </ul>
 
 
 
 
 
 AI &amp; LLM Integration:
 
 
 <ul>
 <li>
 Design and implement complex AI-powered features by integrating LLM APIs and services using frameworks such as LangChain or equivalent, with a focus on reliability and performance in production.
 </li>
 <li>
 Own the architecture of Retrieval-Augmented Generation (RAG) pipelines, including document processing, vectorization, semantic search, and query optimization for large-scale enterprise use cases.
 </li>
 <li>
 Design, implement, and maintain Model Context Protocol (MCP) integrations to connect AI models with external tools, APIs, and data sources, enabling context-aware and extensible AI solutions.
 </li>
 <li>
 Design and maintain robust REST API integrations with third-party AI services and enterprise SaaS platforms, ensuring data integrity and performance at scale.
 </li>
 <li>
 Implement LLM observability and monitoring strategies to ensure transparency, reliability, and continuous improvement of AI features in production environments.
 </li>
 </ul>
 
 
 
 
 
 Deployment &amp; DevOps:
 
 
 <ul>
 <li>
 Lead the containerization and cloud deployment of applications, preferably on Google Cloud Platform (GCP) using GKE and Artifact Registry, while remaining open to other cloud environments based on project requirements.
 </li>
 <li>
 Design and maintain CI/CD pipelines using GitHub Actions or equivalent tools, applying GitOps principles and automated deployment workflows to ensure reliable and repeatable releases.
 </li>
 <li>
 Own the reliability and performance of production environments, proactively identifying bottlenecks and driving resolution of infrastructure and application issues.
 </li>
 </ul>
 
 
 
 
 
 Qualifications:
 
 
 <ul>
 <li>
 4 to 6 years of experience in software engineering and AI development, with a proven track record of delivering production-grade web applications and AI-powered systems.
 </li>
 <li>
 Strong proficiency in Python and a backend framework (preferably FastAPI), with solid experience in a modern frontend framework such as React, Next.js, or Vue.
 </li>
 <li>
 Deep understanding of LLMs, RAG architectures, and production-grade AI service integration (e.g., OpenAI, Gemini, LangChain or equivalent), including observability and performance monitoring.
 </li>
 <li>
 Proven experience designing and implementing Model Context Protocol (MCP) integrations to connect AI models with external tools, APIs, and enterprise data sources.
 </li>
 <li>
 Hands-on experience with Docker and cloud deployment on at least one major cloud platform (AWS, Azure, GCP, or equivalent), with familiarity with container orchestration and artifact management services.
 </li>
 <li>
 Proven experience designing and maintaining CI/CD pipelines using GitHub Actions or similar tools, with strong command of GitOps workflows and branching strategies.
 </li>
 <li>
 Demonstrated ability to lead technical initiatives, mentor junior engineers, and collaborate effectively with product teams and non-technical stakeholders.
 </li>
 <li>
 Experience integrating AI outputs into analytical workflows, dashboards, or data pipelines in a client delivery context.
 </li>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Software Engineering, or a related field.
 </li>
 </ul>
 
 
 
 
 
 Preferred Skills:
 
 
 <ul>
 <li>
 Experience with agentic AI frameworks such as LangGraph or similar orchestration tools for building multi-step AI workflows.
 </li>
 <li>
 Knowledge of advanced prompt engineering, vector database management, and embedding model optimization for production environments.
 </li>
 <li>
 Experience with Infrastructure as Code (IaC) tools such as Terraform or Pulumi.
 </li>
 <li>
 Relevant certifications such as Google Cloud Professional Developer or similar cloud and AI credentials.
 </li>
 </ul>
 
 
 
 
 
 What we offer:
 
 
 <ul>
 <li>
 A competitive compensation and benefits package.
 </li>
 <li>
 The opportunity to lead AI and technology initiatives with real global impact.
 </li>
 <li>
 A dynamic and supportive work environment that values leadership, innovation, and your contributions.
 </li>
 <li>
 Continuous learning and professional development opportunities to propel your career forward in AI and software engineering.
 </li>
 </ul>
 
 
 
 
 
 Application Process:
 
 
 
 Candidates are invited to submit a resume, cover letter, and any relevant portfolio or GitHub links showcasing their experience in web application development, AI integration, and cloud deployment. Shortlisted candidates will undergo a technical assessment and interview to demonstrate their skills and technical leadership capabilities.
 
 
 
 
 
 
 Infomineo: Where brilliant minds meet to shape the future of business.
 
 
 
 
</div>

Data Analytics - Sr. Software Engineer with AI background - Cairo

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