ai engineering manager

Etisalat

<div><div>AI Engineering &amp; Innovation Manager.Customer and Partner Management - (260000V2)</div><div>
Description<div></div> 
Job Purpose
To lead the AI Engineering &amp; Innovation function, with primary focus on AI Development, AI/ML Engineering, Generative AI, and Agentic AI solutions, supported by strong background in platform engineering and full-stack architecture. Responsible for delivering cutting-edge AI solutions, including AI Agents, Agentic Automation, OCR, Chatbots, Conversational AI, Speech-to-Text, Text-to-Speech, Voicebots, and local LLM deployments&mdash;while ensuring solutions are scalable, secure, production-ready, and aligned with enterprise architecture standards. The role drives end-to-end innovation, from lean experimentation and proof-of-concepts to enterprise-scale deployment, ensuring AI solutions are aligned with business strategy, customer experience goals, and market-leading practices.

Report To Position Name
Leadership &amp; Strategy Lead and manage a team of AI Development Engineers, AI/ML Engineers, AI Agent Engineers, and AI Support Engineers. Define AI Engineering and Innovation roadmap aligned with corporate digital transformation strategy. Evaluate emerging AI technologies (LLMs, local LLMs, RAG, AI agents, agent frameworks, vector databases, orchestration layers, and autonomous workflows) and introduce new capabilities. Drive adoption of AI to enhance customer care, CVM, digital channels, enterprise services, and internal efficiency. Establish standards for reusable AI components, agent design, governance, and scalable enterprise AI adoption. AI Development Oversee design and development of AI/ML models, Generative AI applications, reusable AI agents, and agentic workflows for OCR, NLP, Chatbots, Conversational AI, and automation use cases. Guide teams in model training, fine-tuning, prompt engineering, evaluation, deployment, and agent orchestration. Lead deployment and optimization of local / on-prem LLM models, including model serving, inference optimization, GPU utilization, and continuous tuning. Drive integration of speech-to-text, text-to-speech, voicebot, and voice persona capabilities into customer-facing and enterprise applications. Ensure compliance with data governance, model governance, ethical AI use, and responsible AI principles. Design modular, reusable, and scalable AI agents with governance controls and shared services. AI Platforms Engineering Provide architectural oversight leveraging strong platform engineering and full-stack development background(Java, Spring Boot, Node.js, Angular). Ensure robust solution architecture using microservices, containerization, Docker, Kubernetes / OpenShift, Amazon EKS orchestration, APIs, and CI/CD pipelines. Lead production deployment and go-live readiness with full focus on security controls, vulnerability management, secure coding practices, and infrastructure hardening. Integrate AI solutions with enterprise platforms, core systems, vector stores, tool layers, and backend services. Oversee performance, scalability, resilience, and production readiness of AI applications and services. Innovation, Proof-of-Concepts &amp; Productization Lead innovation lifecycle: identify opportunities, run lean experiments, build PoCs, validate impact, and scale successful use cases to production. Collaborate with business units to co-create AI-powered products, agentic workflows, and automation services. Drive rapid experimentation cycles with measurable business impact and customer value. Ensure accelerated time-to-value and time-to-market for AI solutions while maintaining quality and security. Operations &amp; AIOps Ensure operational readiness of deployed AI applications through AIOps, MLOps, and LLMOps monitoring and automation. Oversee incident resolution, model monitoring, change management, and continuous improvement. Maintain SLAs and service reliability for critical AI-enabled business applications. Ensure continuous security patching, vulnerability remediation, and model/runtime lifecycle management.<div> 
</div></div><div>
Qualifications<div></div> 
QUALIFICATIONS_ESSENTIAL
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, AI, or related field 
QUALIFICATIONS_DESIRABLE
Innovation Drive adoption of next-gen AI architectures (Agentic orchestration, vector databases, RAG pipelines). Lead experimentation with new AI platforms and integration models. Skills &amp; Abilities Strong leadership, people management, and cross-functional collaboration. Excellent communication, presentation, and stakeholder engagement skills. Ability to manage multiple parallel projects and deliver under pressure. 

EXPERIENCE_ESSENTIAL
8+ years of experience in AI/ML engineering and software development. At least 3&ndash;5 years in a leadership/managerial role overseeing AI development teams 
EXPERIENCE_DESIRABLE
Strong knowledge of AI/ML technologies (Machine Learning, NLP, Generative AI, Agentic AI, Conversational AI, OCR, autonomous workflows). Proven experience in AI development, reusable agent design, and scalable AI solution engineering. Strong hands-on familiarity with cloud platforms and their AI portfolios, including AWS (Bedrock, SageMaker), Microsoft Azure AI services, and Google Cloud Vertex AI / GenAI services. Solid background in platform engineering, full-stack architecture, microservices, containerization, APIs, and orchestration platforms such as Docker, OpenShift, and EKS. Proven go-live deployment experience with strong focus on security, vulnerability management, and production hardening. Experience in deploying and managing local / on-prem LLM models and inference environments. Familiarity with speech technologies (speech-to-text, text-to-speech, voicebots, voice persona solutions). Deep understanding of cloud, DevOps, MLOps, LLMOps, governance, and observability tools. Strong knowledge of lean experimentation methodologies with impact-driven delivery. Knowledge of telecom, customer care, CVM, sales, and enterprise domains is a plus. 

CERTIFICATIONS_ESSENTIAL
N/A<div> 
</div></div><div>
Job: Manager</div><div>
Organization: Etisalat-Misr</div><div>
Job Posting: 06/May/2026, 6:51:31 AM</div></div>

AI Engineering & Innovation Manager.Customer and Partner Management

World Wide Technology

<div><div>Required Qualifications
<ul>
<li>Strong background in software engineering and system architecture, with experience leading complex, distributed platforms.</li>
<li>Demonstrated experience building AI native applications, including LLM integration, automation workflows, or intelligent agents.</li>
<li>Experience leading or scaling small engineering teams, including hiring, onboarding, and technical mentorship.</li>
<li>Proficiency with modern web and backend technologies (e.g., JavaScript/TypeScript, Node.js, APIs, event-driven systems, cloud platforms).</li>
<li>Experience designing and operating automation platforms or workflow-driven systems at scale.</li>
<li>Strong understanding of data flows, integrations, and platform interoperability.</li>
<li>Ability to think in terms of products and platforms, not just projects.</li>
<li>Comfort operating in ambiguity and driving technical clarity where requirements are evolving.</li>
<li>Excellent communication skills with the ability to explain complex technical concepts to non‑technical audiences.</li>
<li>Solid understanding of Agile and iterative delivery models.</li>
<li>Deep alignment with and commitment to the WWT Core Values.</li>
<li>Bachelor's degree in Computer Science, Engineering, or a related field preferred; equivalent experience will be considered.</li> 
</ul>
Certain states and localities require employers to post a reasonable estimate of the salary range. A reasonable estimate of the current base pay range for this position is $140,400 to $175,000 annually. Actual salary will be based on a variety of factors, including shift, location, experience, skill set, performance, licensure and certification, and business needs. The range for this position in other geographic locations may differ. Certain positions may also be eligible for variable incentive compensation, such as bonuses or commissions, that are not included in the base pay. 
 
</div>The well-being of WWT employees is essential. So, when it comes to our benefits package, WWT has one of the best. We offer the following benefits to all full-time employees:
<ul>
<li>Health and Wellbeing: Health, Dental, and Vision Care, Onsite Health Centers, Employee Assistance Program, Wellness program</li>
<li>Financial Benefits: Competitive pay, Profit Sharing, 401k Plan with Company Matching, Life and Disability Insurance, Tuition Reimbursement</li>
<li>Paid Time Off: PTO and Sick Leave (starting at 20 days per year) &amp; Holidays (10 per year), Parental Leave, Military Leave, Bereavement</li>
<li>Additional Perks: Nursing Mothers Benefits, Voluntary Legal, Pet Insurance, Employee Discount Program</li>
</ul>
We strive to create an environment where all employees are empowered to succeed based on their skills, performance, and dedication. Our goal is to cultivate a culture of belonging that encourages innovation, collaboration, and respect for all team members, ensuring that WWT remains a great place to work for All!

If you have any questions or concerns about this posting, please email taposting@wwt.com.
<div>
#LI-MP1</div>

Requirements:
Why WWT?

At World Wide Technology, we work together to make a new world happen. Our important work benefits our clients and partners as much as it does our people and communities across the globe. WWT is dedicated to achieving its mission of creating a profitable growth company that is also a Great Place to Work for All. We achieve this through our world-class culture, generous benefits, and by delivering cutting-edge technology solutions for our clients.
Founded in 1990, WWT is a global technology solutions provider leading the AI and Digital Revolution. WWT combines the power of strategy, execution, and partnership to accelerate digital transformational outcomes for organizations around the globe. Through its Advanced Technology Center, a collaborative ecosystem of the world's most advanced hardware and software solutions, WWT helps clients and partners conceptualize, test, and validate innovative technology solutions for the best business outcomes and then deploys them at scale through its global warehousing, distribution, and integration capabilities.
With over 12,000 employees across WWT and Softchoice and more than 60 locations around the world, WWT's culture, built on a set of core values and established leadership philosophies, has been recognized 14 years in a row by Fortune and Great Place to Work&reg; for its unique blend of determination, innovation, and creating a great place to work for all.

What is the Internal WWT IT Team, and why join?
The Internal WWT IT team is the backbone of our company's technological infrastructure, ensuring seamless operations and continuous innovation. Our team is dedicated to managing and supporting the company's technology infrastructure, ensuring the smooth operation of hardware, software, networks, and data systems, while providing top-notch technical support to employees.
By joining the Internal WWT IT team, you will play a crucial role in maintaining the efficiency and security of our IT environment, enabling the company to achieve its strategic goals. The Internal IT team offers the opportunity to work in a dynamic and collaborative environment, where your contributions will have a direct impact on the company's success. If you are passionate about technology and eager to take on new challenges, we encourage you to apply and join our team.
What will you be doing?

As a Senior Engineering Manager - Marketing Technology, you will own the technical strategy and execution of WWT's marketing automation and AI capabilities. This role is responsible for designing and building the platforms that power internet and email campaign automation, AI driven‑ content systems, and the next generation of marketing technology at WWT.

You will operate as a hands-on technical leader setting architecture, making build vs. buy decisions, and staffing a small team of engineers to deliver scalable, AI native solutions. While you will partner closely with Marketing and Digital stakeholders, this role is firmly rooted in engineering excellence, platform thinking, and modern AI‑ driven‑ system design. 
 
Responsibilities
<ul>
<li>Define and own the technical architecture for marketing automation, AI enhancements, and MarTech modernization.</li>
<li>Lead and grow a small, high performing‑ team of software engineers focused on automation, AI workflows, and platform development.</li>
<li>Design and deliver systems for internet and email campaign automation, including orchestration, personalization, experimentation, and analytics integration.</li>
<li>Build and modernize AI enabled‑ content platforms, including content generation, enrichment, tagging, governance, and lifecycle automation.</li>
<li>Apply AI native engineering patterns (LLM integration, agents, retrieval, workflow automation) to marketing use cases.</li>
<li>Partner with Marketing, Digital, Analytics, and IT leaders to translate business goals into scalable technical solutions.</li>
<li>Evaluate and integrate third-party platforms and APIs while minimizing vendor ‑lock in‑ and technical debt.</li>
<li>Establish engineering best practices for reliability, security, observability, and maintainability.</li>
<li>Balance speed of delivery with platform quality, governance, and long-term‑ scalability.</li>
<li>Communicate technical strategy, tradeoffs, and outcomes clearly to senior leaders and non‑technical stakeholders.</li>
<li>Coach, mentor, and develop engineers through clear expectations, feedback, and servant leadership.</li></ul></div>

Senior Engineering Manager - Marketing Technology

Hex Technologies

SF or NYC
 
About the role: 
Come define the future of AI Engineering at the company building the world’s leading agentic data science and analytics platform. As our AI Engineering Lead, you will accelerate the product and company by leveraging frontier AI technology and techniques, collaborating closely with product and engineering, and building and developing a world-class team of AI Engineers.
 
What you will do: 
Stay up-to-date on the latest in AI technology and work with engineering teams to push the frontier of product capabilities
 Define and implement the future of the AI Engineering function at Hex as we scale
 Hire and mentor an exceptional team of AI Engineers
 Support an exceptional developer and research experience for teams working with AI technology
 Deliver high-performing shared AI infrastructure, including search systems
 
About You: 
You have 4+ years of people management experience and leading high-performing teams
 You have deep familiarity with modern AI technology as well as classical ML systems and a passion for sharing that with others. Technologies of particular interest include LLMs and transformer models, agentic workflows, context management, and agentic evals.
 You are obsessed with driving business outcomes and delivering value to customers
 You are rigorous but pragmatic, balancing good experimental design with early-stage agility
 You are a strong communicator and love collaborating with other roles and teams to drive outcomes
 You are a talent magnet, with the ability to attract and retain exceptional AI talent
 Our stack
 
Our product is a web-based notebook and app authoring platform. Our frontend is built with Typescript and React, using a combination of Apollo GraphQL and Redux for managing application state and data. On the backend, we also use Typescript to power an Express/Apollo GraphQL server that interacts with Postgres, Redis, and Kubernetes to manage our database and Python kernels. Our backend is tightly integrated with our infrastructure and CI/CD, where we use a combination of Terraform, Helm, and AWS to deploy and maintain our stack.
 
This is a full-time role based out of either our San Francisco or New York office. Employees are encouraged to come into the office at least twice a week, with Tuesdays and Thursdays being our main in-person days.
 
In addition to our unique culture, Hex proudly offers a competitive total rewards package, including but not limited to, market-benched salary & equity, comprehensive health benefits, and flexible paid time off.
 
The salary range for this role is: $246,000 - $329,000
 
The salary range shown may be a reflection of additional factors such as geographical location and skill ranges/levels we’re open to. Placement in the salary range will be decided upon completion of the interview process, taking into account factors like leaving room for growth, internal fairness & parity, your demonstrated skills, and the depth of your experience. Our Recruiting team will be able to provide more details during the interview process.
 
By submitting an application the candidate consents to the use of their personal information in accordance with the Hex Privacy policy: https://learn.hex.tech/docs/trust/privacy-policy.
 
About Hex
 
Hex is growing our team of builders on a mission to make everyone a data person. Our platform solves key pain points with today's data and analytics tooling, and empowers anyone to explore data using natural language, with or without code, on trusted context. Thousands of customers like Ramp, Figma, Stubhub, Anthropic, and Gamma love Hex for our beautiful UI, agentic superpowers, and boundless flexibility.
 
Hex has raised over $100M from leading investors like Sequoia, a16z, Snowflake and Amplify. With office hubs in San Francisco and New York, as well as remote team members throughout the US and UK, we're a high-agency team that ships fast and has fun doing it. Check out our Intro to Hex video and employee handbook to learn more about what it's like to work at Hex.

AI Engineering Lead

York Towers

<div>
 York Towers is the development arm of the York Holding Group. Through continuous research and the ability to predict emerging trends, the company keeps an edge over the market. Playing a leading role in driving the successful development and diversification of one of the most vital economic sectors, York Towers is committed to creating residential products across the country that provide residents with distinctive, universal, multicultural, and enriching lifestyles. York Towers is the exclusive developer of luxury real estate worldwide. The company aims to become a leading real estate player through an efficient business model and advanced technologies used for designing and construction. Since its establishment in 2016, York Towers has delivered 20 real estate properties and runs six dynamic projects. York Towers operates eight offices in five countries across three continents.
 
 
 About Dwelleo
 
 
 
 
 Dwelleo is an AI-powered real estate marketplace transforming how people search, buy, sell, and rent properties across Saudi Arabia.
 
 
 
 
 The platform combines machine learning, intelligent discovery tools, and data-driven insights to connect buyers, renters, brokers, and developers through a seamless, scalable digital experience.
 
 
 
 
 At its core, Dwelleo embeds AI directly into the product &mdash; powering pricing, recommendations, search, and decision-making across the entire property journey.
 
 
 
 
 
 
 
 Job summary:
 
 
 
 
 
 
 As AI Lead, you will own both our ML and LLM workstreams: defining the technical architecture, governing production systems, and leading the team that ships them. This is a hands-on leadership position &mdash; you are expected to be close to the technical decisions, not just the roadmap.
 
 
 
 
 The immediate scope spans two areas: maturing our ML platform (pricing, forecasting, drift monitoring) and scaling our agentic AI systems into robust, production-grade infrastructure.
 
 
 
 
 You will lead a team of 3&ndash;7 engineers, staying hands-on technically while owning delivery, standards, and team growth.
 
 
 
 
 &nbsp;
 
 
 
 
 Main Functions &amp; Responsibilities:
 
 
 
 
 
 ●&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 
 Own the full ML lifecycle &mdash; feature engineering, training, evaluation, deployment, and drift monitoring for pricing, rent, and ROI prediction models
 
 
 
 
 ●&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Define the experimentation framework &mdash; data contracts, labelling strategies, A/B testing pipelines, guardrail metrics, and rollback procedures
 
 
 
 
 ●&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Architect production agentic systems &mdash; design LLM-based multi-agent workflows with deterministic state machines, guardrail layers, and escalation logic
 
 
 
 
 &nbsp;●&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Lead infrastructure and platform decisions &mdash; FastAPI microservices on AWS ECS, model serving, CI/CD (GitHub Actions + MLflow), and end-to-end observability
 
 
 
 
 ●&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Drive research and evaluation &mdash; assess new approaches across supervised learning, NLP, and agentic AI; decide what gets built, what gets dropped, and why
 
 
 
 
 ●&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Lead a team of 3&ndash;7 engineers &mdash; set engineering standards, conduct code and design reviews, mentor team members, and participate in hiring as the technical voice
 
 
 
 &nbsp;
 
 
 
 Qualifications &amp; Requirements:
 
 
 
 
 Required
 
 
 
 
 ●&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;6+ years of ML engineering experience, with at least 3 years in a technical lead or senior individual contributor role
 
 
 
 
 ●&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Production-scale ML: supervised learning, gradient boosting (XGBoost / LightGBM), regression, feature engineering, and model evaluation
 
 
 
 
 ●&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Solid MLOps practice: experiment tracking, model registry, canary deployments, drift detection, and incident response
 
 
 
 
 ●&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;2+ years working with LLM orchestration, RAG architectures, or multi-agent system design
 
 
 
 
 ●&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Demonstrated experience leading a team of engineers &mdash; including hiring, mentoring, setting technical direction, and translating AI capabilities into product outcomes
 
 
 
 &nbsp;
 
 
 
 Skills:
 
 
 
 
 
 
 ●&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Leadership &ndash; guide and support the team to achieve goals
 
 
 
 
 ●&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Clear communication &ndash; align technical and business teams
 
 
 
 
 ●&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Decision-making &ndash; choose the right solutions and priorities
 
 
 
 
 ●&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Teamwork &ndash; build a collaborative and positive team environment
 
 
 
 
 ●&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Problem-solving &ndash; handle challenges and unblock the team
 
 
 
 
 ●&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Strategic thinking &ndash; connect AI work with business goals&nbsp;
 
 
</div>

AI Team Lead

MA'ADEN

<div><div><div><div><div>Role Purpose:
The Data Science &amp; Analytics Manager is responsible for overseeing the end-to-end execution of data science and advanced analytics initiatives that support Maaden&rsquo;s operational and business objectives. The role ensures that data science projects are delivered with high quality, reliability, and measurable impact by managing workflows, coordinating cross-functional stakeholders, and maintaining strong alignment with enterprise data, AI, and governance standards.
As an operational leader, the Manager translates business needs into actionable analytical work, supervises the development of models, analytical products, and data pipelines, and ensures their successful deployment and adoption across functions. This role plays a critical part in embedding data-driven decision-making within production, maintenance, supply chain, engineering, and other business units by enabling teams to access trusted insights, robust analytical tools, and fit-for-purpose ML/AI solutions.
Through effective project management, quality oversight, and close collaboration with technical experts and business partners, the Data Science &amp; Analytics Manager helps accelerate Maaden&rsquo;s transition to a technology-enabled, AI-informed mining enterprise. 
1. Manage End‑to‑End Data Science Delivery
<ul><li>Oversee the development, implementation, and maintenance of databases and data collection systems.
</li><li>Manage the lifecycle of ML/AI initiatives&mdash;supporting problem framing, data exploration, feature engineering, model development, validation, and preparation for MLOps deployment.
</li><li>Ensure delivery of scalable, production‑ready models in alignment with enterprise data governance and AI standards.
</li><li>Conduct statistical analysis to interpret data insights and support decision‑making.
</li><li>Apply data mining techniques to uncover patterns, trends, and relationships in large datasets.
</li><li>Develop predictive models and machine learning algorithms to forecast future outcomes as required.
</li><li>Create clear data visualizations, dashboards, and reports to effectively communicate findings to business stakeholders.
</li><li>Collaborate with cross‑functional teams to understand business needs and translate them into data‑driven solutions.
</li><li>Ensure seamless integration of predictive and optimization models into enterprise platforms, control systems, and digital twins.
</li><li>Stay updated on emerging techniques, tools, and technologies in data science and analytics.
</li><li>Promote experimentation, model versioning, automated retraining, and continuous improvement processes.
</li><li>Recommend enhancements to existing models and analytics workflows for greater efficiency and impact. 
</li></ul></div></div> 
<div><div>2. Data Operations
<ul><li>Partner with data engineering to design, operate, and maintain reliable data pipelines and analytical models, ensuring data accuracy, timeliness, and trustworthiness.
</li><li>Monitor data quality, resolve data issues, and enforce data best practices across teams.
</li><li>Support compliance with data security standards and relevant regulations
</li><li>Supervise the development and deployment of advanced ML models, predictive analytics, GenAI, and optimization solutions, consistent with responsibilities of analytics leadership roles.
</li><li>Ensure technical rigor across the end‑to‑end ML lifecycle: scoping data engineering modeling validation MLOps monitoring.
</li><li>Oversee production reliability, model drift management, and continuous improvement. 
</li></ul></div></div> 
<div><div>3. Team Leadership &amp; Capability Building
<ul><li>Manage and grow a multi‑disciplinary team (Lead Specialists, Senior Specialists, Data Scientists). Roles under this manager are explicitly listed in the org structure.
</li><li>Build technical excellence through coaching on ML, GenAI, statistics, feature engineering, and experimentation.
</li><li>Foster a culture of innovation, peer review, and reusable modeling frameworks. 
</li></ul></div></div> 
<div><div>4. AI Governance, Quality &amp; Standards
<ul><li>Steward high standards in model explainability, auditability, lineage, and risk management.
</li><li>Drive compliance with enterprise data governance, PDPL, and model‑risk principles referenced in internal DS/AI qualification guidance.
</li><li>Ensure adherence to Responsible AI requirements applicable to DS/AI roles (skills and qualifications guidance).
</li><li>Enforce data quality standards, lineage, and reproducibility across the team&rsquo;s projects.
</li><li>Support alignment with enterprise governance frameworks, including PDPL compliance.
</li></ul></div></div> 
</div></div>Minimum Qualifications, Experience and Competencies
Minimum Qualifications:
Bachelor&rsquo;s degree in computer science, Engineering, Data Science, Mathematics, Applied Mathematics, or Physics.
Minimum Experience:
<ul><li>10 &ndash; 12+ years&rsquo; experience in advanced analytics, ML/AI engineering, and industrial data science.
</li><li>Including at least 4 years leading or mentoring analytics professionals.
</li><li>Proven ability to translate business problems into analytic approaches: define hypotheses, design analyses, and synthesize results into clear recommendations.
</li><li>Strong proficiency with modern ML frameworks and cloud platforms (TensorFlow, PyTorch, Azure, AWS).
</li><li>Strong technical fluency with modern analytics stacks, data modeling, SQL, and experience partnering effectively with engineering teams.
</li><li>Strong proficiency with modern ML frameworks and cloud platforms (TensorFlow, PyTorch, Azure, AWS).
</li><li>Proven record of enabling cross-functional business impact through scalable, production-grade data science solutions.
</li></ul>Maaden High-Performance Competencies:
Core Competencies
<ul><li>Value realization from ML/analytics initiatives (impact delivered vs. target).
</li><li>On‑time delivery of analytics roadmap.
</li><li>Adoption rate and integration of solutions into business workflows.
</li><li>Model performance stability (drift incidents, uptime).
</li><li>Team capability maturity and talent development indicators. 
</li></ul>Skills:
<ul><li>Machine Learning &amp; AI Leadership
</li><li>Programming Expertise
</li><li>Generative AI Proficiency
</li><li>Strong Analytical &amp; Statistical Skills
</li><li>Business Strategy &amp; Product Thinking
</li><li>Ethics, Governance &amp; Responsible AI
</li><li>Leadership &amp; People Management</li></ul></div>

Manager, Data Science & Analytics

Globant

<div>
 
 Tech Director (Head of Engineering)
 
 
 Globant &mdash; Riyadh, KSA
 
 
 
 
 Location:
 
 Riyadh, Saudi Arabia (on-site). Alternative locations: Jordan, Lebanon, UAE, Egypt &mdash; with regular travel to Riyadh required.
 
 
 
 Reports to:
 
 VP of Technology
 
 
 
 Direct scope:
 
 50+ engineers across back end and front end disciplines
 
 
 
 Role type:
 
 New role | Permanent | Leadership/Strategy
 
 
 
 About The Role
 
 
 
 This is a senior engineering leadership position responsible for the strategic direction, delivery performance, and technical maturity of Globant's software engineering function in the MENA region. The Head of Engineering will own the engineering roadmap, drive AI adoption, establish engineering culture and standards, and lead a growing organisation of 50+ engineers across back end and front end teams.
 
 
 
 Key Priorities
 
 
 
 <ul>
 <li>
 Improve delivery velocity &mdash; Identify and remove bottlenecks across the engineering lifecycle. Establish metrics, streamline release processes, and improve predictability of delivery across teams.
 </li>
 <li>
 Drive AI adoption across engineering &mdash; Define and execute a strategy for embedding AI into engineering workflows, tooling, and product development. Champion the use of AI-assisted development, testing, and operations to accelerate output and quality.
 </li>
 <li>
 Build engineering culture and processes &mdash; Establish engineering standards, governance, and ways of working. Improve tooling, development processes, and code standards across teams. Create a culture of ownership, technical excellence, and continuous improvement. Introduce career frameworks, knowledge sharing, and communities of practice.
 </li>
 <li>
 Tackle technical debt and platform modernisation &mdash; Assess the current estate, prioritise remediation, and lead modernisation efforts aligned with long-term architectural goals. Balance delivery demands with sustainable engineering practices.
 </li>
 <li>
 Scale the engineering organisation &mdash; Partner with talent acquisition to grow the team in line with business demand. Build a hiring strategy across Riyadh and alternative locations (Jordan, Lebanon, UAE, Egypt), ensuring quality and cultural alignment.
 
 
 
 </li>
 </ul>
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Set the technical vision and engineering strategy aligned with business objectives
 </li>
 <li>
 Lead and develop engineering managers, SMEs, and senior engineers across all disciplines
 </li>
 <li>
 Own engineering delivery performance, reporting, and continuous improvement
 </li>
 <li>
 Collaborate closely with architecture, cybersecurity, product, delivery, design, QA, data, and DevSecOps/platform disciplines to ensure alignment and cohesive outcomes across the engineering organisation
 </li>
 <li>
 Represent engineering in senior leadership forums and client engagements
 </li>
 <li>
 Manage stakeholder relationships across the organisation and with external partners
 </li>
 <li>
 Champion modern engineering practices including DevSecOps, CI/CD, observability, and automation
 </li>
 <li>
 Ensure compliance with security, governance, and regulatory requirements
 
 
 
 </li>
 </ul>
 
 Technical Landscape
 
 
 
 The role provides strategic oversight across the following technology stack. Hands-on coding is not expected, but a strong understanding of the technologies in use and the ability to engage credibly with technical teams is required.
 
 
 
 Back End:
 
 NodeJS, Adobe Experience Manager, Apigee, RESTful APIs, microservices architecture, event-driven architecture, SQL and NoSQL databases, OAuth/JWT, message queuing and async processing.
 
 
 
 Front End:
 
 Flutter, Svelte, HTML5/CSS3/JavaScript/TypeScript, Android and iOS native development, component-based architecture, micro frontend patterns, progressive web applications, accessibility (WCAG), state management.
 
 
 
 AI &amp; Emerging Tech:
 
 AI-assisted development tooling, Agentic AI, LLMOps, AI integration into engineering workflows, evaluation of emerging AI/ML technologies for engineering productivity.
 
 
 
 Requirements
 
 
 
 <ul>
 <li>
 Significant experience leading engineering organisations of 50+ in a Tech/SaaS environment
 </li>
 <li>
 Proven track record of improving delivery velocity and engineering maturity at scale
 </li>
 <li>
 Experience introducing AI tooling and practices into engineering teams
 </li>
 <li>
 Strong understanding of back end and front end technologies &mdash; able to engage credibly with engineering teams and contribute to technical discussions
 </li>
 <li>
 Demonstrated ability to work effectively across disciplines including architecture, cybersecurity, product, delivery, design, and QA
 </li>
 <li>
 Experience building engineering teams across multiple geographies, ideally in the MENA region
 </li>
 <li>
 Strong stakeholder management and communication skills with senior/executive audiences
 </li>
 <li>
 Experience with engineering governance, standards, and platform modernisation
 </li>
 <li>
 Track record of building engineering culture, career frameworks, and communities of practice
 
 
 
 </li>
 </ul>
 
 Desirable
 
 
 
 <ul>
 <li>
 Experience in a consulting or digital services environment
 </li>
 <li>
 Experience working with Saudi Arabia's digital transformation landscape (e.g. Vision 2030 aligned programmes)
 
 </li>
 </ul>
</div>

Tech Director

Apple Federal Credit Union

<div>At Apple Federal Credit Union, we&rsquo;re more than a financial institution; we&rsquo;re a community-focused organization powered by passionate people. With 24 branches across Northern Virginia and a proud legacy of service, we&rsquo;re committed to improving the lives of our members and the communities we serve.
We believe our employees are our greatest asset. That&rsquo;s why we foster a supportive workplace culture that values inclusiveness, innovation and growth. Whether you&rsquo;re just starting out or advancing your career, you&rsquo;ll find opportunities for professional development, mentorship and meaningful impact.
Why Work at Apple FCU<div><ul><li>
Recognized as a USA Top Workplace (2025) and Top Workplace by The Washington Post (2025)</li><li>
Collaborative, welcoming environment with forward-thinking leadership</li><li>
Competitive, comprehensive benefits package, including:<ul><li>
Medical, dental and vision coverage</li><li>
401(k) with employer match</li><li>
Paid time off and 11 paid federal holidays</li><li>
Paid volunteer time to give back</li><li>
Tuition reimbursement and ongoing training opportunities</li><li>
Annual TEAM Bonus plan.</li></ul></li></ul><div><div>
Role:</div><div><div> 
Under the general supervision of the Manager, AI &amp; Data Engineering, and in adherence to established policies and procedures, the AI Solutions Engineer II will be responsible for designing, building, and operationalizing AI-powered solutions that transform how staff discover and consume Apple FCU&rsquo;s enterprise data. This role will serve as a hands-on technical builder who leverages the data platform and curated datasets created by the Data Analytics team to deliver secure, reliable, and scalable AI experiences&mdash;such as internal agents that enable staff to ask natural-language questions and receive accurate, explainable answers grounded in governed data. 
The AI Solutions Engineer will own key technical decisions and implementations required to make AI usable in production, including AI tooling selection and development, integration patterns, Azure compute/runtime considerations, and end-to-end operational supportability (monitoring, logging, error handling, and deployment discipline). The role will partner closely with Data Engineering, Data Analytics leadership, Cybersecurity/IT stakeholders, and business partners to ensure solutions meet business needs while maintaining appropriate governance, privacy, and security controls. 
The candidate will be expected to perform their duties with a mindset that reflects The Apple Way principles: Team Up, Serve with Purpose, Challenge Yourself, and Own It. A keen awareness of and compliance with credit union policies and procedures, as well as regulations pertaining to the Bank Secrecy Act, is imperative. Additionally, the AI Solutions Engineer will undertake other information technology responsibilities as delegated by the Manager, AI &amp; Data Engineering.<div><div> 
Essential Functions &amp; Responsibilities:
Build AI-powered data consumption experiences<ul><li>
Design and implement staff-facing AI experiences that allow non-technical users to ask questions in natural language (e.g., &ldquo;How many members opened accounts yesterday?&rdquo;) and receive accurate, explainable answers grounded in governed enterprise data.</li>
Implement safe &ldquo;natural language<li> analytics&rdquo; workflows (query planning, schema/metadata grounding, semantic definitions, and response formatting) that prioritize correctness, interpretability, and repeatability.</li><li>
Ensure AI outputs include the appropriate context (definitions, time windows, filters used, and confidence/limitations) to reduce misinterpretation and improve trust.</li><li>
Partner with Data Engineering to assess and improve AI-readiness of enterprise datasets, develop metadata, semantic labeling, and data quality standards needed for AI outputs.</li></ul>
Own AI tooling selection, engineering standards, and integrations<ul><li>
Own the technical evaluation, selection, and implementation of AI tooling used to deliver internal AI solutions (model/provider choices, orchestration patterns, retrieval patterns, evaluation harnesses, monitoring/telemetry patterns).</li><li>
Evaluate and develop agentic AI solutions that will assist in everyday organizational processes, build out multi-step workflows that will act on enterprise data with appropriate oversight and traceability.</li><li>
Develop reusable &ldquo;golden path&rdquo; components that the team can consistently apply: prompt templates, retrieval patterns, tool/function calling patterns, safety/guardrail patterns, logging and tracing, and secure data access adapters.</li></ul>
Partner with Data Engineering to define and maintain the interfaces between the AI consumption layer and the governed data platform (Fabric/Warehouse/Lakehouse), ensuring minimal friction for future AI use cases. 
Azure runtime, compute, and operational ownership<ul><li>
Architect and implement the runtime environment for AI services (Azure hosting patterns, identity, secrets, compute scaling, performance tuning, cost controls) to ensure production-grade reliability and supportability.</li><li>
Implement observability and operational discipline for AI solutions: telemetry, auditing, error handling, incident response hooks, and maintainable runbooks.</li><li>
Establish release and change discipline for AI solutions (dev/test/prod separation where applicable, automated deployment patterns, rollback approach).</li></ul>
Governance, security, and responsible AI guardrails<ul><li>
Ensure AI solutions comply with Apple FCU&rsquo;s AI Policy and enterprise security expectations, including data access controls, privacy safeguards, auditability, and human oversight mechanisms.</li></ul>
Partner with stakeholders (Cyber/IT governance) to build out AI governance framework and ensure AI tools do not introduce unacceptable data exposure risk; support third‑party AI assessments as needed (data usage boundaries, retention, model training exclusions, access logging). 
Enablement and adoption (turn capability into usage)<ul><li>
Create practical enablement materials and lightweight training for staff on how to use AI data agents effectively and responsibly (what it can/can&rsquo;t answer, how to phrase questions, how to validate outputs).</li></ul>
Operate as a &ldquo;builder + evangelist&rdquo;: identify adoption blockers, iterate on UX and response quality, and drive measurable increases in self-service usage while reducing manual analyst/engineer lift. 
 
Experience:<ul><li>
5&ndash;8+ years of demonstrated, relevant experience in software engineering, data engineering, platform engineering, and/or applied AI engineering.</li><li>
Strong proficiency in Python (and/or C#) and modern engineering practices (Git, code reviews, testing, CI/CD, observability).</li><li>
Working knowledge of Azure and cloud-native design patterns (secure identity, networking, secrets management, scaling/compute, cost awareness).</li><li>
Strong working knowledge of SQL and data warehousing/lakehouse concepts; ability to safely operationalize natural-language analytics patterns using governed datasets and business definitions.</li><li>
Demonstrated ability to evaluate tools pragmatically (build vs. buy), select architectures, and ship production solutions in ambiguous environments (&ldquo;think and do&rdquo;).</li><li>
Demonstrated experience with RAG patterns, vector search, prompt engineering, and LLM output evaluation techniques</li><li>
Familiarity with emerging agentic AI platforms and runtimes, with the ability to evaluate and explore available tools that support persistent agent execution, governance, and security</li><li>
Demonstrated understanding of responsible AI expectations (human oversight, privacy, security, transparency, and risk management) and ability to implement guardrails accordingly.</li></ul>
Education:<ul><li>
BA/BS degree with an emphasis in IT/IS, Computer Science or equivalent combination of experience and relevant certifications</li></ul><div><div>
Must possess excellent verbal and written communication skills. The ability to motivate or influence others is a material part of the job, requiring a significant level of diplomacy and trust. Obtaining cooperation (internally and/or externally) is an important part of the job. Must be able to communicate complex AI concepts to diverse audiences, ensuring clarity and understanding across all levels of the organization. Collaborates effectively with cross-functional teams to achieve AI objectives, exemplifying leadership and team-building abilities.
Strong analytical, prioritizing, interpersonal, problem-solving, presentation, allocating, project management (from conception to completion), &amp; planning skills.
Strong verbal and written communication skills (including analysis, interpretation, &amp; reasoning).
Skilled at understanding, detailing, and describing complex technical subjects, and aligning business capabilities to Technology solutions.
Ability to develop and maintain collaborative relationships with peers and colleagues across the organization, as well as internal and external clients.
Ability to work well autonomously and within a team in a fast-paced and deadline-oriented environment. 
 Apple Federal Credit Union values, encourages, and implements diversity in the workplace.
As an equal opportunity employer, Apple Federal Credit Union does not discriminate in employment with regard to race, color, religion, national origin, citizenship status, ancestry, age, sex (including sexual harassment), sexual orientation, marital status, physical or mental disability, military status or unfavorable discharge from military service or any other characteristic protected by law.
All selected candidates will be subject to credit and background checks to determine employment eligibility.</div></div></div></div></div></div></div></div></div>

AI Solutions Engineer II

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