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Palladium Pakistan Pvt Ltd

<div><div><div><div>Posted date</div> <div>27th February, 2026</div> <div>Last date to apply</div> <div>5th March, 2026</div>
</div> 
<div><div>Country</div> <div>Pakistan</div> <div>Locations</div> <div>Islamabad</div>
</div> 
<div><div>Category</div> <div>Artificial Intelligence
</div></div> 
<div><div>Type</div> <div>Consultancy</div> <div>Position</div> <div>1</div>
</div> 
<div><div>Experience</div> <div>10 years</div></div></div></div>
 <div>Mid National - AI / Machine Learning Specialist/Developer

E4H FED TA: Embedded Technical Support to the Ministry of National Health Services, Regulation &amp; Coordination (M/o NHSR&amp;C)

Programme Overview

Evidence for Health (E4H) is a Foreign, Commonwealth &amp; Development Office (FCDO)-funded programme aimed at strengthening Pakistan's healthcare system, thereby decreasing the burden of illness and saving lives. E4H provides technical assistance (TA) to the Federal, Khyber Pakhtunkhwa (KP), and Punjab governments, and is being implemented by Palladium along with Oxford Policy Management (OPM).

Through its flexible, embedded, and demand-driven model, E4H supports the government to achieve a resilient health system that is prepared for health emergencies, responsive to the latest evidence, and delivers equitable, quality, and efficient healthcare services. Specifically, E4H delivers TA across three outputs:

Output 1: Strengthened integrated health security, with a focus on preparing and responding to health emergencies, including pandemics.

Output 2: Strengthened evidence-based decision-making to drive health sector performance and accountability.

Output 3: Improved implementation of Universal Health Coverage, with a focus on ending preventable deaths.

Position Summary

The overall goal is to develop a National Digital Health Hub (NDHH) software and implement an integrated, scalable, and interoperable digital health information platform within a six-month timeframe

Specific Objectives

The specific objectives are to:
<div>
<ul><li>Link the remaining two provinces to NDHH through secure, standards-aligned interoperability mechanisms and validated data pipelines;</li></ul>
<ul><li>Operationalise the Practice Hub to deliver AI-enabled advanced analytics and decision support, including explainable insights and scenario-oriented outputs;</li></ul>
<ul><li>Strengthen governance, capacity, and sustainability arrangements so that NDHH is routinely usable and maintainable within Government systems (NHDC/NIH and provincial counterparts).</li></ul>
</div>
Strategic Approach

Phase II will follow the same strategic logic established in Phase 1. The focus will be on connecting/linking existing systems and datasets, support interoperability, ensure secure and ethical use of health data, strengthen capacity for routine use, and build a flexible platform aligned with global standards that can adapt to future health system needs.

Key strategic principles include:
<ul>
<li>Federated interoperability (connect and exchange rather than replace existing provincial systems)</li>
<li>Governance-led implementation (data sharing and decision rights defined up-front)</li>
<li>Incremental rollout with verification (pilot-to-scale with measurable acceptance criteria)</li>
<li>Human-centred adoption (capacity building, usability, and local operational ownership)</li>
</ul>
Scope of Work

As a part of this TA assignment, the consultant(s) will cover the following scope of work:

1 Governance, Coordination, and Data Sharing

Building on Phase 1 governance structures, the consultant(s) will:
<ul>
<li>Strengthen and operationalise national&ndash;provincial coordination mechanisms for NDHH implementation (including provincial inclusion and decision pathways).</li>
<li>Support the completion/update of data sharing instruments (e.g., MoUs/DSA) between M/o NHSR&amp;C, NIH/NHDC and the participating provinces/areas, clarifying roles, responsibilities, and permissible use.</li>
<li>Establish practical governance for AI-enabled decision support (approval workflow for use-cases, safeguards, and change control).</li>
</ul>
2 Provincial Onboarding and Integration (Remaining Two Provinces)
<ul>
<li>Conduct onboarding the two remaining provinces (systems integration, linkage, APIs, metadata alignment, connectivity, and privacy constraints).</li>
<li>Implement and validate secure data exchange pipelines (scheduled ingestion, reconciliation, error handling, and alerting), consistent with the Phase 1 approach to backend integration and validation.</li>
<li>Use and apply existing national metadata packages and indicator mappings to ensure comparability across provinces while retaining provincial context.</li>
<li>Conduct integration testing and provincial UAT with documented sign-off.</li>
</ul>
3 Practice Hub Development (AI-enabled Advanced Analytics)

The consultant(s) will design, develop, test, deploy and operationalise the Practice Hub, including AI models configured and executed in the accordance with NDHH requirements, as a controlled decision-support layer that:
<ul>
<li>Enables authorised users to query integrated datasets and receive interpretable results (trends, comparisons, alerts, &ldquo;&rdquo; what-if&rdquo; scenarios, briefs and short summaries).</li>
<li>Connects with the Knowledge Hub, so results are linked to relevant policies, guidelines, and evidence resources to support learning and consistent decision making..</li>
<li>Implements ethical and safety AI controls to protect privacy, reduce bias, ,explain how results are generated , track system use, and restrict access based on user role.</li>
<li>Uses approved AI services through secure APIs (where approved) to support advanced analysis and summarisation, while protecting sensitive information and tracking data sources.</li>
</ul>
4 Security, Identity, and Access Management
<ul>
<li>Ensure role-based access controls and permissions for new provincial users and for Practice Hub functions (including auditability).</li>
<li>Protect system and data by using encryption, multi-factor authentication, and secure operating practices with national hosting requirements.</li>
</ul>
5 Testing, Quality Assurance, and Deployment
<ul>
<li>Execute a structured test plan: unit, integration, end-to-end, performance/load, security testing, and UAT.</li>
<li>Conduct UAT in the two newly onboarded provinces and ensure the NDHH is ready to for routine use.</li>
<li>Establish monitoring and operational procedures; configure alerts and routine checks (operational sustainability).</li>
</ul>
6 Documentation, Training, Capacity Building, and Handover
<ul>
<li>Produce comprehensive technical documentation (NDHH architecture, APIs, interoperability mechanisms, and end to end data flows), user guides, and training materials and conduct structured training sessions.</li>
<li>Strengthen NIH/NHDC operational capacity through hands-on administration, supervised operations, and progressive handover.</li>
</ul>
Focal points nominated by the Director General (Health) and NIH will be actively engaged in the activity. Staff of HPSIU and the Ministry will also be engaged in the activity.

Sustainability: Capacity Building, Institutionalisation, and/or Transition Planning
Capacity Building: Targeted trainings, on-the-job mentoring, and practical guidance will strengthen NIH/NHDC and provincial capacity to operate, maintain, and routinely use NDHH, including interoperability, analytics, and decision-support functions.

Institutionalisation: NDHH to be embedded within existing government HIS structures through formal governance arrangements, standard operating procedures, data-sharing agreements, and alignment with national data and interoperability standards.

Transition Planning: A phased handover will transfer full operational ownership to NIH/NHDC and provinces, supported by complete documentation, system access transfer, and formal validation of government readiness at the end of Phase II.

Responsibilities

The AI/Machine Learning Specialist/Developer will be responsible for:
<ul>
<li>Inception Report &amp; detailed Workplan including integrated Gantt chart</li>
<li>Provincial onboarding, Governance, Integration and Go-live of the Remaining Two Provinces</li>
<li>Practice Hub V1.0 (AI-enabled advanced analytics)</li>
<li>Security Hardening, Documentation, Capacity Building, and Operational Handover</li>
<li>Final Phase II report</li>
</ul>
Timeline and Days

The level of effort (LOE) for the role is 30 days from May 2026 &ndash; Sep 2026.

Requirement

Technical Expertise
<ul>
<li>Minimum 10 years of experience in machine learning and natural language processing.</li>
<li>Experience with OpenAI, Google AI APIs, and model integration.</li>
<li>Experience applying AI in healthcare/public health data systems</li>
</ul>
Competencies
<ul>
<li>Innovative Thinking</li>
<li>Strong algorithmic and coding skills and data literacy</li></ul></div>

FED TA DigitalHub - Mid STTA AI / Machine Learning Specialist/Developer

Datamatics Global Services Ltd

<div>Department: IT Development 
Reports To: AI Engineering Lead<h2 class="jobSectionHeader">
Position Summary</h2>
The AI Engineer is responsible for designing, developing, and deploying AI-powered applications and systems that integrate with Android, iOS, and web platforms. The role involves working on applied machine learning, automation, and intelligent features that enhance customer experience and operational efficiency. The ideal candidate should have strong expertise in mobile development, backend engineering (Python), and web technologies, along with hands-on experience in building, testing, and scaling AI-driven solutions.<h2 class="jobSectionHeader">
Duties &amp; Responsibilities</h2><ul><li>
Design, build, and maintain AI-driven features for mobile (Android/iOS) and web platforms</li><li>
Collaborate with cross-functional teams (mobile, backend, product) to integrate AI capabilities such as recommendation engines, chatbots, fraud detection models, and personalization systems</li><li>
Develop machine learning models, perform data preprocessing, and deploy production-ready models using Python frameworks (TensorFlow, PyTorch, Scikit-learn)</li><li>
Write clean, modular, and scalable code using engineering best practices (SOLID principles, Clean Architecture)</li><li>
Build and manage APIs and microservices for AI functionality using Flask, FastAPI, or Node.js</li><li>
Work closely with UX/UI and product teams to convert insights into intelligent user experiences</li><li>
Conduct model performance optimization, A/B testing, and evaluation for real-world accuracy and reliability</li><li>
Integrate AI systems with cloud infrastructure (AWS, GCP, or Azure) ensuring compliance, governance, and security standards</li><li>
Participate in code reviews, peer-learning sessions, and agile ceremonies such as scrums and sprint reviews</li><li>
Stay updated with emerging AI, ML, GenAI, and automation trends to propose innovative solutions</li><li>
Demonstrate Behaviors &mdash; Be Respectful, Keep Promises, Always Explore, Create Together &mdash; in daily work practices</li></ul><h2 class="jobSectionHeader">
Direct Reports</h2><ul><li>
None</li></ul><h2 class="jobSectionHeader">
Role Relationships</h2><h3 class="jobSectionHeader">
Internal</h3><ul><li>
IT Development</li><li>
Information Security</li><li>
Operations</li><li>
Internal Audit</li></ul><h3 class="jobSectionHeader">
External</h3><ul><li>
Vendors</li></ul><h2 class="jobSectionHeader">
Knowledge &amp; Experience</h2><h3 class="jobSectionHeader">
Education</h3><ul><li>
BS/MS in Computer Science, Artificial Intelligence, Data Science, or a related field</li></ul><h3 class="jobSectionHeader">
Experience</h3><ul><li>
3+ years of software development experience</li><li>
Proven experience in AI/ML projects</li><li>
Hands-on experience with mobile development (Android/iOS), Python engineering, and web technologies</li></ul><h2 class="jobSectionHeader">
Competencies</h2><h3 class="jobSectionHeader">
AI / ML</h3><ul><li>
Flowise, PyTorch, OpenAI APIs, N8N</li><li>
Machine Learning &amp; Applied AI development</li><li>
Data preprocessing, model training, deployment</li></ul><h3 class="jobSectionHeader">
Programming</h3><ul><li>
Python</li><li>
Swift / Kotlin</li><li>
JavaScript / TypeScript</li></ul><h3 class="jobSectionHeader">
Cloud &amp; DevOps</h3><ul><li>
AWS / GCP</li><li>
Docker, CI/CD pipelines</li></ul><h3 class="jobSectionHeader">
Version Control</h3><ul><li>
Git</li></ul><h3 class="jobSectionHeader">
Data Engineering</h3><ul><li>
Pandas, NumPy, SQL</li><li>
ETL processes &amp; data pipelines</li></ul><h3 class="jobSectionHeader">
Mobile &amp; Web Development</h3><ul><li>
Android Studio</li><li>
Xcode</li><li>
React / Next.js</li><li>
Flutter (optional)</li></ul><h3 class="jobSectionHeader">
API &amp; Backend</h3><ul><li>
REST, GraphQL</li><li>
Flask / FastAPI</li><li>
Node.js</li></ul><h3 class="jobSectionHeader">
Security &amp; Compliance</h3><ul><li>
Secure coding standards</li><li>
Data privacy and compliance frameworks</li></ul>
UUnhBo8fyy</div>

AI Engineering Lead

Mercurial Minds (Pvt) Ltd

Job Description &ndash; AI EngineerCompany: Mercurial Minds (Pvt.) Ltd. Location: Islamabad (On-site) Employment Type: Full-time Experience Required: 2&ndash;4 years (AI / Machine Learning / Applied Data Science)Company OverviewMercurial Minds (Pvt.) Ltd. is a forward-thinking technology and digital innovation company delivering end-to-end software solutions that help businesses transform, scale, and innovate through modern digital technologies. Our expertise spans cloud-native platforms, data-driven systems, AI-powered products, and large-scale digital transformation initiatives across telecom, media-tech, and enterprise environments.At Mercurial Minds, we focus on building intelligent, scalable, and production-ready systems that create measurable business value. We foster a culture of innovation, technical excellence, and continuous learning.Role OverviewWe are seeking an experienced and highly motivated AI Engineer to design, build, and deploy intelligent systems powered by modern AI technologies, including large language models (LLMs), machine learning, and advanced data pipelines.This role involves working on end-to-end AI solutions such as agentic systems, retrieval-augmented generation (RAG), semantic search, question-answering systems, summarization engines, recommendation systems, AI-powered matching platforms, and production-grade analytics solutions.The ideal candidate combines strong AI engineering expertise with applied machine learning knowledge and hands-on experience deploying scalable AI solutions in production environments.Key Responsibilities<ul><li>Design, develop, and optimize end-to-end AI-powered applications</li><li>Build and maintain RAG pipelines using vector databases, embeddings, and document processing workflows</li><li>Implement semantic search, filtering, and ranking systems across large and multi-source datasets</li><li>Fine-tune, evaluate, and deploy open-source LLMs and other machine learning models</li><li>Design scalable data pipelines for ingestion, cleaning, transformation, and storage</li><li>Deploy models and AI services using cloud infrastructure and containerization technologies</li><li>Collaborate with product, backend, and frontend teams to integrate AI capabilities into applications</li><li>Monitor model performance, latency, and operational costs, and continuously optimize system quality</li></ul>Required Skills &amp; Qualifications<ul><li>Bachelor&rsquo;s degree (BS) in Computer Science, Artificial Intelligence, Data Science, or a related field</li><li>Strong proficiency in Python programming and software engineering best practices</li><li>Hands-on experience with agentic and LLM frameworks such as LangChain, LlamaIndex, LangGraph, CrewAI, or similar</li><li>Experience working with vector databases (Pinecone, Weaviate, Milvus, FAISS, Chroma, etc.)</li><li>Solid understanding of NLP, embeddings, transformers, and semantic similarity techniques</li><li>Experience deploying models using Docker and cloud platforms (AWS, Azure, or GCP)</li><li>Familiarity with REST APIs and microservices architectures</li><li>Knowledge of data processing libraries (Pandas, NumPy) and machine learning frameworks (Scikit-learn, PyTorch, or TensorFlow)</li><li>Experience with model evaluation, prompt engineering, and performance optimization</li><li>Understanding of the full ML lifecycle including training, validation, deployment, and monitoring</li></ul>Nice to Have<ul><li>Experience fine-tuning open-source models (LoRA, PEFT, quantization)</li><li>Knowledge of MLOps tools such as MLflow, Weights &amp; Biases, Airflow, or Kubeflow</li><li>Background in data science or advanced analytics</li><li>Familiarity with graph databases or knowledge graphs</li><li>Experience building high-availability production systems</li><li>Master&rsquo;s degree (MS) in Computer Science, Artificial Intelligence, Data Science, or related field</li><li>Strong hands-on project experience in real-world AI applications</li></ul>What We Offer<ul><li>Opportunity to work on real-world, high-impact AI solutions</li><li>Exposure to cutting-edge AI and LLM technologies</li><li>Collaborative and fast-growing engineering environment</li><li>Competitive compensation and career growth opportunities</li></ul>Ideal Candidate ProfileYou are someone who enjoys taking AI ideas from concept to production, understands both theoretical foundations and practical implementation of modern AI systems, and actively stays current with rapidly evolving AI and LLM ecosystems.Job Type: Full-timeAbility to commute/relocate:<ul><li>Islamabad: Reliably commute or planning to relocate before starting work (Preferred)</li></ul>Application Question(s):<ul><li>Do you have hands-on experience building or deploying LLM-based applications (e.g., RAG pipelines, semantic search, or agentic systems) in a production or real-world environment?</li></ul><ul><li> Have you worked with vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus, Chroma) and deployed AI/ML models using cloud platforms or Docker?</li></ul>Location:<ul><li>Islamabad (Required)</li></ul>Work Location: In person

AI Engineer

<div>Job Title: Agentic AI Engineer 
Location: Islamabad, Pakistan (Onsite) 
Experience: 7&ndash;8 Years 
Employment Type: Full-Time<h3 class="jobSectionHeader">
Job Overview</h3>
We are looking for a highly skilled Agentic AI Engineer to design, build, and deploy intelligent AI agents capable of autonomous decision-making, workflow execution, and tool integration. The ideal candidate will have strong experience in AI/ML systems, LLM-based applications, and building multi-agent or autonomous AI solutions that solve real business problems.<h3 class="jobSectionHeader">
Key Responsibilities</h3><ul><li>
Design and develop agentic AI systems that can plan, reason, and execute tasks autonomously.</li><li>
Build and optimize applications using Large Language Models (LLMs) and advanced AI frameworks.</li><li>
Develop multi-agent architectures for complex workflows and decision-making processes.</li><li>
Integrate AI agents with enterprise tools, APIs, databases, and internal platforms.</li><li>
Implement memory, planning, retrieval, and tool-use capabilities in AI agents.</li><li>
Work closely with product, engineering, and business teams to identify AI automation opportunities.</li><li>
Ensure scalability, security, and performance of AI systems in production.</li><li>
Continuously evaluate new AI frameworks, models, and techniques to improve solutions.</li></ul><h3 class="jobSectionHeader">
Required Skills &amp; Experience</h3><ul><li>
7&ndash;8 years of experience in AI/ML, software engineering, or applied AI development.</li><li>
Strong programming experience in Python.</li><li>
Hands-on experience with LLMs and AI frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, or similar.</li><li>
Experience with RAG architectures, vector databases, and embeddings.</li><li>
Familiarity with OpenAI, open-source LLMs, or similar AI model ecosystems.</li><li>
Experience building AI agents, automation workflows, or intelligent assistants.</li><li>
Strong understanding of APIs, microservices, and cloud platforms (AWS, GCP, or Azure).</li><li>
Experience with Docker, CI/CD, and scalable system design.</li></ul><h3 class="jobSectionHeader">
Preferred Qualifications</h3><ul><li>
Experience with multi-agent systems and autonomous AI workflows.</li><li>
Knowledge of prompt engineering, model evaluation, and AI safety.</li><li>
Familiarity with vector databases such as Pinecone, Weaviate, or FAISS.</li><li>
Experience working in AI startups or advanced R&amp;D environments.</li><li>
Background in Computer Science, AI, Data Science, or related field.</li></ul><h3 class="jobSectionHeader">
What We Offer</h3><ul><li>
Opportunity to work on cutting-edge AI and autonomous systems.</li><li>
Competitive salary and growth opportunities.</li><li>
Collaborative and innovation-driven work environment.</li><li>
Exposure to global AI projects and modern technology stack.</li></ul>
Hr0rUNuBPn</div>

Agentic AI Engineer

Datamatics Technologies

<div>
 
 
 Department:
 
 IT Development
 
 
 Reports To:
 
 &nbsp; AI Engineering Lead
 
 
 Position Summary
 
 
 The AI Engineer is responsible for designing, developing, and deploying AI-powered applications and systems that integrate with Android, iOS, and web platforms. The role involves working on applied machine learning, automation, and intelligent features that enhance customer experience and operational efficiency. The ideal candidate should have strong expertise in mobile development, backend engineering (Python), and web technologies, along with hands-on experience in building, testing, and scaling AI-driven solutions.
 
 
 Duties &amp; Responsibilities
 
 <ul>
 <li>
 
 Design, build, and maintain AI-driven features for mobile (Android/iOS) and web platforms
 
 </li>
 <li>
 
 Collaborate with cross-functional teams (mobile, backend, product) to integrate AI capabilities such as recommendation engines, chatbots, fraud detection models, and personalization systems
 
 </li>
 <li>
 
 Develop machine learning models, perform data preprocessing, and deploy production-ready models using Python frameworks (TensorFlow, PyTorch, Scikit-learn)
 
 </li>
 <li>
 
 Write clean, modular, and scalable code using engineering best practices (SOLID principles, Clean Architecture)
 
 </li>
 <li>
 
 Build and manage APIs and microservices for AI functionality using Flask, FastAPI, or Node.js
 
 </li>
 <li>
 
 Work closely with UX/UI and product teams to convert insights into intelligent user experiences
 
 </li>
 <li>
 
 Conduct model performance optimization, A/B testing, and evaluation for real-world accuracy and reliability
 
 </li>
 <li>
 
 Integrate AI systems with cloud infrastructure (AWS, GCP, or Azure) ensuring compliance, governance, and security standards
 
 </li>
 <li>
 
 Participate in code reviews, peer-learning sessions, and agile ceremonies such as scrums and sprint reviews
 
 </li>
 <li>
 
 Stay updated with emerging AI, ML, GenAI, and automation trends to propose innovative solutions&nbsp;
 
 </li>
 <li>
 
 Demonstrate Behaviors &mdash;
 
 Be Respectful, Keep Promises, Always Explore, Create Together
 
 &mdash; in daily work practices
 
 </li>
 </ul>
 
 Direct Reports
 
 <ul>
 <li>
 
 None
 
 </li>
 </ul>
 
 Role Relationships
 
 
 Internal
 
 <ul>
 <li>
 
 IT Development
 
 </li>
 <li>
 
 Information Security
 
 </li>
 <li>
 
 Operations
 
 </li>
 <li>
 
 Internal Audit
 
 </li>
 </ul>
 
 External
 
 <ul>
 <li>
 
 Vendors
 
 </li>
 </ul>
 
 Knowledge &amp; Experience
 
 
 Education
 
 <ul>
 <li>
 
 BS/MS in Computer Science, Artificial Intelligence, Data Science, or a related field
 
 </li>
 </ul>
 
 Experience
 
 <ul>
 <li>
 
 3+ years of software development experience
 
 </li>
 <li>
 
 Proven experience in AI/ML projects
 
 </li>
 <li>
 
 Hands-on experience with mobile development (Android/iOS), Python engineering, and web technologies
 
 </li>
 </ul>
 
 Competencies
 
 
 AI / ML
 
 <ul>
 <li>
 
 Flowise, PyTorch, OpenAI APIs, N8N
 
 </li>
 <li>
 
 Machine Learning &amp; Applied AI development
 
 </li>
 <li>
 
 Data preprocessing, model training, deployment
 
 </li>
 </ul>
 
 Programming
 
 <ul>
 <li>
 
 Python
 
 </li>
 <li>
 
 Swift / Kotlin
 
 </li>
 <li>
 
 JavaScript / TypeScript
 
 </li>
 </ul>
 
 Cloud &amp; DevOps
 
 <ul>
 <li>
 
 AWS / GCP
 
 </li>
 <li>
 
 Docker, CI/CD pipelines
 
 </li>
 </ul>
 
 Version Control
 
 <ul>
 <li>
 
 Git
 
 </li>
 </ul>
 
 Data Engineering
 
 <ul>
 <li>
 
 Pandas, NumPy, SQL
 
 </li>
 <li>
 
 ETL processes &amp; data pipelines
 
 </li>
 </ul>
 
 Mobile &amp; Web Development
 
 <ul>
 <li>
 
 Android Studio
 
 </li>
 <li>
 
 Xcode
 
 </li>
 <li>
 
 React / Next.js
 
 </li>
 <li>
 
 Flutter (optional)
 
 </li>
 </ul>
 
 API &amp; Backend
 
 <ul>
 <li>
 
 REST, GraphQL
 
 </li>
 <li>
 
 Flask / FastAPI
 
 </li>
 <li>
 
 Node.js
 
 </li>
 </ul>
 
 Security &amp; Compliance
 
 <ul>
 <li>
 
 Secure coding standards
 
 </li>
 <li>
 
 Data privacy and compliance frameworks
 
 </li>
 </ul>
</div>

ImagineArt

<div><h3 class="jobSectionHeader">Job Title: React Developers Advocate (Youtube Face)</h3>
Department: Creative
Location: On-Site (NSTP, H12, Islamabad)<h3 class="jobSectionHeader">
About VYRO</h3>
VVyro is an AI-first creative technology company empowering creators worldwide. With 5M+ active users every month and 20+ AI-powered apps, we help millions create, edit, and design across images, videos, and digital media&mdash;faster and more intuitively.
ImagineArt, Vyro&rsquo;s flagship generative AI platform, enables artists and designers to create high-quality visual art from simple text prompts, making creativity more accessible and limitless.
Powered by AI and Machine Learning, Vyro&rsquo;s products remove friction from the creative process while unlocking new possibilities for creators at every level.
We are an 8-figure, fully bootstrapped company built by a focused team of builders&mdash;Vyronauts&mdash;who move fast, take ownership, and build with long-term impact.
We&rsquo;re shaping the future of AI-powered creativity&mdash;and we&rsquo;re just getting started.
Job Summary
We&rsquo;re looking for a Developer Advocate who is comfortable being the public face on YouTube and passionate about educating developers through video content. In this role, you&rsquo;ll create technical videos, tutorials, demos, and walkthroughs that help developers understand, adopt, and build with our products.
You&rsquo;ll combine strong technical knowledge with on-camera presence&mdash;breaking down complex concepts into clear, engaging content. Beyond YouTube, you&rsquo;ll engage with the developer community, gather feedback, and work closely with product and engineering teams to improve developer experience and adoption.
This role is ideal for someone who enjoys teaching through video, building in public, and representing the product to a global developer audience.
Requirements:<ul><li>
Strong programming experience in one or more relevant languages (e.g., JavaScript, Python, etc.).</li><li>
Hands-on experience working with APIs, SDKs, or developer platforms.</li><li>
Proven ability to explain technical concepts clearly on camera.</li><li>
Experience creating YouTube or video-based technical content (tutorials, demos, explainers).</li><li>
Comfortable being the public-facing representative of a product or platform.</li><li>
Strong communication and storytelling skills tailored to developer audiences.</li><li>
Ability to script, plan, and structure educational video content.</li><li>
Familiarity with basic video recording and editing workflows.</li><li>
Experience engaging with developer communities through comments, forums, or social platforms.</li><li>
Ability to collaborate closely with product and engineering teams.</li><li>
Curiosity and willingness to stay updated with new technologies and developer trends.</li><li>
A portfolio, YouTube channel, or sample videos demonstrating technical teaching or advocacy.</li></ul><h3 class="jobSectionHeader">
Responsibilities</h3><ul><li>
Serve as the public YouTube face of the product, creating regular developer-focused video content.</li><li>
Plan, script, and record technical tutorials, walkthroughs, demos, and explainers.</li><li>
Break down complex technical concepts into clear, engaging, and educational videos.</li><li>
Showcase new features, APIs, SDKs, and updates through hands-on YouTube content.</li><li>
Build demo projects and sample applications to support video content.</li><li>
Engage with developers through YouTube comments, community posts, and live sessions.</li><li>
Collaborate with product and engineering teams to align content with launches and roadmap updates.</li><li>
Gather feedback from YouTube and community interactions and share insights with internal teams.</li><li>
Maintain and improve developer documentation by supporting it with video explanations.</li><li>
Track YouTube performance metrics (views, engagement, watch time) and optimize content accordingly.</li><li>
Represent the product in live streams, AMAs, webinars, or virtual events.</li><li>
Stay updated on developer trends, tools, and YouTube best practices to continuously improve content quality.</li></ul><h3 class="jobSectionHeader">
Benefits</h3><ul><li>
Quarterly Bonuses</li><li>
Competitive compensation and comprehensive benefits package</li><li>
Medical Insurance (IPD/OPD)</li><li>
Company Sponsored Lunch</li><li>
Free Product Subscriptions</li><li>
Yearly Performance-Based Increments</li><li>
Paid Leaves</li><li>
EOBI</li></ul><h3 class="jobSectionHeader">
Company Culture</h3><ul><li>
Impact: Opportunity to work on innovative AI products like ImagineArt, shaping the future of creativity and user interaction.</li><li>
Team: Be part of a passionate, fast-moving team that values innovation and data-driven decisions.</li></ul>
Growth: A culture where learning, growth, and experimenting with new ideas are deeply encouraged.</div>

Developer's Advocate (YouTube Face)

RocketDevs

<div>
 
 RocketDevs empowers software engineers by bridging talent with global tech opportunities. We connect skilled developers with innovative projects, fostering an inclusive tech community.
 
 
 
 
 
 We are seeking a
 
 AI Engineer
 
 with a strong focus on
 
 AI systems and agent development
 
 to join our team and work on client projects that leverage modern AI capabilities. This is a
 
 full-time, remote position
 
 focused on building intelligent, scalable backend systems and AI-powered agents for global clients.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design, build, and maintain backend systems that power AI-driven applications.
 </li>
 <li>
 Develop and deploy
 
 AI agents
 
 capable of reasoning, planning, tool usage, and multi-step workflows.
 </li>
 <li>
 Integrate Large Language Models (LLMs) and AI APIs (e.g., OpenAI, Anthropic, Hugging Face) into backend services.
 </li>
 <li>
 Build and manage RESTful or GraphQL APIs for AI-powered features.
 </li>
 <li>
 Design data pipelines for storing prompts, embeddings, agent memory, and model outputs.
 </li>
 <li>
 Implement vector search and retrieval systems (e.g., embeddings, RAG pipelines).
 </li>
 <li>
 Optimize AI workflows for performance, cost, and reliability.
 </li>
 <li>
 Handle authentication, authorization, and secure access to AI services.
 </li>
 <li>
 Collaborate in architecture discussions, code reviews, and sprint planning.
 </li>
 <li>
 Explore and implement AI tooling to improve developer productivity and client outcomes.
 </li>
 </ul>
 
 
 
 
 
 Qualifications
 
 
 <ul>
 <li>
 Strong software engineering experience with
 
 Python (FastAPI, Flask, Django)
 
 or
 
 Node.js (Express, NestJS)
 
 .
 </li>
 <li>
 Hands-on experience integrating
 
 LLMs or AI APIs
 
 into production systems.
 </li>
 <li>
 Experience building or experimenting with
 
 AI agents
 
 , including:
 </li>
 </ul>
 <ol>
 <li>
 Tool calling / function calling
 </li>
 <li>
 Multi-step reasoning or workflows
 </li>
 <li>
 Agent memory or state management
 </li>
 </ol>
 <ul>
 <li>
 Solid understanding of API design, async processing, and background jobs.
 </li>
 <li>
 Experience with databases such as:
 </li>
 </ul>
 <ol>
 <li>
 SQL (PostgreSQL - PgVector, MySQL)
 </li>
 <li>
 NoSQL (MongoDB)
 </li>
 <li>
 Vector databases (e.g., Pinecone, Weaviate, FAISS, Elasticsearch)
 </li>
 <li>
 Familiarity with Redis or similar caching layers.
 </li>
 </ol>
 <ul>
 <li>
 Experience with Git &amp; GitHub, Docker, and basic CI/CD workflows.
 </li>
 <li>
 Experience with
 
 web scraping and document parsing (HTML, PDFs).
 
 </li>
 <li>
 A
 
 deployed project
 
 (personal or professional) demonstrating an AI-powered backend system or agent is required.
 </li>
 </ul>
 
 
 
 
 
 Nice to Have
 
 
 <ul>
 <li>
 Experience with RAG (Retrieval-Augmented Generation) systems.
 </li>
 <li>
 Familiarity with agent frameworks (e.g., LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen).
 </li>
 <li>
 Experience with embeddings, prompt versioning, and evaluation.
 </li>
 <li>
 Familiarity with
 
 Model Context Protocol (MCP)
 
 or similar standards for connecting AI models to tools, data sources, and environments.
 </li>
 <li>
 Experience building or integrating
 
 automation workflows
 
 for AI systems (e.g., background jobs, task orchestration, event-driven workflows, or tools like Temporal, Airflow, n8n, Zapier).
 </li>
 <li>
 Knowledge of Kubernetes, serverless platforms, or Supabase.
 </li>
 <li>
 Understanding of AI safety, cost optimization, and observability.
 </li>
 <li>
 Familiarity with AI-assisted development tools or platforms.
 </li>
 </ul>
 
 
 
 
 
 Hiring Process
 
 
 
 We ensure a fair and transparent process for every applicant:
 
 
 
 Apply &rarr; Take a Compulsory 30-minute Assessment &rarr; 30-minute Onboarding Interview &rarr; Final interview &amp; selection
 
 
 
 
 
 
 
 Note
 
 
 <ul>
 <li>
 The assessment is mandatory. Please apply only if you&rsquo;re willing to take it.
 </li>
 <li>
 Having a deployed AI-powered backend project (personal or professional) is a must.
 </li>
 </ul>
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