ai technical lead

MASTER-WORKS

<div>Provide end-to-end AI technical leadership and solution architecture ownership across AI Projects. The role ensures sound architectural decisions, correct application of AI patterns, and delivery-ready designs, while reducing technical dependency on Project Managers and strengthening execution alignment across delivery teams.Key Responsibilities
Architecture &amp; Technical Leadership<ul><li>
Own and lead AI solution architecture across projects, from concept design through deployment and operational readiness.</li><li>
Define and review end-to-end solution architectures, including AI models, data pipelines, platforms, integrations, infrastructure, and security considerations.</li><li>
Ensure architectural decisions are scalable, secure, cost-effective, and aligned with enterprise and client standards.</li></ul>
AI Pattern &amp; Technology Selection<ul><li>
Ensure the correct selection and implementation of AI patterns, including:</li><li><ul><li>
Computer Vision (CV)</li><li>
Natural Language Processing (NLP)</li><li>
Advanced Analytics</li><li>
Large Language Models (LLMs)</li></ul></li><li>
Evaluate trade-offs between model types, architectures, and deployment approaches (cloud, on-prem, edge).</li></ul>
Delivery &amp; PM Enablement<ul><li>
Support Project Managers and Delivery Managers with:</li><li><ul><li>
Technical estimations and feasibility assessments</li><li>
Identification of technical risks, dependencies, and constraints</li><li>
Delivery sequencing and technical milestone definition</li></ul></li><li>
Act as the technical reference point to unblock delivery and reduce escalation cycles.</li></ul>
Platform, Integration &amp; Readiness<ul><li>
Drive technical alignment across AI teams, platform teams, and infrastructure teams.</li><li>
Ensure code readiness, release readiness, and integration planning across environments (Dev, SIT, UAT, Prod).</li><li>
Review technical deliverables to ensure quality, consistency, and architectural compliance.</li></ul>
Stakeholder Communication<ul><li>
Translate complex technical decisions into clear, structured communication for non-technical stakeholders.</li><li>
Participate in client discussions where architectural clarity or technical assurance is required.</li></ul> 
Requirements 
 
Qualifications &amp; Requirements<ul><li>Strong hands-on background in delivering enterprise-grade AI projects and AI platforms.</li><li>Proven experience in solution architecture, including AI systems, data architectures, and system integrations.</li><li>Solid understanding of AI lifecycle, model deployment, monitoring, and operational considerations.</li><li>Ability to balance technical depth with delivery practicality.</li></ul>
Required Certifications
AI / ML certification from Azure, AWS, or GCP (mandatory or strong requirement).
Arabic speaker with strong spoken and written English.<ul><li>Immediate joining preferred.</li></ul></div>

AI Technical Lead - Arabic speaker

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.
 
 
 <ul>
 <li>
 End-to-End AI/ML Solution Delivery
 </li>
 <li>
 Design &amp; Develop~ Design, develop, industrialize, and deploy advanced predictive and machine learning models (e.g., supervised/unsupervised, scoring, NLP, recommendation &amp; personalization systems,classification, regressions and diagnostic).
 </li>
 <li>
 Build &amp; Innovate~ Build, maintain, and improve robust, scalable data and ML pipelines, from exploration to production (API, CI/CD, MLOps). Construct and innovate with Generative AI systems (LLMs, RAG, fine-tuning) to enhance product features and internal processes.
 </li>
 <li>
 Ensure Quality~ Guarantee solutions are robust, scalable, and production-ready by applying best practices in software engineering and MLOps (e.g., containerization, monitoring, versioning).
 </li>
 <li>
 Own &amp; Deploy~ Own your models end-to-end, from idea generation and prototyping to deployment, monitoring, A/B testing, and continuous improvement. Drive the integration of models into production-ready pipelines, establishing and managing version control, validation, and automated testing strategies.
 </li>
 <li>
 Technical Strategy &amp; Leadership
 </li>
 <li>
 Problem Framing~ Frame use cases with business teams, validate data availability, and use rigorous analysis to break down ambiguous business questions into testable hypotheses and concrete data science projects. Define success metrics (KPIs) upfront to ensure every project has a measurable business impact.
 </li>
 <li>
 Technology Assessment~ Lead "make-or-buy" decisions by evaluating the trade-offs between building proprietary models versus integrating third-party AI services, always aligning with business objectives for speed, cost, and long-term value.
 </li>
 <li>
 Mentorship &amp; Standardization~ Act as a technical reference, providing leadership and mentorship to junior data scientists through code reviews and knowledge sharing. Drive technical excellence by standardizing frameworks and improving our technical stack, modeling approaches, and deployment practices.
 </li>
 <li>
 Innovation~ Stay ahead of market trends and conduct active research on the latest advancements in AI/ML to identify and propose innovative approaches and new use cases. This includes attending conferences,, and participating in meetups and internal learnshops.
 </li>
 <li>
 Collaboration &amp; Influence
 </li>
 <li>
 Data-Driven Collaboration~ Act as the analytical authority within cross-functional teams (Product, Engineering, Business). Challenge existing assumptions with data, guide strategic decisions with analytical evidence, and ensure model outputs are directly integrated into business workflows.
 </li>
 <li>
 Insightful Communication~ Go beyond just presenting results. Clearly explain the "why" behind your model's logic, its limitations (e.g., biases, confidence levels), and the trade-offs between different analytical approaches to both technical and executive audiences.
 </li>
 <li>
 Actionable Visualization~ Create clear dashboards and visualizations that tell a story with the data, empowering stakeholders to make data-informed decisions independently.
 </li>
 <li>
 Cross-Functional Leadership~ Lead collaboration with IT and Data Engineering teams to enhance data accessibility, harmonization, pipeline robustness, and streamline model deployment.
 </li>
 <li>
 Data Strategy~ Evaluate data availability, coverage, and quality, proposing pragmatic approaches for calibration, substitution, or enrichment when datasets are incomplete or imperfect.
 
 
 </li>
 </ul>
 
 
 
 Professional
 
 
 Experience
 
 
 
 
 
 We are looking for a candidate who embodies three core strengths~
 
 
 <ul>
 <li>
 Technical &amp; Execution Excellence You are a master builder who ships robust, production-grade solutions.
 </li>
 <li>
 After a master degree and PhD , you bring 5+ years of applied experience as a Data Scientist, with a proven track record of taking complex Machine Learning projects from initial POC to full production deployment.
 </li>
 <li>
 Your experience comes from a fast-paced, commercial environment (such as E-commerce, FinTech, Online Travel, SaaS, or modern Tech Consulting), where you have successfully built and shipped models for dynamic pricing, demand forecasting, or resource optimization.
 </li>
 <li>
 Your technical toolkit is extensive, with an excellent mastery of Python and its core data science libraries (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, pandas, NumPy).
 </li>
 <li>
 You have strong knowledge of the full MLOps and Data Engineering lifecycle, including SQL, containerization (Docker), workflow orchestration (Airflow), CI/CD, and model deployment/serving (MLflow, Kubernetes, REST APIs).
 </li>
 <li>
 You have a deep understanding of Generative AI architectures and workflows (embeddings, RAG, fine-tuning) and have experience with GenAI/LLM projects.
 </li>
 <li>
 You are adept at creating clear, insightful visualizations using tools like Looker, Tableau, or Power BI and applying Agile/scrum methodologies to deliver results iteratively.
 </li>
 <li>
 You have hands-on experience working with large-scale datasets in cloud environments (e.g., AWS, GCP).
 </li>
 <li>
 Strategic &amp; Business Acumen You think like a business owner and translate complex data into tangible value.
 </li>
 <li>
 You have a proven ability to deconstruct ambiguous business problems into a clear analytical framework, defining testable hypotheses and the KPIs that will measure success.
 </li>
 <li>
 You demonstrate strong project management skills, taking ownership of the entire project lifecycle to ensure solutions are delivered on time and create measurable business impact.
 </li>
 <li>
 You practice statistical rigor, going beyond model accuracy to validate choices, quantify uncertainty, and ensure the reliability and fairness of your results in a real-world context.
 </li>
 <li>
 You have led root-cause investigations, using data to diagnose why business metrics deviate from expectations and recommending a clear solution.
 </li>
 <li>
 You demonstrate exceptional business impact translation, turning complex model outputs into a compelling narrative that influences leadership-level decisions.
 </li>
 <li>
 Leadership &amp; Collaborative Influence You are a natural coach and communicator who elevates the entire team.
 </li>
 <li>
 You possess strong leadership and mentoring skills with a genuine passion for sharing knowledge, helping others grow, and fostering a collaborative team environment.
 </li>
 <li>
 Your communication skills are excellent, giving you the ability to tell a compelling story with data and distill complex topics into simple, clear explanations for any audience.
 </li>
 <li>
 You have a proactive, autonomous, and results-oriented mindset. You are intellectually curious, pragmatic, and thrive in a fast-paced, collaborative setting.
 </li>
 <li>
 You have the business acumen to understand complex challenges and translate them into adapted technical solutions.
 
 
 </li>
 </ul>
 
 Position~
 
 
 
 Engineering Disciplines
 
 
 
 D&eacute;partement~
 
 
 
 Software Development
 
 
 
 Schedule~
 
 
 
 Temps plein
 
 
 
 Employee Status~
 
 
 
 CDI
 
 
 
 Type de contrat~
 
 
 
 
 Job Posting Date~
 
 
 
 2026-02-22
 
 
 
 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>

Senior AI Technical Lead, Valeo Service

Fusion Cortex

Job Title: AI Architect &amp; Technical LeadLocation: Johar Town, Lahore Experience: 5+ Years (Full-Stack Development &amp; Systems Architecture) Technology Stack: TypeScript/Node.js, React, Vector Databases, Cursor/Vibe-Native Tools, Python/FastAPIThe MissionWe are a fast-moving AI venture leveraging the &ldquo;Vibe Coding&rdquo; revolution to build MVPs at exceptional speed. We are seeking a Founding AI Architect &amp; Technical Lead who can embrace this rapid development pace while ensuring our systems remain structured, scalable, and secure.You will lead a passionate team of junior developers, mentoring them on how to effectively use AI development tools (Cursor, Lovable, Claude) while maintaining strong engineering discipline, architectural consistency, and production readiness.Key ResponsibilitiesAI Development OrchestrationDefine and maintain development standards for AI-assisted coding, including frameworks such as .cursorrules, prompt libraries, and system prompts, ensuring AI-generated code aligns with our architectural and security standards.Hybrid Data ArchitectureDesign and oversee a scalable hybrid data ecosystem that integrates:&middot; Relational databases (PostgreSQL / MySQL) for application portals&middot; Vector databases (Pinecone, Weaviate, pgvector) for RAG systems and AI pipelines&middot; NoSQL or unstructured storage for model training datasetsAI-Driven Engineering MentorshipLead developers through pair programming and AI-assisted development workflows, teaching best practices for prompt engineering and code validation while maintaining clean, modular backends using Node.js/TypeScript and Python/FastAPI.Infrastructure &amp; ReliabilityTransform AI-generated prototypes into production-ready microservices, implementing Dockerized architectures that are secure, scalable, and reliable.Data Pipeline OversightCollaborate closely with the data scraping and data engineering team to ensure collected datasets are clean, structured, and high-quality for both marketing platforms and AI model training/fine-tuning pipelines.Required Technical Expertise Full-Stack EngineeringExpert-level experience with:&middot; React (Frontend Development)&middot; Node.js / TypeScript (Backend Systems)AI-Native DevelopmentHands-on expertise with modern AI development tools such as:&middot; Cursor , Claude &amp; LovableYou view AI as a force multiplier for engineering productivity, not a shortcut that replaces sound engineering practices.Database &amp; Data ArchitectureStrong experience with:&middot; PostgreSQL or MySQL&middot; Vector databases (Pinecone, Weaviate, pgvector)&middot; Data modeling for hybrid AI + application architecturesDevOps &amp; SecurityPractical experience with:&middot; Docker and containerized microservices&middot; Production infrastructure practices&middot; Security auditing of AI-generated code&middot; Secure API design and system hardeningThe Ideal Candidate:&middot; 5+ years of professional software engineering experience&middot; Maintains a strong builder / hacker mindset&middot; Enjoys mentoring developers and pair programming&middot; Comfortable operating in startup environments with evolving requirements&middot; Thrives in phase-wise product delivery and rapid iteration cyclesEngineering Philosophy Code Quality:AI-generated code is treated as a first draft, not the final product. Every output must be reviewed, refactored, and validated for maintainability and security.Scalability: Even early MVPs should be designed with the potential to scale to 100,000+ users.Efficiency: Success is measured by the team&rsquo;s iteration velocity combined with production stability and reliability.Job Type: Full-timePay: Rs300,000.00 - Rs500,000.00 per monthWork Location: In person

AI Architect & Technical Lead

Vodafone

<div><div><div><div><h2 class="jobSectionHeader">Join Us</h2>
</div><div>
At Vodafone, we&rsquo;re not just shaping the future of connectivity for our customers &ndash; we&rsquo;re shaping the future for everyone who joins our team. When you work with us, you&rsquo;re part of a global mission to connect people, solve complex challenges, and create a sustainable and more inclusive world. If you want to grow your career whilst finding the perfect balance between work and life, Vodafone offers the opportunities to help you belong and make a real impact.</div></div><div><div><h2 class="jobSectionHeader">
Role Purpose</h2>
</div><div><ul><li>Act as the technical lead responsible for implementing enterprise customers&rsquo; requirements into actionable AI/ML solutions, working in close coordination with the Enterprise AI Solution Tech Lead and Product Owners.</li><li>
Develop and deliver robust AI models and data pipelines (on-prem and cloud-hosted), ensuring they meet business objectives, customer expectations, and performance standards.</li><li>
Collaborate with the Enterprise AI team to operationalize AI use cases and translate high-level solution designs into scalable, production-ready implementations.</li><li>
Apply deep data science expertise to bridge the gap between AI solution design and execution, ensuring technical soundness and business relevance.</li></ul></div></div><div><div><h2 class="jobSectionHeader">
Role Responsibilities</h2>
</div><div>
Solution Implementation<ul><li>
Translate customers&rsquo; requirements into actionable data science tasks and implementation plans.</li><li>
Lead the development, training, and deployment of AI models and data pipelines tailored to customer-specific requirements.</li><li>
Ensure models and AI components are scalable, efficient, and production-ready, with smooth integration into customer systems and enterprise platforms.</li></ul>
Technical Leadership<ul><li>
Serve as the subject matter expert (SME) in machine learning, data science, and AI engineering practices.</li><li>
Provide hands-on technical guidance to data scientists, engineers, and MLOps teams, ensuring accurate and effective implementation.</li><li>
Lead technical squads through virtual collaboration, guaranteeing solutions are built to meet both customer expectations and technical standards.</li></ul> 
Decision Execution<ul><li>
Validate model performance, data quality, and technical fit before solution handover.</li><li>
Collaborate with the Enterprise Tech Leads and Product Owners to review and confirm solution readiness based on business impact, feasibility, and model validation results.</li><li>
Provide input on task prioritization based on complexity, risk, and technical dependencies.</li></ul>
Customer Support<ul><li>
Work alongside the Enterprise team to ensure implemented AI solutions meet business outcomes and address real customer needs.</li><li>
Explain data science approaches, results, and business insights in a clear and accessible manner to both technical and non-technical stakeholders.</li><li>
Contribute to building customer confidence in Vodafone&rsquo;s AI capabilities by ensuring reliable and transparent solution delivery.</li></ul>
Value Realization<ul><li>
Identify technical opportunities to improve performance, accuracy, and efficiency of existing AI solutions.</li><li>
Recommend data science enhancements and automation strategies that can further strengthen the customer&rsquo;s business outcomes.</li></ul>
Contribute to refining reusable assets, components, and best practices for enterprise AI delivery</div></div><div><div><h2 class="jobSectionHeader">
Core Competencies and Qualifications</h2>
</div><div>
Customer-Focused Execution<ul><li>
Strong communication skills to understand solution requirements in collaboration with Enterprise Tech leads and Product Owners and translate them into data science tasks.</li><li>
Ability to present data-driven insights, model performance, and implementation results in a clear, business-relevant manner.</li></ul>
Problem Solving and Innovation<ul><li>
Strong analytical thinking and debugging skills to address real-world AI deployment challenges (e.g., model drift, data quality, latency).</li></ul>
Creativity in designing tailored AI pipelines that are both effective and maintainable in production.
Collaboration and Delivery Leadership<ul><li>
Proven ability to collaborate with engineers, data scientists, MLOps specialists, and architects to deliver high-quality AI solutions.</li></ul>
Leadership in execution: mentoring technical team members, performing code reviews, and ensuring delivery excellence.
Must-Have Technical / Professional Qualifications<ul><li>
Bachelor&rsquo;s or master&rsquo;s degree in computer science, Data Science, Artificial Intelligence, or a related field.</li><li>
5&ndash;7 years of hands-on experience in developing and deploying AI/ML models in production environments.</li><li>
Advanced proficiency in ML libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).</li><li>
Strong expertise in building advanced Generative AI (GenAI) and Natural Language Processing (NLP) applications using modern large language models and frameworks (e.g., Hugging Face, Langchain, OpenAI APIs, Agents Frameworks).</li><li>
Experience with big data processing and distributed computing using Apache Spark or similar technologies.</li><li>
Proficiency in building, deploying, and managing AI, GenAI and big data applications on cloud platforms (e.g., AWS, Azure, GCP).</li></ul>
Experience with MLOps tools and techniques for versioning, CI/CD, monitoring, and scaling models</div></div><div><div><h2 class="jobSectionHeader">
Not a perfect fit?</h2>
</div><div>
Worried that you don&rsquo;t meet all the desired criteria exactly? At Vodafone we are passionate about empowering people and creating a workplace where everyone can thrive, whatever their personal or professional background. If you&rsquo;re excited about this role but your experience doesn&rsquo;t align exactly with every part of the job description, we encourage you to still apply as you may be the right candidate for this role or another opportunity.</div></div><div><div><h2 class="jobSectionHeader">
Who we are</h2>
</div><div>
We are a leading international Telco, serving millions of customers. At Vodafone, we believe that connectivity is a force for good. If we use it for the things that really matter, it can improve people's lives and the world around us. Through our technology we empower people, connecting everyone regardless of who they are or where they live and we protect the planet, whilst helping our customers do the same.
Belonging at Vodafone isn't a concept; it's lived, breathed, and cultivated through everything we do. You'll be part of a global and diverse community, with many different minds, abilities, backgrounds and cultures. ;We're committed to increase diversity, ensure equal representation, and make Vodafone a place everyone feels safe, valued and included.
If you require any reasonable adjustments or have an accessibility request as part of your recruitment journey, for example, extended time or breaks in between online assessments, please refer to https://careers.vodafone.com/application-adjustments/ for guidance.
Together we can.</div></div></div></div>

Enterprise AI Solutions Technical Lead

APGAR

<div>
 
 APGAR is a leading consultancy company specialized in
 
 Data Management
 
 and
 
 Artificial Intelligence
 
 , helping organizations across industries harness the power of data and AI to drive strategic and operational transformation.
 
 
 
 
 
 Your missions
 
 
 
 
 
 As an AI Solution Architect, you will be part of a team working on Client projects. You will be supervised by a Technical Director or a Manager and will act as a technical reference for AI-related topics.
 
 
 
 
 
 
 External missions
 
 :
 
 <ul>
 <li>
 You will work on all phases of AI and Data &amp; AI solutions delivery, from use case definition to production readiness
 </li>
 <li>
 You will take part in the design and definition of AI solution architectures (data flows, AI services, integration, security)
 </li>
 <li>
 You will define the technical approach for AI solutions (ML, Generative AI, RAG, predictive models) and validate implementation choices
 </li>
 <li>
 You will define operating rules, non-functional requirements, and scalability principles for AI solutions
 </li>
 <li>
 You will supervise and validate the implementation carried out by technical teams or partners
 </li>
 <li>
 You will be responsible for continuous integration, deployment, and monitoring principles for AI solutions (MLOps supervision)
 </li>
 <li>
 You will endorse responsibility for the overall technical quality of AI solutions and support the project team on complex technical topics
 </li>
 <li>
 You will be accountable for the overall quality of deliveries and technical documentation (architecture documents, security notes, operating guides)
 </li>
 <li>
 You will assist the client in the setup, administration, and governance of AI solutions in cloud or on-premise environments, while defining methodologies and DevOps/MLOps processes
 </li>
 </ul>
 
 
 
 
 
 Pre-sales
 
 :
 
 
 
 <ul>
 <li>
 You will be involved in effort estimation for tender calls
 </li>
 <li>
 You will write the technical and architectural sections of tender calls in full autonomy (writing and presentation)
 </li>
 <li>
 You will participate in client workshops and solution presentations to position AI solutions
 </li>
 </ul>
 
 
 
 
 
 R&amp;D and internal missions
 
 :
 
 <ul>
 <li>
 You will contribute to R&amp;D activities in collaboration with the Offers and Innovation teams
 </li>
 <li>
 You will participate in the design of reusable AI architectures, frameworks, and accelerators
 </li>
 <li>
 You will take part in technical knowledge capitalization (best practices, reference architectures, AI patterns)
 </li>
 <li>
 You will evaluate new AI platforms, tools, and cloud services to enrich our AI offerings
 </li>
 <li>
 You will participate in internal initiatives (mentoring, offers structuring, community of practice, recruitment support)Depending on your career path wishes and desires, you will have the opportunity to move towards a position of technico-functional consultant. While still acting as a functional consultant, you will also be involved in the setting and configuration of the solution.
 </li>
 </ul>
 
 
 
 
 Your Profile :
 
 <ul>
 <li>
 Master&rsquo;s degree or equivalent, with at least 5 &ndash; 8 years of experience in a consulting firm or IT services company
 </li>
 <li>
 You have designed, assessed, and guided the implementation of AI or advanced data solutions in enterprise environments
 </li>
 <li>
 You have strong experience in AI solution architecture and technical leadership
 </li>
 <li>
 You are comfortable working in client-facing and presales contexts
 </li>
 <li>
 You explained ML, GenAI, and Agentic AI concepts to non-technical stakeholders
 </li>
 <li>
 You communicated AI limitations, risks, and trade-offs clearly
 </li>
 <li>
 You have clearly written documentation and customer-facing summaries
 </li>
 <li>
 You participated in customer calls, demos, and workshops
 </li>
 <li>
 You did cross-functional communication with product, engineering, and sales teams
 </li>
 </ul>
 
 
 
 
 You have a solid grasp of the following fields:
 
 
 Core AI &amp; Machine Learning
 
 <ul>
 <li>
 Understanding of machine learning fundamentals (supervised/unsupervised learning, model training, evaluation)
 </li>
 <li>
 Familiarity with common ML algorithms (regression, classification, clustering)
 </li>
 <li>
 Basic understanding of feature engineering and data preprocessing
 </li>
 <li>
 Ability to interpret ML model outputs and performance metrics (accuracy, precision/recall, F1, etc.)
 </li>
 <li>
 Awareness of model overfitting, bias, and generalization
 </li>
 <li>
 Understanding of model lifecycle (training, validation, deployment, monitoring)
 </li>
 </ul>
 
 Data &amp; Integration
 
 <ul>
 <li>
 Data architectures (data lake, lakehouse, batch &amp; streaming)
 </li>
 <li>
 Data integration patterns, APIs, and enterprise systems
 </li>
 <li>
 Data quality, metadata, and governance concepts
 </li>
 </ul>
 
 Cloud &amp; Platforms
 
 <ul>
 <li>
 Strong exposure to Azure, AWS, or GCP ecosystems
 </li>
 <li>
 Managed AI services and vector databases
 </li>
 <li>
 Security, identity management, and access control
 </li>
 </ul>
 
 Architecture &amp; Documentation
 
 <ul>
 <li>
 Design of technical and solution architecture documents
 </li>
 <li>
 Definition of operating models and deployment strategies
 </li>
 <li>
 Ability to review and challenge technical designs
 </li>
 </ul>
 
 Methodology &amp; Delivery
 
 <ul>
 <li>
 Agile delivery methodologies
 </li>
 <li>
 CI/CD and MLOps concepts (deployment, monitoring, retraining)
 </li>
 <li>
 Experience working with tools such as Jira, Git-based workflows, and CI pipelines
 </li>
 </ul>
 
 AI-Readiness &amp; Enablement
 
 <ul>
 <li>
 Assessing customer AI-readiness (data availability, quality, governance, risk)
 </li>
 <li>
 Identifying AI-appropriate use cases based on customer maturity
 </li>
 <li>
 Supporting customers in preparing data and workflows for ML and GenAI adoption
 </li>
 <li>
 Educating customers on responsible AI and realistic expectations
 </li>
 <li>
 Contributing to AI-readiness assessments, frameworks, or playbooks
 </li>
 </ul>
 
 
 
 
 
 
 
 Do not hesitate to apply if you are a dynamic, enthusiastic and curious person. You will join a pleasant, benevolent and fraternal working environment&hellip; Future Apgarians, we are waiting for you!
 
</div>

AI Solution Consultant

Polarity Holdings

Note: This is a fully remote role for a US-based company. Professionals from all over Pakistan are encouraged to apply.Title: Head of Artificial Intelligence, Data Science, &amp; Machine LearningLocation: 100% Remote &ndash; Work from Anywhere in PakistanCompany HQ: New York, NY, USAContact: www.falconscaling.com | optimize@falconscaling.com | PolarityIQ.comCompensation: 363,000 PKR per month starting salaryAbout Us:Falcon Scaling and PolarityIQ are seeking a technical leader to own the creation of AI-powered products and the construction, enrichment, and intelligence of our core databases.This is a hands-on, high-autonomy role. You will conceptualize and build original AI products, design and deploy machine learning pipelines, architect intelligent data systems, and deliver real revenue-generating assets across both platforms.We are not looking for someone who manages AI teams. We are looking for someone who builds AI products &mdash; with their own hands, their own judgment, and their own code.If you thrive in ambiguity, take pride in ownership, and measure yourself by outcomes rather than hours logged, read on.Why You Might Want This RoleThis is a role for an extraordinarily skilled and motivated individual. Thorough, efficient, high-quality work is heavily rewarded.<ul><li>You will be paid weekly, on-time, every time &mdash; no waiting, no wondering, no anxiety.</li><li>With salary + commission, your on-target monthly earnings (OTE) can exceed Rs1,000,000 PKR.</li><li>This position will expand how you think, build, and solve problems at the intersection of AI, data, and product.</li><li>You will be consistently challenged &mdash; your assumptions, processes, biases, conclusions, and limitations.</li></ul>What You&rsquo;ll OwnAt a Glance &mdash; This Role Requires Someone Who:<ul><li>Builds AI products from scratch &mdash; not just uses AI, but designs, engineers, and ships revenue-generating AI tools and platforms</li><li>Architects and enriches databases &mdash; building, cleaning, deduplicating, normalizing, and scaling the data infrastructure that powers PolarityIQ</li><li>Deploys Claude Code as a primary development environment &mdash; building, iterating, and shipping features through agentic terminal-based workflows</li><li>Designs and trains machine learning models &mdash; classification, NLP, entity resolution, predictive scoring, and recommendation systems</li><li>Builds data pipelines &mdash; ingestion, transformation, enrichment, and quality assurance across structured and unstructured sources</li><li>Masters data science workflows &mdash; statistical analysis, feature engineering, model evaluation, and deployment</li><li>Uses AI daily as a force multiplier &mdash; without outsourcing judgment</li><li>Owns outcomes autonomously &mdash; no hand-holding, no excuses</li><li>Communicates in flawless English &mdash; first draft publishable</li><li>Treats budget like their own money &mdash; questions every tool, subscription, and cost that doesn&rsquo;t earn its place</li></ul>If Claude Code isn&rsquo;t already part of your daily workflow, this role will move too fast for you.AI Product Creation<ul><li>Conceptualize, build, and launch original AI-powered products &mdash; similar in nature to our Family Office Catalyst toolkit: https://www.polarityiq.com/fo-cat-63798</li><li>Translate real market problems into structured AI-driven solutions, not just prompts wrapped in a PDF</li><li>Identify new product opportunities across both platforms and take them from idea to revenue-generating asset</li><li>Build automated AI workflows that create genuine leverage without replacing critical thinking</li><li>Design product architectures that are scalable, maintainable, and cost-efficient &mdash; not proof-of-concept demos that collapse under real usage</li><li>Use AI as a force multiplier &mdash; not a crutch. You bring the strategy, judgment, and domain expertise; AI accelerates execution</li></ul>AI Agent Development<ul><li>Design and deploy autonomous AI agents that gather, validate, and synthesize intelligence across public and proprietary data sources</li><li>Build agents that monitor target accounts for personnel changes, allocation shifts, fund launches, and other actionable signals &mdash; without manual triggering</li><li>Understand agent architecture patterns &mdash; tool use, memory, multi-step reasoning, human-in-the-loop checkpoints</li><li>Know the difference between a prompt chain and an actual agent, and when each is appropriate</li></ul>Data Science &amp; Machine Learning<ul><li>Design, train, and deploy machine learning models for entity resolution, lead scoring, classification, clustering, and predictive analytics</li><li>Build NLP pipelines for extracting structured intelligence from unstructured data &mdash; filings, news, bios, fund documents, and web content</li><li>Develop recommendation and matching algorithms that surface high-relevance connections within family office and institutional data</li><li>Implement model monitoring, evaluation, and retraining workflows to maintain accuracy over time</li><li>Apply statistical rigor to data analysis &mdash; hypothesis testing, confidence intervals, A/B testing, and causal inference where appropriate</li><li>Translate complex analytical findings into actionable product features and business insights</li></ul>Database Architecture &amp; Enrichment<ul><li>Own the architecture, integrity, and growth of PolarityIQ&rsquo;s core intelligence database &mdash; the central asset that powers the platform</li><li>Design and manage relational schema across Supabase/PostgreSQL, ensuring normalization, indexing, and query performance at scale</li><li>Build and manage multi-source data enrichment waterfalls using Clay, Apollo, Hunter, People Data Labs, Clearbit, and similar platforms</li><li>Scrape and structure data from web sources using tools like Apify, Phantombuster, or Browse AI</li><li>Clean, deduplicate, and normalize large datasets for CRM or database ingestion</li><li>Apply data hygiene principles across all pipelines &mdash; bounce rates, email verification, contact scoring, and stale record detection</li><li>Work with APIs to pull, push, and transform data between platforms independently</li><li>Use Claude Code to orchestrate enrichment pipelines intelligently &mdash; not just routing data, but applying reasoning to flag stale records, infer missing attributes, and surface insights that standard enrichment tools cannot</li><li>Build data pipelines with cost efficiency in mind &mdash; avoiding expensive vendor overlap and prioritizing solutions that scale without proportional cost growth</li></ul>Claude Code &mdash; Non-Negotiable ProficiencyClaude Code is not a nice-to-have here. It is how development gets done.<ul><li>Operate Claude Code in terminal-based, agentic workflows &mdash; not as a code completer, but as a development collaborator you can direct, correct, and build with autonomously</li><li>Use Claude Code to orchestrate multi-step data enrichment pipelines &mdash; chaining Apollo, Clay, People Data Labs, Hunter, and your own Supabase database in a single automated workflow</li><li>Apply Claude Code&rsquo;s 200K context window to large codebase refactoring and architectural decisions that IDE-based tools cannot handle at the same depth</li><li>Understand Claude Code&rsquo;s limits &mdash; know when to use it versus when a GUI-based IDE is the right tool, and make that call without hand-holding</li></ul>SaaS Technical Development<ul><li>Architect, build, and maintain features across our SaaS platform (app.polarityiq.com), including frontend UI, backend logic, API integrations, and database management</li><li>Design clean, intuitive user experiences that reduce friction and improve conversion</li><li>Leverage Claude Code as a primary development tool &mdash; using agentic coding workflows to accelerate feature builds, prototype rapidly, and maintain output quality without ballooning engineering hours</li><li>Audit and rationalize tool spend across both platforms &mdash; identifying redundant subscriptions, underutilized licenses, and cheaper alternatives without sacrificing capability</li></ul>Technical Stack &amp; ToolsAI, ML, &amp; Data Science<ul><li>Strong proficiency with Python data science stack &mdash; pandas, NumPy, scikit-learn, XGBoost, and similar libraries</li><li>Experience with NLP frameworks and tools &mdash; spaCy, Hugging Face Transformers, LangChain, or equivalent</li><li>Working knowledge of deep learning frameworks (PyTorch or TensorFlow) for custom model development where needed</li><li>Experience building and deploying ML models in production &mdash; not just notebooks</li><li>Daily working proficiency with Claude, ChatGPT, and Gemini for content, research, automation, and product development</li><li>Claude Code Proficiency &mdash; Non-Negotiable: You are comfortable operating Claude Code in terminal-based, agentic workflows. It should feel like a natural extension of how you work &mdash; not something you&rsquo;re learning on the job.</li><li>Ability to build and refine custom prompts, automated workflows, and original AI-generated product pipelines</li><li>Critically important: you know how to leverage AI without losing your own judgment. You do not outsource your brain.</li></ul>Development &amp; Infrastructure<ul><li>Proficient in at least one modern frontend framework (React, Vue, or equivalent)</li><li>Backend experience with Python, Node.js, or similar</li><li>Database administration: SQL, relational schema design, and query optimization &mdash; including managed platforms such as Supabase or Firebase</li><li>API integration experience (REST, GraphQL, webhooks, third-party SaaS tools)</li><li>Version control via Git / GitHub</li></ul>Data &amp; Productivity<ul><li>Advanced Microsoft Excel &mdash; pivot tables, complex formulas, data modeling, and large dataset management</li><li>Experience with CRM tools, email platforms, and marketing automation (HubSpot, Apollo, Instantly, or equivalents)</li><li>Comfortable operating across Notion, Slack, and collaborative project management tools</li></ul>Communication<ul><li>Exceptional English proficiency: written and spoken</li><li>Able to write client-facing copy, technical documentation, and professional correspondence without editorial oversight</li><li>Communicates with clarity and precision; understands that how something is said is as important as what is being said</li><li>No heavy editing cycles required &mdash; your first draft should be close to publishable</li></ul>Deadlines / Work Pace / Evaluatory CriteriaMuch of your work will be done autonomously &mdash; meaning you will not be closely supervised. Your work will be evaluated in terms of both pace and output quality. You will be expected to adhere to internal deadlines and keep up with the pace set by management.For full performance evaluation criteria:Who You AreThe technical skills matter. But this section matters more.We are looking for someone who takes ownership before being asked &mdash; who sees a problem and solves it without waiting for a task list. Someone who measures themselves by outcomes, not activity. Who is honest, even when it&rsquo;s uncomfortable. Reliable, not occasionally but consistently. And resourceful enough to treat every dollar spent like it&rsquo;s coming out of their own pocket.If that description doesn&rsquo;t fit you naturally, this role will be a poor fit.You Think RigorouslyYour thought process is disciplined. You verify before you assert. You distinguish between facts, inferences, and conclusions &mdash; and you never conflate the three. You test your assumptions before acting on them, and you&rsquo;re willing to challenge your own hypotheses when the evidence points elsewhere.You resist the temptation to treat incomplete data as certainty. In a world saturated with AI-generated content, the ability to evaluate what is actually true &mdash; not just what sounds true &mdash; is among the most valuable skills you bring to this role. You are the quality filter. Not the other way around.You Use AI as a Tool, Not a CrutchWe use AI extensively, and we expect you to as well. But we are looking for someone who thinks independently first and uses AI to sharpen that thinking &mdash; not someone who outsources their judgment to a model and forwards the output.Claude Code, in particular, should feel like a natural extension of how you work &mdash; not something you&rsquo;re learning on the job. You will know when it&rsquo;s wrong. You will know when it&rsquo;s shallow. And you will apply the human layer of thinking that no prompt can replicate.You Are Savvy with ResourcesYou treat budget like it&rsquo;s your own money. You identify the leanest path to an outcome and question every tool, subscription, and workflow that doesn&rsquo;t earn its cost. You don&rsquo;t accumulate software &mdash; you audit it. You don&rsquo;t add vendors &mdash; you justify them.We have seen what happens when someone in this seat builds without cost awareness. We are not going back.Operating PrinciplesThese are not resume keywords. They are the standards we hold ourselves to &mdash; and what we will be evaluating in the first 30 days.<ul><li>Mature &mdash; You handle pressure, ambiguity, and feedback like a professional</li><li>Reliable &mdash; Your commitments mean something</li><li>Honest &mdash; You tell the truth about progress, blockers, and mistakes</li><li>Goal-Focused &mdash; You optimize for outcomes, not the appearance of busyness</li><li>Autonomous &mdash; You make sound decisions independently and move forward without hand-holding</li><li>Accountable &mdash; You own your results fully, including the bad ones</li><li>Expeditious &mdash; You move with urgency and respect that time is the scarcest resource</li><li>Resourceful &mdash; You find the leanest path and question every cost that doesn&rsquo;t earn its place</li><li>Responsible &mdash; You are drawn toward responsibility, not away from it</li></ul>Job Type: Full-timePay: Rs363,000.00 per monthEducation:<ul><li>Master's (Preferred)</li></ul>Language:<ul><li>English (Preferred)</li></ul>Work Location: In person

Head of Artificial Intelligence, Data Science, & Machine Learning

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