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Intellias

<div>
 
 
 Python / AI Engineer (AWS Bedrock, Multi-Agent AI)
 
 
 
 
 About the Role
 
 
 
 
 
 
 We are looking for a
 
 Python / AI Engineer
 
 to design, build, and test intelligent multi-agent applications running on
 
 AWS Bedrock
 
 . In this role, you will develop AI agents using modern agent frameworks, implement agent collaboration and delegation patterns, integrate foundation models, and establish testing and evaluation practices for production-grade AI solutions.
 
 
 You will work closely with AI engineers, platform teams, and architects to build scalable, maintainable, and enterprise-ready agent-based applications.
 
 
 
 
 
 
 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
 
 Python / AI Engineer
 
 , you will become part of the
 
 Core Architecture Team
 
 , contributing to the development of a modern Digital Engineering Enterprise Platform.
 
 
 The platform provides engineering teams with reusable services, development tools, cloud technologies, governance standards, and operational best practices that accelerate software delivery across more than 700 enterprise applications.
 
 
 
 
 
 
 Responsibilities
 
 
 <ul>
 <li>
 Design, develop, and maintain AI agent applications using Python and modern agent frameworks such as LangGraph, Strands, CrewAI, or equivalent.
 </li>
 <li>
 Build intelligent multi-agent workflows with collaboration and delegation capabilities.
 </li>
 <li>
 Integrate AI agents with AWS Bedrock foundation models and related AWS AI services.
 </li>
 <li>
 Develop Agent-to-Agent (A2A) communication using JSON-RPC 2.0, Server-Sent Events (SSE), and related communication patterns.
 </li>
 <li>
 Design and implement automated testing strategies for agent behavior, workflow correctness, and system reliability.
 </li>
 <li>
 Build evaluation frameworks using pytest, LangSmith, and other testing and validation tools.
 </li>
 <li>
 Create reusable components, templates, and pattern libraries that accelerate AI application development.
 </li>
 <li>
 Produce clear technical documentation, implementation guides, and engineering best practices.
 </li>
 <li>
 Collaborate with platform, AI, DevOps, and product teams to deliver scalable and production-ready AI solutions.
 </li>
 <li>
 Monitor, troubleshoot, and optimize agent performance, reliability, and operational efficiency.
 </li>
 <li>
 Promote engineering excellence through observability, testing, governance, and AI application lifecycle best practices.
 </li>
 </ul>
 
 
 
 
 
 Requirements
 
 
 <ul>
 <li>
 Bachelor's degree in computer science, Software Engineering, or a related field.
 </li>
 <li>
 4+ years of professional Python software development experience.
 </li>
 <li>
 Hands-on experience with at least one modern agent framework such as LangGraph, Strands, Crew AI, or an equivalent framework.
 </li>
 <li>
 Experience implementing multi-agent collaboration and delegation patterns.
 </li>
 <li>
 Experience integrating applications with AWS Bedrock APIs and foundation models.
 </li>
 <li>
 Knowledge of Agent-to-Agent (A2A) communication patterns, including JSON-RPC 2.0 and Server-Sent Events (SSE).
 </li>
 <li>
 Experience building automated testing frameworks using pytest and AI evaluation tools such as LangSmith.
 </li>
 <li>
 Experience writing technical documentation and creating reusable engineering assets.
 </li>
 <li>
 Strong understanding of software engineering best practices, code quality, and testing methodologies.
 </li>
 <li>
 Excellent problem-solving, communication, and collaboration skills.
 </li>
 </ul>
 
 
 
 
 
 Nice to Have
 
 
 <ul>
 <li>
 Hands-on experience with the Strands SDK.
 </li>
 <li>
 Experience with LangSmith tracing, evaluation, and observability.
 </li>
 <li>
 Familiarity with prompt engineering and AI evaluation methodologies.
 </li>
 <li>
 Experience deploying AI applications in AWS cloud environments.
 </li>
 <li>
 Knowledge of CI/CD pipelines, Infrastructure as Code (IaC), and cloud-native application development.
 </li>
 </ul>
 
 
 
 
 
 Why Join Us
 
 
 <ul>
 <li>
 Work on enterprise-scale AI initiatives for a global industry leader.
 </li>
 <li>
 Build intelligent multi-agent applications using the latest AI frameworks and AWS Bedrock technologies.
 </li>
 <li>
 Collaborate with experienced architects and AI engineers on innovative cloud-native solutions.
 </li>
 <li>
 Contribute to engineering standards, reusable frameworks, and best practices for enterprise AI development.
 </li>
 <li>
 Be part of a team shaping the future of production-grade AI applications at global scale.
 </li>
 </ul>
 
 
 
</div>

Senior Python / AI Engineer (AWS Bedrock, Multi-Agent AI)

<div>
 
 
 Senior Python Engineer &ndash; Multi-Agent AI (AWS, LangGraph)
 
 
 
 
 
 
 
 About the Role
 
 
 
 We are looking for a
 
 Senior Python Engineer
 
 to design and build enterprise-grade
 
 multi-agent AI systems
 
 on AWS. In this role, you will architect and develop intelligent agent solutions using
 
 LangGraph
 
 ,
 
 LangChain
 
 , and
 
 AWS Bedrock AgentCore Runtime
 
 , focusing on scalable orchestration, stateful workflow execution, human-in-the-loop (HITL) processes, and distributed agent collaboration.
 
 
 You will work closely with architects, platform engineers, and product teams to deliver production-ready AI solutions that are reliable, scalable, and aligned with enterprise engineering standards.
 
 
 
 
 
 
 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. The engineering organization develops core platform components powering best-in-class eCommerce, Digital Marketing, and IoT solutions.
 
 
 As a
 
 Senior Python Engineer
 
 , you will join the
 
 Core Architecture Team
 
 , contributing to the design and implementation of a modern Digital Engineering Enterprise Platform.
 
 
 The platform consists of services and applications that accelerate software delivery by providing engineering teams with reusable technologies, standardized development practices, compliance controls, and operational capabilities across more than 700 enterprise applications.
 
 
 
 
 
 
 Responsibilities
 
 
 <ul>
 <li>
 Design, develop, and maintain enterprise-grade multi-agent AI applications using Python, LangGraph, and LangChain.
 </li>
 <li>
 Build scalable agent workflows leveraging AWS Bedrock AgentCore Runtime.
 </li>
 <li>
 Implement advanced orchestration patterns, including supervisor/worker, fan-out/fan-in, and collaborative multi-agent architectures.
 </li>
 <li>
 Design stateful workflow execution using LangGraph checkpointing, recovery, and persistence mechanisms.
 </li>
 <li>
 Develop resilient, fault-tolerant, and idempotent execution strategies for long-running AI workflows.
 </li>
 <li>
 Integrate Human-in-the-Loop (HITL) approval processes into business-critical agent workflows.
 </li>
 <li>
 Enable agent delegation and collaboration through Agent Gateway and Agent-to-Agent (A2A) communication.
 </li>
 <li>
 Implement memory, context management, and persistence strategies for AI agents.
 </li>
 <li>
 Optimize workflow scalability, reliability, observability, and performance within distributed cloud environments.
 </li>
 <li>
 Collaborate with platform, security, DevOps, and product teams to deliver production-ready AI solutions.
 </li>
 <li>
 Define engineering standards, testing strategies, and operational best practices for agent-based applications.
 </li>
 <li>
 Support deployment, monitoring, troubleshooting, and continuous improvement of AI solutions running on AWS.
 </li>
 </ul>
 
 
 Requirements
 
 
 <ul>
 <li>
 Bachelor's degree in computer science, Software Engineering, or a related field.
 </li>
 <li>
 5+ years of professional Python software engineering experience.
 </li>
 <li>
 Hands-on experience building multi-step agent workflows with LangGraph.
 </li>
 <li>
 Strong experience with LangChain.
 </li>
 <li>
 Experience with AWS Bedrock AgentCore Runtime.
 </li>
 <li>
 Solid understanding of multi-agent orchestration patterns, including supervisor/worker and fan-out/fan-in architectures.
 </li>
 <li>
 Experience implementing LangGraph checkpointing and state management.
 </li>
 <li>
 Knowledge of Human-in-the-Loop (HITL) workflow design.
 </li>
 <li>
 Experience with Agent-to-Agent (A2A) delegation through Agent Gateway.
 </li>
 <li>
 Experience with workflow orchestration platforms such as Temporal, Apache Airflow, or similar.
 </li>
 <li>
 Strong understanding of distributed systems concepts, including checkpointing, idempotency, fault tolerance, and workflow recovery.
 </li>
 <li>
 Experience building scalable, cloud-native applications on AWS.
 </li>
 <li>
 Strong problem-solving, communication, and collaboration skills.
 </li>
 </ul>
 
 
 
 
 
 Nice to Have
 
 
 <ul>
 <li>
 Experience evaluating AWS AgentCore Runtime maturity and enterprise adoption.
 </li>
 <li>
 Hands-on experience with AWS Bedrock Memory API.
 </li>
 <li>
 Experience integrating enterprise approval workflows into Human-in-the-Loop AI systems.
 </li>
 <li>
 Experience with AI observability, monitoring, and production operations.
 </li>
 <li>
 Familiarity with CI/CD pipelines and Infrastructure as Code in AWS environments.
 </li>
 </ul>
 
 
 
 
 
 Why Join Us
 
 
 <ul>
 <li>
 Work on enterprise-scale AI initiatives for a global industry leader.
 </li>
 <li>
 Design and build next-generation multi-agent AI systems using cutting-edge AWS technologies.
 </li>
 <li>
 Influence architecture decisions and engineering best practices across large-scale platforms.
 </li>
 <li>
 Collaborate with highly experienced architecture and engineering teams on innovative cloud-native solutions.
 </li>
 <li>
 Opportunity to shape the future of enterprise AI orchestration in production environments.
 </li>
 </ul>
 
 
 
</div>

Senior Python Engineer – Multi-Agent AI (AWS, LangGraph)

<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)

Sana Commerce

<div>
 
 What started in 2007 with a pizza and a plan has grown into a fast-moving SaaS company empowering manufacturers, distributors, and wholesalers to thrive in complex B2B commerce.
 
 
 
 
 Our mission is simple: help businesses build stronger relationships through seamless digital commerce.
 
 
 
 
 At Sana Commerce, you&rsquo;ll join a team that&rsquo;s bold, growth-oriented, and customer-obsessed, where every engineer has real ownership and impact.
 
 
 
 
 We are looking for a
 
 Senior Data Engineer
 
 to design, build, and optimize our
 
 Azure and Databricks-based data infrastructure
 
 . You will play a critical role in developing scalable
 
 ETL pipelines, data ingestion frameworks, and
 
 
 contribute to
 
 
 AI/ML-powered solutions
 
 that drive internal decision-making and customer-facing insights.
 
 
 
 
 This is a hands-on role that requires expertise in
 
 Azure Data Services, Databricks, and Python/SQL
 
 . You will work closely with
 
 Data Architects, Engineers, and Product teams
 
 to develop robust data solutions that power
 
 analytics, personalization, and AI-driven customer experiences
 
 .
 
 
 
 
 
 
 Job Description
 
 
 
 
 
 Data Pipeline Development &amp; Infrastructure
 
 
 
 
 <ul>
 <li>
 Design, build, and maintain
 
 scalable data pipelines
 
 </li>
 <li>
 Develop
 
 real-time and batch data processing
 
 frameworks for structured and unstructured data.
 </li>
 <li>
 Implement
 
 ETL/ELT workflows
 
 to ingest data from various sources, ensuring
 
 high availability and performance
 
 .
 </li>
 <li>
 Optimize
 
 data storage and retrieval
 
 of data in (near) real time and batch processes
 </li>
 <li>
 Ensure
 
 cost-efficient
 
 and
 
 high-performance
 
 data infrastructure that scales with business needs.
 </li>
 </ul>
 
 
 Data Solutions &amp; AI-Driven Applications
 
 
 
 
 <ul>
 <li>
 develop data pipelines for
 
 ML recommenders, search functionality, and AI-enhanced features
 
 .
 </li>
 <li>
 Develop and maintain
 
 data models, APIs, and integrations
 
 to support analytics and customer applications.
 </li>
 <li>
 Support
 
 eCommerce-related data solutions
 
 , including product recommendations, customer segmentation, and personalization models.
 </li>
 </ul>
 
 
 Collaboration &amp; Continuous Improvement
 
 
 
 
 <ul>
 <li>
 Work closely with
 
 Data Architects, Analysts, and Product Teams
 
 to understand data requirements and deliver best-in-class solutions.
 </li>
 <li>
 Monitor and troubleshoot
 
 performance issues
 
 , ensuring high availability and efficiency of data pipelines.
 </li>
 <li>
 Continuously optimize
 
 cost, performance, and scalability
 
 of data engineering solutions.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 6+ years of experience as a
 
 Data Engineer
 
 , working with
 
 Azure and Databricks
 
 </li>
 <li>
 Strong expertise in
 
 data pipeline development, ETL workflows, and real-time/batch data processing
 
 .
 </li>
 <li>
 Experience in
 
 big data technologies, and large-scale data storage
 
 .
 </li>
 <li>
 Familiarity with
 
 data governance, security, and compliance best practices
 
 and
 
 tools
 
 </li>
 <li>
 Proficiency in
 
 Python,
 
 
 and
 
 
 SQL,
 
 for data transformation, data quality and automation.
 </li>
 <li>
 Strong experience in
 
 optimizing data performance and cost-efficiency in cloud environments
 
 .
 </li>
 </ul>
 
 
 Nice to Have
 
 
 
 
 <ul>
 <li>
 Experience with
 
 eCommerce data solutions
 
 , such as customer segmentation, recommendation engines, and personalization models.
 </li>
 <li>
 Knowledge of
 
 event-driven architectures, streaming data processing, and real-time analytics
 
 .
 </li>
 <li>
 Familiarity with
 
 LLM-based AI applications and OpenAI
 
 
 or similar
 
 
 APIs
 
 .
 </li>
 </ul>
 
 
 Why you&rsquo;ll love working here
 
 
 
 
 <ul>
 <li>
 Impact from day one &ndash; Join a scale-up where your ideas shape how global businesses operate online.
 </li>
 <li>
 Continuous learning &ndash; Access a structured onboarding rated 9.1/10 by previous hires, mentorship, and feedback culture.
 </li>
 <li>
 Hybrid flexibility &ndash; Work from our office in Alexandria 3 days per week and from home 2 days.
 </li>
 <li>
 Career growth &ndash; Expand your technical and leadership scope in a company built for long-term success.
 </li>
 </ul>
 
 
 Our values
 
 
 
 
 
 At Sana Commerce, our values drive everything we do:
 
 
 
 <ul>
 <li>
 Champions of Our League &ndash;
 
 We deliver lasting success, balancing quick wins and long-term value
 
 </li>
 <li>
 Supercharge Our Customers &ndash;
 
 We&rsquo;re revolutionizing B2B commerce together, helping our customers to lead and succeed.
 
 </li>
 <li>
 Determined to Grow &ndash;
 
 We embrace challenges, growing and raising the bar for ourselves and our industry.
 
 </li>
 <li>
 Bold Together &ndash;
 
 We dare to be bold because we have each other&rsquo;s back.
 
 </li>
 </ul>
 
 
 Ready to build reliability that scales?
 
 
 
 
 
 Apply now and help shape the foundation of our next-generation SaaS platform.
 
 
 
 
 
 
 Additional Information
 
 
 
 
 
 
 
 
 
 
 
</div>

Senior Data Engineer - Alexandria

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>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Deploy and maintain secure cloud infrastructure primarily on GCP (Google Cloud Platform) and AWS, ensuring seamless integration between services.
 </li>
 <li>
 Manage and optimize GKE (Google Kubernetes Engine) clusters for high-availability AI applications and microservices.
 </li>
 <li>
 Infrastructure as Code: Build and enforce Terraform strategies to provision and manage infrastructure, ensuring environments are reproducible and version-controlled.
 </li>
 <li>
 CI/CD &amp; Software Verification: Design and implement advanced CI/CD workflows using GitHub Actions, moving beyond simple deployments to create intelligent automation.
 </li>
 <li>
 Build robust verification pipelines that include automated testing, linting, security scanning, and quality gates before production release.
 </li>
 <li>
 Streamline the release process for backend and frontend applications, ensuring "one-click" reliability.
 </li>
 <li>
 Oversee the deployment, maintenance, and backup strategies for databases.
 </li>
 <li>
 Implement comprehensive monitoring and logging solutions (Prometheus, Grafana, Cloud Ops, Cloud Monitoring) to ensure system health, performance, and rapid incident response.
 </li>
 <li>
 Implement security best practices (IAM, VPC configuration, encryption) to protect sensitive AI data and intellectual property.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 
 Education &amp; Experience
 
 
 
 
 <ul>
 <li>
 B.Sc. or M.Sc. in Computer Science, Computer Engineering, or a related technical field.
 </li>
 <li>
 5+ years of relevant experience in DevOps, Cloud Engineering, or Site Reliability Engineering (SRE).
 </li>
 <li>
 Proven experience acting as a Senior or Lead engineer, guiding architectural decisions.
 
 
 </li>
 </ul>
 
 
 Technical Requirements
 
 
 
 
 <ul>
 <li>
 Advanced hands-on experience with GCP (specifically GKE, VPC, IAM) and a working knowledge of AWS.
 </li>
 <li>
 Proven ability to design and implement robust, scalable, and secure cloud architectures.
 </li>
 <li>
 Mastery of Docker and Kubernetes administration.
 </li>
 <li>
 Strong proficiency in Terraform.
 </li>
 <li>
 Expert knowledge of GitHub Actions for building, test, build, and deploy pipelines.
 </li>
 <li>
 Experience managing PostgreSQL and ClickHouse databases.
 </li>
 <li>
 Deep understanding of Linux System Administration.
 </li>
 <li>
 Experience with AI/ML lifecycle tools (e.g., Kubeflow, MLflow, Vertex AI).
 </li>
 <li>
 Strong proficiency in Python and Bash scripting.
 </li>
 <li>
 Familiarity with DevSecOps tools and practices.
 </li>
 <li>
 Bonus: Official GCP Certifications (e.g., Professional Cloud Architect, Professional Cloud DevOps Engineer) and Kubernetes Certifications (e.g., CKA, CKAD, CKS) are highly preferred.
 </li>
 <li>
 Bonus: Knowledge of Javascript/Node.js is a strong plus.
 
 
 </li>
 </ul>
 
 
 Soft Skills &amp; Mindset
 
 
 
 
 <ul>
 <li>
 Ability to design long-term solutions rather than quick fixes.
 </li>
 <li>
 Excellent ability to explain complex cloud concepts to Data Scientists and business stakeholders.
 </li>
 <li>
 Comfortable working in a fast-paced environment with evolving requirements.
 </li>
 <li>
 Fluent English is a must.
 </li>
 </ul>
</div>

Senior DevOps Engineer, AI4ALL

Lua AI (YC F25)

<div>
 
 Location: Cairo, Egypt (remote / hybrid) &middot; Reports to: Head of Operations - MENA
 
 
 &nbsp;
 
 
 
 About Lua
 
 
 
 Lua is the Agent OS. We build digital employees &mdash; agents that do a real job end to end: they read a company&rsquo;s own systems, make the decision, take the action, and get a little better every time they run. Not chatbots that answer questions &mdash; digital workers that do the work, on the company&rsquo;s own data and workflows, and everything they build stays owned by the business. Teams write their logic on Lua (agents, skills, tools, jobs, webhooks, guardrails) and we run the hard parts underneath: infrastructure, multi-provider model orchestration, data, channels (WhatsApp, Slack, Email, Instagram, Messenger, a voice-capable website widget, HTTP API) and monitoring.
 
 
 Our customers are the companies that run their markets &mdash; the operator of one of the world&rsquo;s most-visited heritage sites, a major travel-and-hospitality group, the largest supermarket chain in its country, a listed conglomerate spanning healthcare and consumer goods, large regional banks, social-commerce companies and a microinsurer covering over a million people &mdash; across Africa, the Middle East and South Asia. Together they employ 64,000+ people and turn over $5bn+ a year, and they all want the same thing: to be AI-native on the systems they already run, with nothing to rip out. Backed by Y Combinator, we&rsquo;ve raised $5.8M &mdash; and this is a chance to build the playbook, not inherit one.
 
 
 
 
 
 
 Responsibilities
 
 
 
 We&rsquo;re looking for a junior engineer to join the implementation team and help build and deploy AI agents for our mid-market customers. You&rsquo;ll work alongside a senior implementation engineer, learning the Lua platform and contributing to live customer projects from your first week.
 
 
 This is an apprentice-track role with a clear growth path. You&rsquo;ll start with structured work &mdash; environment setup, testing, knowledge base configuration &mdash; and grow into owning full implementations within 6 months.
 
 <ul>
 <li>
 
 Build agent skills and tools
 
 in TypeScript using the Lua CLI &mdash; the functions that let agents take real actions like API calls, data lookups, and webhook triggers.
 </li>
 <li>
 
 Set up and configure agent environments
 
 : sandbox for development, production for live deployments.
 </li>
 <li>
 
 Configure and manage client knowledge bases
 
 &mdash; the information agents use to answer questions and follow business rules.
 </li>
 <li>
 
 Run QA
 
 and testing cycles before deployment &mdash; test across channels (WhatsApp, web, Slack) and flag issues.
 </li>
 <li>
 Support the senior engineer on active implementations across the full build lifecycle.
 </li>
 <li>
 Write and maintain technical documentation for each implementation.
 </li>
 </ul>
 
 
 
 
 
 Requirements
 
 
 <ul>
 <li>
 
 1&ndash;2 years writing code
 
 &mdash; professional experience, bootcamp, side projects, or university projects. You need to be comfortable in TypeScript or JavaScript.
 </li>
 <li>
 
 Familiarity with REST APIs, JSON, and basic web architecture.
 
 You know what an endpoint is and how to test with Postman or similar.
 </li>
 <li>
 A fast learner who figures things out by doing, not by waiting for instructions. The platform, CLI, and agent architecture will all be new.
 </li>
 <li>
 Strong written communication &mdash; you&rsquo;ll be in Slack daily, writing updates, flagging blockers, and documenting your work.
 </li>
 <li>
 Reliable. When you say something is done and tested, it needs to actually be done and tested.
 </li>
 <li>
 Fluent in Arabic and English
 </li>
 </ul>
 
 
 
 
 Nice to have
 
 <ul>
 <li>
 Experience with any chatbot or conversational AI platform.
 </li>
 <li>
 Familiarity with WhatsApp Business API, Slack API, or similar messaging platforms.
 </li>
 <li>
 Comfortable with Git, GitHub, and CLI tooling.
 </li>
 <li>
 Previous remote work experience.
 </li>
 </ul>
 
 
 
 
 
 Growth Path
 
 
 <ul>
 <li>
 
 Months 1&ndash;3:
 
 Support builds, learn the platform, follow the runbook, handle structured work.
 </li>
 <li>
 
 Months 3&ndash;6:
 
 Own specific integrations within an implementation. Run client test sessions.
 </li>
 <li>
 
 Months 6&ndash;12:
 
 Own an implementation end-to-end. Client-facing. Responsible for time-to-value on your accounts.
 </li>
 </ul>
 
 
 
 
 
 What we offer
 
 
 <ul>
 <li>
 Hybrid - Most of our work is remote.
 </li>
 <li>
 Small team, massive ownership. No bureaucracy. Ship and iterate.
 </li>
 <li>
 Direct access to the founding team. Your work is visible and impactful from day one.
 </li>
 <li>
 A platform that&rsquo;s actually in production with real customers &mdash; not a pre-product startup.
 </li>
 </ul>
 
 
 
</div>

Junior Implementation Engineer, MENA

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