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senior full stack developer Jobs in Islamabad

senior full stack developer

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ai engineer (2+ years of experience) Jobs in Islamabad

ai engineer (2+ years of experience)

senior lead software engineer

eMumba

<div><div><div><div><div>As Emumba&rsquo;s <b>Senior DevOps Engineer</b>, you&rsquo;ll play a pivotal role in designing and operating highly available, scalable, and secure cloud platforms that power real-world applications.<br>
</div><div>This is about building automation-first ecosystems, advocating DevOps culture, and ensuring our engineering practices align with long-term business impact. You&rsquo;ll work closely with customers and cross-functional teams to transform requirements into resilient, production-grade infrastructure.<br>
</div><div>This role demands ownership, strategic thinking, and a passion for continuous improvement.</div></div></div>
</div><h2 class="jobSectionHeader"><b>Must-Have Qualifications
</b></h2><div><div><div><ul><li>5+ years of hands-on experience in DevOps / Cloud Engineering roles</li>
<li>Strong experience designing highly available, fault-tolerant, and scalable systems in <b>AWS</b>
</li><li>Deep understanding of the <b>AWS Well-Architected Framework</b> (six pillars)</li>
<li>Experience designing CI/CD pipelines for dev, staging, and production environments (GitHub CI, ArgoCD, Jenkins preferred)</li>
<li>Hands-on expertise with <b>Infrastructure as Code</b> (Terraform or AWS CloudFormation)</li>
<li>Experience with container orchestration, preferably <b>Amazon EKS</b>
</li><li>Strong knowledge of monitoring and logging tools (Prometheus, Grafana, ELK)</li>
<li>Solid understanding of cloud security best practices</li>
<li>Proven analytical and problem-solving skills</li>
<li>Ability to mentor and contribute to team growth</li></ul><div><br>
<br>
</div></div></div></div><h2 class="jobSectionHeader"><b>What You&rsquo;ll Do
</b></h2><div><div><div><div><b>Cloud Architecture &amp; Infrastructure</b>
</div><ul><li>Design and deploy highly available, fault-tolerant applications in AWS</li>
<li>Optimize cloud infrastructure according to the AWS Well-Architected Framework</li>
<li>Implement Infrastructure as Code using Terraform or CloudFormation</li>
</ul><div><b>CI/CD &amp; Automation</b>
</div><ul><li>Design and manage CI/CD pipelines across multiple environments</li>
<li>Drive automation-first initiatives across engineering workflows</li>
<li>Utilize configuration management tools such as Ansible, Puppet, or Chef</li>
</ul><div><b>Reliability &amp; Observability</b>
</div><ul><li>Implement monitoring and logging stacks (Prometheus, Grafana, ELK)</li>
<li>Strengthen infrastructure security and resilience</li>
<li>Proactively troubleshoot and resolve production issues</li>
</ul><div><b>Leadership &amp; Cultural Advocacy</b>
</div><ul><li>Champion DevOps culture and continuous improvement practices</li>
<li>Mentor engineers through coaching, feedback, and knowledge sharing</li>
<li>Translate customer requirements into scalable, long-term infrastructure solutions</li>
<li>Align DevOps practices with broader business and project goals</li>
</ul><p>Nice-to-Have</p><ul>
<li>Experience leading teams in customer-facing projects</li>
<li>Exposure to AI tooling in DevOps or LLMOps</li>
<li>AWS Professional Certifications (Solutions Architect Pro, DevOps Pro)</li>
<li>Kubernetes certifications (CKA, CKAD)</li>
<li>Terraform certification (HashiCorp Terraform Associate)</li>
</ul></div></div></div><h2 class="jobSectionHeader"><b>What&rsquo;s In It for You
</b></h2><div><div><div><ul><li>Ownership of impactful cloud and platform initiatives</li>
<li>Work alongside high-performing engineers in a collaborative environment</li>
<li>Exposure to enterprise-scale customer projects</li>
<li>Opportunities to lead through expertise and influence through execution</li>
</ul></div></div></div><h2 class="jobSectionHeader"><b>About Emumba
</b></h2><div><div>Emumba is a global engineering and consulting company with strengths in software development and an established AWS cloud practice focused on Data and GenAI. For 15 years, our teams across the US, the UAE, and Pakistan have earned trust through quality delivery and ownership of work. We look for people who value the culture they work in as much as the craft they bring to it.</div></div></div><p></p>

Senior DevOps Engineer

Skylabs AI

<div><p><b>About Us</b></p><p>
At SkyLabs AI Inc., we are at the forefront of the artificial intelligence revolution. As a US-headquartered company, we conduct applied research on AI for intelligent reasoning. We specialize in complex neurosymbolic AI to solve intricate problems within software engineering. Our team is composed of world-class researchers and engineers dedicated to building the platforms and intelligent agents that will power the next generation of software. If you are passionate about building truly intelligent systems and want to make a lasting impact, join us.</p><p></p><p><b>
The Role</b></p><p>
We are seeking an exceptional <b>Senior AI Research Engineer</b> with a strong focus on <b>training and improving LLMs across the full lifecycle</b>&mdash;from <b>Domain‑Adaptive Pretraining</b> to <b>Supervised Fine‑Tuning (SFT)</b>, <b>RL/RLVR</b>, and advanced post‑training techniques (e.g., reward modeling, preference optimization, RL‑VR style workflows). You will lead hands‑on training efforts, contribute to research direction, and build robust pipelines for data, training, evaluation, and deployment.</p><p>
You should have <b>in‑depth understanding of LLM internals</b> (attention/MLP dynamics, normalization, optimization behavior, scaling laws), and modern architectures including <b>Mixture of Experts (MoE)</b> and other frontier design choices. You will work closely with product and platform teams to translate research ideas into performant systems.</p><p><b>
Requirements</b></p><p><b>
Key Responsibilities</b></p><ul>
<li><b>
Lead the team of AI Engineers/Researchers
</b></li><li><b>Train and iterate on LLMs end-to-end</b> across DAPT/CPT, SFT, and RL-based post-training (preference optimization, reward modeling, verifiable rewards, policy optimization, and related variants).
</li><li><b>Design training recipes</b>: tokenization strategy, curriculum/sampling, batch/sequence packing, optimizer + scheduler choices, stability techniques, and hyperparameter search.
</li><li><b>Architect and implement efficient training systems</b> using distributed training (data/tensor/pipeline parallelism), FSDP/ZeRO, activation checkpointing, mixed precision, and throughput optimization.
</li><li><b>Develop and maintain LLM data pipelines</b>: large-scale data ingestion, filtering, deduplication, contamination checks, domain balancing, safety filtering, and dataset versioning.
</li><li><b>Perform deep EDA and root-cause analysis</b> for training/eval regressions (loss spikes, instability, alignment drift, memorization, toxicity, domain overfitting), and implement mitigations.
</li><li><b>Build evaluation and benchmarking suites</b>: offline metrics, human preference pipelines, automatic evals, domain-specific test sets, adversarial probing, and model behavior tracking over time.
</li><li><b>Apply and advance model compression and efficiency</b>: distillation from LLMs, quantization-aware considerations, pruning/sparsity (including MoE routing behavior), and inference-time optimization tradeoffs.
</li><li><b>Implement and operationalize LLMOps</b>: experiment tracking, reproducible runs, model registry, training telemetry, artifact management, CI for training configs, and safe rollout strategies.
</li><li><b>Leverage AI coding tools</b> (e.g., Cursor, Copilot) to accelerate development while maintaining strong engineering rigor, testability, and code review standards.
</li><li><b>Collaborate cross-functionally</b> with platform, infra, and product teams to integrate trained models into agentic/production pipelines (retrieval, tool use, evaluation gates, monitoring).
</li><li><b>Stay current with the field</b> and translate new ideas (architectures, post-training, data strategies, evals) into internal experiments and improvements.
</li></ul><p></p><p><b>Qualifications &amp; Skills</b></p><ul>
<li>
<b>5+ years</b> in ML engineering / applied research, with <b>significant hands-on experience training large models</b>, especially LLMs.
</li><li>Strong practical knowledge of <b>transformer internals</b> and modern variations (MoE, routing, load balancing, attention variants, normalization choices, long-context strategies).
</li><li>Demonstrated experience with <b>DAPT/CPT</b>, <b>SFT</b>, and <b>RL-based post-training</b> (e.g., reward modeling, preference datasets, verifiable rewards, policy optimization). Ability to reason about why a method works and when it fails.
</li><li>Excellent understanding of <b>data science fundamentals</b>: EDA, dataset design, bias/contamination, sampling strategies, and error analysis.
</li><li>Proven ability to <b>root-cause and debug</b> training instabilities and performance regressions (numerics, data issues, infra bottlenecks, config drift).
</li><li>Expert-level programming in <b>Python</b>, with strong software engineering fundamentals (data structures, algorithms, systems thinking).
</li><li>Experience with key tooling such as <b>PyTorch</b>, distributed training frameworks (FSDP/DeepSpeed/ZeRO), and training orchestration.
</li><li>Familiarity with <b>LLMOps</b>: tracking (e.g., W&amp;B/MLflow), dataset versioning, reproducibility, deployment constraints, and monitoring of model behavior.
</li><li>Comfortable building <b>agentic pipelines</b> around LLMs (evaluation agents, data generation/labeling loops, model-in-the-loop distillation, automated red-teaming).
</li><li>Bonus: publications, open-source contributions, or demonstrated leadership in shipping LLM training improvements.
</li></ul><p></p><p><b>Who You Are</b></p><p>
You&rsquo;re a pragmatic researcher-engineer: you can read papers, run experiments, and also build the training and data systems that make results reproducible and shippable. You&rsquo;re meticulous about data and measurement, fast at debugging, and comfortable making tradeoffs between quality, cost, and timeline. You communicate clearly, mentor others, and thrive in an environment where you&rsquo;re trusted to drive big initiatives.</p><p><b>
Benefits</b></p><ul>
<li>
Salaries in USD (income tax exemptions)</li>
<li>Work in Pakistan Timezone</li>
<li>Comprehensive health allowance</li>
<li>Monthly team events and activities</li>
<li>Relocation allowance (if you're moving to Islamabad)</li>
<li>Opportunity to work with top minds in the industry and academia</li>
<li>Startup culture where ideas are heard at all levels</li>
<li>Adequate annual, sick, casual and parental leaves</li></ul></div>

Senior AI Research Engineer

Rapid Labs

<p><b>Senior Full Stack Machine Learning Engineer</b></p><p><b>About Rapid Labs</b></p><p>Rapid Labs is a US based AI startup focused on building production ready, practical machine learning systems that solve real operational problems. We partner with businesses to design and deploy AI solutions that deliver measurable outcomes, not experiments or hype driven prototypes.</p><p>Our culture values ownership, engineering excellence, and clear thinking. We work in fast moving, ambiguous environments where strong fundamentals and real world execution matter more than buzzwords.</p><p><b>About the Role</b></p><p>We are hiring a Senior Full Stack Machine Learning Engineer to own the design, development, and operation of production grade machine learning systems. This role is centered on applied and classical machine learning, not LLM only or prompt driven workflows.</p><p>You will work close to the problem space, translating messy operational and business challenges into reliable ML systems that run in production. This is a hands on role for engineers who enjoy building, deploying, and improving real systems in the cloud and taking responsibility for outcomes.</p><p><b>What You Will Do</b></p><p><b>Build and Own End to End ML Systems</b></p><ul><li>Own the full machine learning lifecycle from raw data to deployed, monitored, and continuously improving models</li><li>Design predictive, prescriptive, and optimization solutions for use cases such as manufacturing operations, predictive maintenance, quality analytics, and supply chain efficiency</li><li>Apply classical ML and statistical methods including time series forecasting, anomaly detection, regression, classification, clustering, probabilistic modeling, and optimization</li></ul><p><b>Engineer Strong Data and Feature Pipelines</b></p><ul><li>Build reliable ETL and ELT pipelines for batch and near real time ML workloads</li><li>Perform exploratory data analysis to understand data quality, distributions, bias, and signal</li><li>Design feature pipelines and feature stores that keep training and inference consistent</li><li>Integrate data from APIs, databases, and event streams with strong validation, schema control, and observability</li></ul><p><b>Ship and Operate Production ML</b></p><ul><li>Deploy models as scalable services using APIs, batch jobs, or streaming inference</li><li>Implement monitoring for model performance, drift, data quality, and system health</li><li>Work closely with platform and software teams to deliver secure, reliable, and cost efficient systems</li><li>Help define and enforce MLOps standards including CI CD, versioning, reproducibility, and rollback strategies</li></ul><p><b>Lead Technically and Collaborate Effectively</b></p><ul><li>Turn ambiguous business problems into clear ML problem statements, success metrics, and delivery plans</li><li>Make sound technical decisions on model selection, evaluation methods, and trade offs</li><li>Communicate results, risks, and limitations clearly to stakeholders using dashboards, visualizations, and documentation</li><li>Mentor junior engineers and raise the bar for ML engineering practices at Rapid Labs</li></ul><p><b>What We Are Looking For</b></p><p><b>Must Have</b></p><ul><li>Seven or more years of experience across machine learning engineering, data engineering, and production systems</li><li>At least five years of hands on experience delivering end to end machine learning solutions in production</li><li>Strong depth in classical machine learning and applied statistics beyond generative AI focused work</li><li>Solid understanding of evaluation techniques, validation strategies, bias variance trade offs, and failure modes</li><li>Advanced Python skills for production ML including clean code, testing, packaging, and performance tuning</li><li>Strong SQL skills and experience designing data models for analytics and ML</li><li>Three or more years of cloud experience with GCP preferred and AWS acceptable</li><li>Hands on experience with BigQuery, Cloud Storage, Dataflow or Apache Beam, Airflow or Cloud Composer, and containerized deployments using Docker and Kubernetes or managed equivalents</li><li>Experience operationalizing ML using tools such as MLflow, CI CD pipelines, workflow orchestration, and monitoring systems</li><li>Proven ability to monitor, debug, and improve models after deployment including drift detection and retraining</li><li>Strong problem solving skills with the ability to translate business needs into ML outcomes</li><li>Clear and confident communication skills with both technical and non-technical stakeholders</li><li>Experience working with cross functional teams including engineering, operations, and product</li></ul><p><b>Nice to Have</b></p><ul><li>Experience in manufacturing, industrial systems, or supply chain domains</li><li>Ownership of a technical roadmap or AI product lifecycle from planning to delivery</li><li>GCP or AI and ML related professional certifications</li><li>Background in consulting or client facing roles</li><li>Some exposure to GenAI or LLMs is welcome when combined with strong classical ML fundamentals, with LLMs used as supporting components rather than the core focus</li></ul><p><b>Salary &amp; Benefits</b></p><ul><li>Competitive salary and fringe benefits.</li><li>Paid Time off</li><li>Leaves encashment</li><li>EOBI</li><li>Professional Development</li><li>Career Advancement</li><li>Team Building Activities</li><li>Innovative Work Environment</li><li>Work-Life Balance</li><li>Company trips</li><li>Wellness Programs</li><li>Performance based promotion</li></ul><p><b>Location: </b></p><p><b>Lahore Office, Islamabad Office, or Remote (Flexible)</b></p><p>This role offers flexibility in how you work. Candidates may choose to join our <b>Lahore office</b>, work from our <b>Islamabad office</b>, or operate <b>fully remote</b>, depending on what works best for them.</p><p><b>Office Hours: 05:00 PM to 02:00 AM (Monday to Friday) </b></p><p>Job Type: Full-time</p><p>Application Question(s):</p><ul><li>What is your current salary?</li><li>What is your expected salary?</li><li>What is the duration of your notice period in days?</li><li>Do you have 7+ years of experience as a Senior Full Stack Machine Learning Engineer?</li></ul><p>Experience:</p><ul><li>Senior Full Stack Machine Learning Engineer: 7 years (Preferred)</li></ul><p>Language:</p><ul><li>English fluently (Preferred)</li></ul><p>Work Location: In person</p>

Senior Full Stack Machine Learning Engineer

Devsinc

<div>
 We are looking for a Senior Software Engineer (AI/ML) who can design, build, and scale intelligent systems &mdash; from machine learning pipelines to advanced AI agents capable of reasoning, planning, and automation.
 <br/>
 <br/>
 You will work on building production-grade AI models, integrating LLMs and tools, and designing agent architectures that interact with APIs, databases, and workflows. The role blends applied ML expertise with strong backend engineering and product-focused problem-solving.
 <br/>
 <br/>
 <strong>
  Responsibilities:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design and build autonomous or semi-autonomous AI agents that can plan, reason, and interact with tools, APIs, or external systems
  </li>
  <li>
   Implement agentic frameworks (e.g., LangChain, LlamaIndex, CrewAI, or custom orchestration systems)
  </li>
  <li>
   leverage existing industry capabilities to deliver virtual assistant capabilities on top of xquic content including voice interactions
  </li>
  <li>
   Optimize reasoning and retrieval pipelines using embeddings, vector databases, and prompt engineering
  </li>
  <li>
   Develop, train, and fine-tune ML models using frameworks like PyTorch, TensorFlow, or scikit-learn
  </li>
  <li>
   Work on data preprocessing, feature engineering, and model evaluation for NLP, computer vision, or predictive tasks
  </li>
  <li>
   Build ML pipelines for training, deployment, and monitoring in production environments
  </li>
  <li>
   Collaborate with engineering teams to integrate AI components into backend systems and APIs
  </li>
  <li>
   Ensure scalable, maintainable codebases with CI/CD, observability, and cloud-native design (AWS/GCP/Azure)
  </li>
  <li>
   Contribute to technical architecture and design reviews for AI-driven features and platforms
  </li>
  <li>
   Stay current with the latest in LLMs, agent frameworks, and model architectures
  </li>
  <li>
   Prototype and evaluate new approaches for reasoning, tool use, and adaptive behavior in agents
  </li>
  <li>
   Share learnings and mentor peers in ML and AI development best practices
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelors Degree in Computer Science or related fields
  </li>
  <li>
   3+ years of experience
  </li>
  <li>
   Strong programming skills in Python (mandatory); proficiency with PyTorch,
  </li>
  <li>
   TensorFlow, or transformers-based models
  </li>
  <li>
   Experience in building or integrating AI agents (LangChain, LlamaIndex, CrewAI, custom frameworks)
  </li>
  <li>
   Strong grasp of ML model lifecycle &mdash; data processing, model training, evaluation, deployment, and monitoring
  </li>
  <li>
   Experience with cloud platforms (AWS/GCP/Azure) and containerization (Docker, Kubernetes)
  </li>
  <li>
   Familiarity with API integrations, microservices, and asynchronous systems
  </li>
  <li>
   Strong understanding of vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) and retrieval architectures
  </li>
  <li>
   Solid software engineering fundamentals &mdash; testing, version control, and system design
  </li>
  <li>
   Experience with LLM fine-tuning, prompt optimization, or RAG (Retrieval-Augmented Generation) systems
  </li>
  <li>
   Familiarity with multi-agent systems and coordination mechanisms
  </li>
  <li>
   Knowledge of MLOps tools (MLflow, Kubeflow, Sagemaker, Vertex AI)
  </li>
  <li>
   Experience in AI system observability, evaluation metrics, and continuous learning loops
  </li>
  <li>
   Exposure to reinforcement learning or self-improving agent architectures
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Benefits
  <br/>
  <br/>
 </strong>
 Provident Fund, Medical Inpatient Facility, Medical Outpatient Facility, Paid Overtime, In-house Subsidized Lunch &amp; Dinner, Gym Facility, Entertaining Activities, Interest Free Loan Facility, Advance Salaries and Sports Allowance.
</div>


Senior Software Engineer (AI/ML)

<div><div><div><div><div>We are looking for a highly skilled Senior Python Developer to work with us in the development of robust, scalable, and secure serverless applications on AWS. As a critical member of our engineering team, you will use your expertise in Python to design and build cloud-native applications that leverage the power of AWS serverless technologies.</div></div></div>
</div><h2 class="jobSectionHeader"><b>Key Responsibilities
</b></h2><div><div><div><ul><li><b>Serverless Application Development:</b> Design and develop AWS Lambda-based serverless applications and RESTful APIs using frameworks like Flask or FastAPI, integrated with AWS API Gateway.</li>
<li><b>Backend Logic and Event-Driven Architectures:</b> Build backend logic using Python for event-driven architectures with services like SNS, SQS, and Kinesis, while leveraging Python&rsquo;s libraries for data processing and file handling.</li>
<li><b>Asynchronous Programming:</b> Utilize asynchronous programming in Python (asyncio, aiohttp) to efficiently manage concurrent tasks in distributed environments.</li>
<li><b>Data Processing Pipelines</b>: Design and implement serverless data processing pipelines using Python for workflows with AWS services like S3, Lambda, and DynamoDB.</li>
<li><b>Optimization and Performance:</b> Optimize Python applications for performance and scalability by implementing caching mechanisms, asynchronous calls, and minimizing latency.</li>
<li><b>Testing, Debugging, and Monitoring:</b> Implement unit testing with PyTest, and use AWS CloudWatch, X-Ray, and other tools to monitor, log, debug, and troubleshoot applications.</li>
<li><b>Security and Authentication:</b> Ensure adherence to AWS security best practices (IAM, encryption, VPC), and implement authentication mechanisms using AWS Cognito or Python JWT libraries.</li>
<li><b>Collaboration and Mentorship:</b> Collaborate with DevOps teams for CI/CD integration using AWS CodePipeline, CodeBuild, or Jenkins, and mentor junior developers on best practices and architecture decisions.</li>
</ul></div></div></div><h2 class="jobSectionHeader"><b>Requirements
</b></h2><div><div><div><ul><li>Education: Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Software Engineering, or a related field.</li>
<li>Experience: 5+ years of hands-on experience in Python development, with a minimum of 2 years working on AWS Serverless solutions.</li>
<li>Python Expertise: Deep expertise in Python programming, with strong understanding of Python libraries, tools, and frameworks such as Flask, FastAPI, Pandas, and PyTest.</li>
<li>AWS Serverless Proficiency: Proven experience with AWS services like Lambda, API Gateway, DynamoDB, S3, Step Functions, and CloudFormation or AWS CDK.</li>
<li>Asynchronous and Concurrent Programming: Hands-on experience with asynchronous programming in Python and parallel task execution.</li>
<li>Testing and Debugging: Expertise in writing and executing unit tests using Python frameworks like PyTest and debugging complex serverless architectures.</li>
</ul></div></div></div><h2 class="jobSectionHeader"><b>About Emumba
</b></h2><div><div>Emumba is a global engineering and consulting company with strengths in software development and an established AWS cloud practice focused on Data and GenAI. For 15 years, our teams across the US, the UAE, and Pakistan have earned trust through quality delivery and ownership of work. We look for people who value the culture they work in as much as the craft they bring to it.</div></div></div><p></p>

Senior Python Engineer

NorthBay Solutions

<div><p><b>Job Title: </b>Senior QA Automation Engineer<br>
<b>Experience Required: </b>8+ years<br>
<b>Employment Type: </b>Full-time, Permanent<br>
<b>Work Model:</b> Hybrid<br>
<b>Location:</b> Lahore, Karachi, Islamabad</p><p><b>
Job Summary</b><br>
We are seeking a Senior QA Automation Engineer with strong experience in manual and automated testing to ensure the quality and reliability of web and mobile applications. The role requires close collaboration with product, engineering, and DevOps teams to design effective test strategies, improve automation coverage, and maintain high software quality standards throughout the delivery lifecycle.</p><p><b>
Key Responsibilities</b></p><ul><li>
Develop comprehensive test plans, test scenarios, and test cases for web and mobile applications</li><li>
Execute manual and automated tests including functional, regression, UI, API, and exploratory testing</li><li>
Collaborate with product managers and software engineers to understand requirements, use cases, and performance considerations</li><li>
Prepare and maintain clear and structured test documentation including objectives, steps, and expected results</li><li>
Participate in requirement discussions, sprint planning, daily stand-ups, and review meetings</li><li>
Identify, document, and track defects with clear reproduction steps and supporting evidence</li><li>
Collaborate with engineering teams to perform root cause analysis and ensure effective resolution of complex issues</li><li>
Support developers during debugging and verification of fixes</li><li>
Ensure adequate UI and API automation coverage aligned with project needs</li><li>
Contribute to continuous improvement of QA processes, standards, and best practices</li></ul><p><b>
Mandatory Requirements</b></p><ul><li>
8+ years of professional experience in Software Quality Assurance</li><li>
Strong hands-on experience with Selenium, Java, TestNG / Pytest, and RestAssured</li><li>
Strong experience in API testing using tools such as Postman</li><li>
Solid understanding of software testing methodologies, QA processes, and defect management</li><li>
Strong working knowledge of Git including branch management, pull requests, and conflict resolution</li><li>
Experience with CI/CD tools and practices</li><li>
Hands-on experience working in Agile / Scrum environments</li><li>
Excellent verbal and written communication skills in English</li><li>
Strong attention to detail, analytical thinking, and problem-solving skills</li><li>
Ability to work independently, manage time effectively, and take ownership of assigned tasks</li></ul><p><b>
Nice to Have</b></p><ul><li>
Knowledge of JMeter and performance testing concepts</li><li>
SQL query writing skills</li><li>
Experience with Atlassian tools such as Jira and Confluence</li></ul><p>
</p><p>ODilJUTuiy</p></div>

Senior QA Automation Engineer

<div><h3 class="jobSectionHeader"><b>Senior Full Stack Engineer (Vue.js &amp; Node.js)</b></h3><p><b>
Experience:</b> 5&ndash;8 Years<br>
<b>Employment Type:</b> Full-Time, Permanent<br>
<b>Work Model:</b> Hybrid<br>
<b>Location:</b> Lahore, Karachi, Islamabad (Pakistan)</p><h3 class="jobSectionHeader"><b>
Role Overview</b></h3><p>
We are seeking a highly skilled <b>Senior Full Stack Engineer (Vue &amp; Node)</b> to contribute to the design, development, and delivery of scalable, cloud-native applications. The ideal candidate will be hands-on across frontend and backend development, with strong experience in Vue.js, Node.js, and AWS-based architectures.</p><h3 class="jobSectionHeader"><b>
Required Skills &amp; Qualifications</b></h3><ul><li>
5&ndash;8 years of professional experience in full-stack software development</li><li>
Strong backend development expertise using <b>Node.js</b></li><li>
Hands-on frontend experience with <b>Vue.js (Vue 3)</b> for building responsive user interfaces</li><li>
Experience working with <b>RESTful APIs and/or GraphQL</b></li><li>
Practical exposure to <b>AWS services</b>, including Lambda, Amplify, API Gateway, and RDS/MySQL</li><li>
Understanding of <b>microservices, serverless architectures, and event-driven systems</b></li><li>
Experience with <b>Web Sockets and real-time communication</b></li><li>
Familiarity with <b>CI/CD pipelines, automated testing, and version control systems</b></li><li>
Solid problem-solving skills and attention to detail</li><li>
Strong communication and collaboration skills</li></ul><h3 class="jobSectionHeader"><b>
Preferred Qualifications</b></h3><ul><li>
Exposure to <b>Docker, AWS CDK, or CloudFormation</b></li><li>
Experience with <b>Agile/Scrum methodologies</b> and tools such as Jira or Confluence</li><li>
Basic experience mentoring junior engineers</li></ul><h3 class="jobSectionHeader"><b>
Key Responsibilities</b></h3><ul><li>
Design, develop, and maintain full-stack applications using <b>Vue.js and Node.js</b></li><li>
Build scalable backend services and APIs integrated with AWS infrastructure</li><li>
Implement responsive UI components and frontend architecture best practices</li><li>
Work closely with product, QA, and DevOps teams to deliver high-quality solutions</li><li>
Contribute to code reviews, testing strategies, and technical documentation</li><li>
Troubleshoot, debug, and optimize application performance</li><li>
Stay current with modern web development and cloud technologies</li></ul><h3 class="jobSectionHeader"><b>
What We Offer</b></h3><ul><li>
Opportunity to work on modern, cloud-native products</li><li>
Competitive compensation and benefits</li><li>
Hybrid working environment in Lahore, Karachi, or Islamabad</li><li>
Collaborative engineering culture with learning and growth opportunities</li></ul><p>
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Senior Full Stack Engineer (Vue.js & Node.js)

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