Freelance DevOps Engineers in PunjabFreelance DevOps Engineers in Punjab
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Haris M.'s avatar
Haris M.
proLahore, Pakistan
Full Stack Web & Mobile Dev | Next Js | AI Agent | React
1x
Hired
5.0
Rating
28
Followers
Full Stack Web & Mobile Dev | Next Js | AI Agent | React
Cover image for Northward Capital Investment Platform Development
Northward Capital Investment Platform Development
2
16
Cover image for Chat Buddy – Real-Time Mobile Chat Application Development
Chat Buddy – Real-Time Mobile Chat Application Development
2
13
Cover image for Prodigi Studios
Prodigi Studios
1
11
Cover image for Prodigi Studios: Mobile App Development
Prodigi Studios: Mobile App Development
1
11
DevOps Engineer(1)
Adil Shahzad's avatar
Adil Shahzad
proLahore, Pakistan
Senior DevOps & DevSecOps Engineer · Cloud Security
Senior DevOps & DevSecOps Engineer · Cloud Security
Cover image for Secure architecture for auto-scaling AI
Secure architecture for auto-scaling AI services Containerised AI agents on hardened private networking, provisioned as code with no long-lived credentials. Who it was for: An AI SaaS platform running inference workloads behind a public product. The problem. AI workloads scale unpredictably and tend to accumulate credentials — API keys in environment variables, secrets pasted into config, services talking over paths nobody documented. What I did. Provisioned the whole environment as code. Ran the agents in managed containers with auto-scaling, put load balancing in front with a controlled frontend-to-backend path, and moved every credential into managed secrets so nothing long-lived sits in the workload. The result. A platform that scales with demand and holds no long-lived credentials, with the architecture reproducible from source rather than remembered.
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8
Cover image for Reliability engineering for a data-sensitive
Reliability engineering for a data-sensitive platform SLI/SLO practice and hardening that held 99.99% uptime on a platform handling sensitive personal records. Who it was for: A healthcare SaaS platform handling sensitive personal data. The problem. A platform holding health records can't treat availability and confidentiality as separate problems — an outage and a leak are both incidents, and both are reportable. What I did. Defined SLIs and SLOs so reliability had a number attached rather than a feeling. Hardened networking and access, and enforced encryption in transit and at rest across the platform. Ran vulnerability scanning continuously rather than at release checkpoints. The result. 99.99% uptime sustained, with protective controls around personal data documented and testable.
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11
Cover image for Enterprise DevSecOps platform and mobile
Enterprise DevSecOps platform and mobile delivery Reusable governed pipelines and automated store releases that cut a banking release cycle from weeks to days. Who it was for: A banking group with multiple product teams and a manual release process. The problem. Every team had built its own pipeline, releases were manual, and mobile submissions were a person following a checklist. Slow, and impossible to prove consistent to an auditor. What I did. Stood up the platform — enterprise CI/CD, artifact management and mobile security scanning — then built reusable pipeline templates with role-based access and policy enforcement so every team inherited the same controls. Automated mobile releases to both stores. Trained the engineering teams on the new path so it stuck after I left. The result. Release cycles moved from weeks to days, roughly 70% faster, with the same governance applied across every team by default.
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17
Cover image for Secure Kubernetes platform for a
Secure Kubernetes platform for a regulated environment Production Kubernetes for regulated finance, with scanning enforced in every pipeline before anything deploys. Who it was for: A regulated financial services environment. The problem. Production Kubernetes in regulated finance has to satisfy two audiences at once: engineers who need to ship, and auditors who need to see that nothing ships unchecked. What I did. Provisioned clusters and supporting networking with Terraform so the platform is reproducible and reviewable. Designed the routing layer through a gateway and ingress controllers. Built reusable pipeline workflows with image, IaC and policy scanning embedded, so the security step isn't something a team can skip under deadline — it is the path to production. The result. Every build is scanned before deploy, and control evidence is a by-product of the pipeline rather than a separate exercise.
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22
DevOps Engineer(9)
Abdul Rafay's avatar
Abdul Rafay
Gujranwala, Pakistan
AI-powered web apps, SaaS backends & automations.
New to Contra
AI-powered web apps, SaaS backends & automations.
Cover image for Rangoli CRM - Serverless React
Rangoli CRM - Serverless React CRM Platform Rangoli CRM was a serverless React.js CRM platform that I developed from scratch, including the frontend, serverless backend workflows, API integrations, deployment, and production setup. The system was built to manage customers, orders, billing, printable invoices, shipments, and business reporting from a single dashboard. The frontend was built with React.js and hosted on Firebase Hosting. For backend/serverless logic, I used Firebase Cloud Functions, while Hasura was deployed on Heroku to provide GraphQL APIs for application data. I integrated shipment workflows, including Shiprocket, so the business could manage order delivery and tracking directly through the CRM. My Role Full Project Developer Key Work Developed the complete CRM from scratch Built React.js dashboard screens for customers, orders, billing, invoices, shipments, and reports Hosted the frontend on Firebase Hosting Built serverless workflows using Firebase Cloud Functions Used Hasura on Heroku for GraphQL data APIs Integrated GraphQL APIs with Apollo Client Integrated Shiprocket for shipment and delivery workflows Managed frontend state using Redux Built responsive UI using Ant Design Handled deployment, debugging, and production setup Tech Stack React.js, Redux, Ant Design, Firebase Hosting, Firebase Cloud Functions, Hasura, GraphQL, Apollo Client, Heroku, Shiprocket API, JavaScript
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104
Cover image for MisterChatter is an AI agent
MisterChatter is an AI agent for businesses running customer support and sales over chat and Telegram. It's trained on behavioral psychology to hold calm, on-brand, human-like conversations 24/7 — answering every query, converting casual inquiries into paying customers, and handling the workload of a 10-person team. I built the full product: positioning, landing page, pricing tiers, and three specialized agent types (Public Support, Sales-focused, VIP Care). Live at misterchatter.com (http://misterchatter.com)
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Cover image for AI-Powered Lead Automation Website for
AI-Powered Lead Automation Website for a Real Estate AI Startup Built a full marketing site for a startup selling AI voice + chat automation to real estate agencies — the kind of project where the design had to sell "AI that never sleeps" before a single line of copy did. The challenge: The client's pitch was simple but the proof had to be visual: leads get missed after hours, after open homes, and in cold databases — and their AI catches all three. The site needed to feel alive — like the AI was actually running in the background — not just describe automation with a static hero image. What I built: A dark, glass-morphic hero with a live animated 3D AI avatar (Three.js) that reacts and pulses, paired with a custom cursor and magnetic buttons for a premium, "always-on" feel Animated counters and a scrolling proof ticker (GSAP + ScrollTrigger) that reveal results and capabilities as you scroll, instead of dumping everything above the fold A "Problem" section built around four real numbered failure points agencies actually experience (late-night enquiries, open-home follow-up, vendor nurture, database reactivation) — each paired with how the AI solves it A live embedded chat bot demo panel plus a placeholder for a voice bot demo, so prospects could try the product instead of reading about it A 4-step "how it works" process timeline and a results section translating automation into business outcomes (more appraisals, faster response time, always-on coverage) Full mobile responsiveness and a booking-call CTA wired straight into their CRM funnel Stack: Semantic HTML5 with a token-based CSS architecture (custom properties, fluid typography, CSS Grid) for a maintainable design system; GSAP + ScrollTrigger driving the scroll-based motion; Three.js/WebGL powering the real-time 3D avatar; vanilla ES6+ for interaction logic (no framework overhead); integrated with a CRM booking API for lead capture and routing. The result: A site that doesn't just claim "AI that never misses a lead" — it demonstrates it, from the first scroll to the live chat demo, giving the client a genuinely differentiated landing page in a market full of templated agency sites.
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Cover image for MCP Intel Agent is a
MCP Intel Agent is a crypto intelligence and signal automation platform I built for MyCryptoParadise/ProParadiser. It ingests market data from a third-party source, validates and stores it in MongoDB, scores long/short opportunities across multiple timeframes, generates AI-assisted market intel using OpenAI, and publishes formatted updates to Telegram. I built the system from scratch, including backend APIs, scoring logic, admin dashboard, Telegram automation, deployment, and production maintenance. Live at https://mycryptoparadise.com/pro-paradiser/
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108
DevOps Engineer(2)
Ammar Haider's avatar
Ammar Haider
Lahore, Pakistan
Web(Full Stack) I Blockchain I DevOps
Web(Full Stack) I Blockchain I DevOps
Cover image for Guarda Wallet
Guarda Wallet
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10
Cover image for Trust Wallet
Trust Wallet
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6
Cover image for NFT Auto Minter / Auto Generator
NFT Auto Minter / Auto Generator
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5
Cover image for Thorfi Staking Platform
Thorfi Staking Platform
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4
DevOps Engineer(5)
Safoor Safdar's avatar
Safoor Safdar
Lahore, Pakistan
Cloud Solution Architect & DevOps Engineer / SRE
Cloud Solution Architect & DevOps Engineer / SRE
Cover image for Enhancing AWS & Magento 2 Efficiency – Kent.ca
Enhancing AWS & Magento 2 Efficiency – Kent.ca
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18
Cover image for Advanced observability for Zand.ae (Logicera)
Advanced observability for Zand.ae (Logicera)
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22
Cover image for AI-Based Identity Verification - Trust but verify | IDWise
AI-Based Identity Verification - Trust but verify | IDWise
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19
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DevOps Engineer(3)
Advancing Data Solutions's avatar
Advancing Data Solutions
proLahore, Pakistan
AI & Data Engineer|Data & AI Architect| AWS|Azure |Snowflake
AI & Data Engineer|Data & AI Architect| AWS|Azure |Snowflake
Cover image for OnPrem .NET to AWS Migration Migrated
OnPrem .NET to AWS Migration Migrated an on‐premises .NET web application and SQL Server database to AWS to achieve scalability, high availability, and cross‐region resilience. The legacy environment ran on Windows servers with a clustered SQL Server, resulting in high maintenance and limited elasticity. The new AWS architecture features EC2 Auto Scaling behind an Application Load Balancer (ALB), Amazon RDS for SQL Server with Multi‐AZ and a cross‐region read replica, and DNS failover via Route 53. ◦ Deployed the .NET application on an EC2 Auto Scaling group (Windows AMI) across private subnets in us‐east‐1. 5- Build Scalable Real-Time Data Analytics on AWS for Instant Insights Designed and implemented a real-time data analytics platform on AWS, enabling stream processing, transformation, and visualization for high-volume IoT and log data. This system was built to process and analyze millions of records per second, providing actionable insights for business decision-making. The solution leveraged AWS native services like Kinesis, Glue, Lambda, and Redshift, integrating Apache Spark Structured Streaming to handle real-time data ingestion and transformation. Airflow and Step Functions were used for workflow automation.
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Cover image for Oracle to Amazon RDS PostgreSQL Designed
Oracle to Amazon RDS PostgreSQL Designed and Implemented a secure, scalable architecture to migrate an on-prem Oracle database to Amazon RDS for PostgreSQL. Data Flow: Modeled end-to-end flow, used AWS Glue (SCT) for schema conversion and DMS for full-load and CDC. Stored artifacts in S3 and loaded into RDS. Services: Glue for conversion, DMS for Migration , S3 for artifacts, and RDS as target. Security: IAM roles with least privilege, KMS for encryption at rest. HA & DR: Architected in us-east-1 with Glue, DMS, RDS, S3, and monitoring via CloudWatch.
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Cover image for Real-Time Analytics Platform on AWS
Real-Time Analytics Platform on AWS designed to ingest, process, and visualize high-volume streaming data from IoT devices and application logs. Ingestion: Device telemetry (IoT Core) and application logs are published into Amazon Kinesis Data Streams, followed by lightweight routing and enrichment using AWS Lambda. Processing & Storage: Amazon EMR performs heavy data transformations via Spark Structured Streaming, landing the curated output into Amazon S3 as partitioned Parquet files. AWS Glue then handles batch transformations before loading the data into Amazon Redshift for the analytics workload. Orchestration & Serving: AWS Step Functions coordinate the batch processing workflows. Finally, Amazon QuickSight generates actionable business dashboards while Amazon CloudWatch monitors operational metrics and alarms
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Cover image for Batch ETL Data Warehouse Modernization Led
Batch ETL Data Warehouse Modernization Led modernization of a legacy batch ETL pipeline into a scalable AWS-based data warehouse. Replaced manual SQL jobs with an automated system loading diverse sources into Amazon Redshift. Ingestion: Daily CSVs and API data land in S3; S3 events trigger Lambda to launch Glue Crawlers and update the Data Catalog. Transformation: Glue PySpark jobs join and cleanse sales, inventory, and customer data, apply quality checks, and move errors to a quarantine path. Output: Partitioned Parquet files stored in S3 for loading into Redshift.
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DevOps Engineer(1)