Open to Work — AI Engineer Roles

    Hassan AbbasAI Engineer

    Building Production LLM Systems

    AI Engineer building production-grade LLM, RAG, and agentic automation systems.

    2+ years shipping scalable enterprise AI at Liquid Technologies and Teknloje Solutions — from LLM orchestration and voice automation to computer vision and backend architecture.

    44
    MCP tools in production
    7
    Business domains shipped
    4
    Calendar providers
    2+
    Years shipping AI
    Hassan Abbas, AI Engineer
    GPT-4
    RAG
    LangChain
    Pinecone
    01 · Profile

    About Me

    I am a production-focused AI Engineer with 2+ years of experience designing, building, and deploying intelligent systems that solve real business problems. My work spans Generative AI, Large Language Models, Retrieval-Augmented Generation, voice AI automation, computer vision, and backend architecture — from system design to scalable production deployment.

    I currently work at Liquid Technologies, where I am building Sally — a two-product AI meeting-intelligence suite. Sally Web is a multi-tenant B2B SaaS platform with a production RAG knowledge base, live tool-calling, and 16+ third-party integrations, while Sally Desktop is a privacy-first Tauri app that transcribes meetings entirely on-device. Before this, I spent 18 months at Teknloje Solutions shipping five production AI systems across enterprise RAG, banking document verification, multi-camera surveillance, and voice AI automation.

    I focus on systems that drive measurable business impact, not prototypes. I take full ownership from architecture through deployment, combining strong backend engineering with AI automation to build out-of-the-box solutions that are reliable, scalable, and easy to integrate.

    Quick Facts
    • Location · Karachi, Pakistan
    • Current · AI Engineer @ Liquid Technologies
    • Degree · BS Computer Science — FAST NUCES
    • Focus · Generative AI · LLMs · RAG · Voice AI
    • hassanabbas2975@gmail.com
    • Open to full-time AI Engineer roles
    02 · Stack

    Technical Skills

    Languages

    TypeScriptPythonJavaScriptRustSQL

    Backend

    Node.jsNestJSExpressFastAPIFlaskTypeORMDrizzle ORMBullMQSocket.IOSSEREST/OpenAPIJest

    Frontend

    ReactNext.jsViteRedux Toolkit / RTK QueryTanStack QueryAnt Designshadcn/uiTailwindCSSZodRecharts

    AI / LLM

    LLM tool calling and agent loopshuman-in-the-loop approvalsModel Context Protocol (client and server)RAG (pgvector, hybrid search, reciprocal rank fusion, LLM re-ranking)embeddingsstructured outputsAI usage meteringAnthropic ClaudeOpenAIGoogle GeminivLLMLangChainWhisperParakeetONNX RuntimeYOLOv8ArcFacePaddleOCRBioBERT

    Data & Security

    PostgreSQL (pgvector, full-text search, advisory locks, triggers)RedisSQLiteFAISSAWS S3JWTOAuth 2.0/2.1 (PKCE, dynamic client registration)HMAC-signed webhooksAES-256-GCMArgon2SSRF defencemulti-tenant isolationappend-only audit logs

    Infrastructure

    DockerKubernetesNGINXGitHub Actions CI/CDTauri 2TurborepopnpmPlaywrightn8nStripeSlack Bolt
    03 · Career

    Work Experience

    AI Engineer

    Current Role
    Liquid Technologies
    April 2026 — Present
    Karachi, Pakistan

    Sally — Multi-Tenant AI SaaS Platform · Sally Desktop · LeadGenPro · Upwork Analytics Platform

    Sally — Multi-Tenant AI SaaS Platform

    Product

    NestJS 11, PostgreSQL + pgvector, Redis/BullMQ, Socket.IO, React 18 — principal contributor across backend and frontend.

    • Designed governed agent execution: every agent action is risk-classified fail-closed, high-risk writes wait for owner approval and replay from the stored payload, and the audit log is append-only at the database, keeping every agent write accountable.
    • Built a bidirectional Model Context Protocol integration: an MCP server exposing 44 tenant-scoped tools to Claude Desktop behind an OAuth 2.1 authorization server, plus a multi-transport MCP client governed by the same gate.
    • Closed the tenant-isolation gaps the product is sold on: per-person feature switches on every route, a positions-based access model rolled out in shadow mode with zero regressions, and an audit that fixed cross-tenant reads.
    • Cut the cost of adding integrations and AI providers: a four-provider calendar connector platform with zero frontend code per provider, per-tenant encrypted OAuth apps, and bring-your-own-key LLM routing across OpenAI, Anthropic, Gemini and vLLM.
    • Shipped seven business domains end to end, from a PMO cockpit over Google Sheets, Odoo and Trello to a passwordless client portal, plus a meeting-intelligence pipeline turning Recall.ai and Meetstream.ai transcripts into Jira and Asana action items.

    Sally Desktop

    Product

    Offline-first meeting recorder for Windows, macOS and Linux (Tauri 2, Rust, Next.js) with on-device Whisper/Parakeet transcription on ONNX Runtime, GPU acceleration and meeting sync to Sally, so meetings are transcribed without audio leaving the machine.

    LeadGenPro

    Product

    Lead-generation SaaS (NestJS, PostgreSQL, React) that turns keyword searches on LinkedIn, Reddit, Twitter/X and Hacker News into CRM-ready leads via a Playwright worker, a BullMQ LLM-qualification pipeline and GoHighLevel sync.

    Upwork Analytics Platform

    Product

    Solo-built read-only multi-account BI platform (Next.js, NestJS, SQLite/Drizzle) with incremental OAuth sync, AES-256-GCM token encryption and a CI-enforced read-only boundary that fails the build on any Upwork mutation.

    AI Engineer

    Teknloje Solutions
    October 2024 — April 2026
    Karachi, Pakistan · 18 months

    Delivered 5 production AI systems across enterprise AI, computer vision, OCR, voice automation, and medical NLP in 18 months.

    • Built TekInsight — an enterprise AI platform with LLM-powered chat, FAISS + LangChain RAG document intelligence, and JWT multi-tenant authentication deployed on Flask/IIS, reducing retrieval time by 60% and query latency by 40%.
    • Engineered TekCondor — a hybrid YOLOv8 + ResNet Siamese network signature verification pipeline at 94%+ accuracy with sub-300ms PaddleOCR cheque digitisation inference, eliminating manual review for 75% of submissions.
    • Built a real-time multi-camera AI surveillance system using YOLOv8 + ArcFace embeddings with cosine similarity matching and polygon zone tracking, achieving 95%+ face recognition accuracy across distributed cameras.
    • Designed an AI Voice Agent Platform using Twilio + Retell AI + n8n that monitors inbound emails, extracts leads via LLM parsing, and triggers AI outbound calls — cutting lead response time from hours to under 2 minutes.
    • Built a LLaMA 3.2 + LangChain FastAPI medical summarisation service converting doctor-patient conversations to structured clinical JSON at sub-3s latency, reducing documentation effort by 70%.
    LangChainOpenAILLaMAFAISSYOLOv8PaddleOCRArcFaceTwilioRetell AIn8nFlaskFastAPIDockerPyTorchSQL Server
    04 · Case Studies

    Case Studies

    Deep dives into the systems I have shipped — the problem each one faced, how I approached it, and the impact it had in production.

    Agentic AI · MCP · Tenant Isolation

    Sally Web — Governed Agent Execution in a Multi-Tenant SaaS

    Liquid Technologies · 2026
    Challenge

    Sally's AI agents act directly inside tenants' workspaces — writing to calendars, CRMs and project tools. Every action had to be accountable, tenant-isolated, and reversible without blocking the product's speed.

    Approach
    • Risk-classified agent execution: every action is classified fail-closed before it runs, and high-risk writes wait for owner approval, then replay from the stored payload.
    • Bidirectional Model Context Protocol: an MCP server exposing 44 tenant-scoped tools to Claude Desktop behind an OAuth 2.1 authorization server, plus a multi-transport MCP client governed by the same gate.
    • Tenant isolation hardening: per-person feature switches on every route and a positions-based access model rolled out in shadow mode with zero regressions.
    • Integration economics: a four-provider calendar connector platform with zero frontend code per provider, per-tenant encrypted OAuth apps, and bring-your-own-key LLM routing across OpenAI, Anthropic, Gemini and vLLM.
    Impact
    • 44 MCP tools in production
    • 7 business domains shipped end to end
    • 4 calendar providers, zero frontend code each
    • Append-only audit log at the database
    NestJS 11PostgreSQL + pgvectorRedis/BullMQSocket.IOReact 18MCPOAuth 2.1
    On-Device AI · Speech-to-Text · Privacy

    Sally Desktop — Meetings That Never Leave the Machine

    Liquid Technologies · 2026
    Challenge

    Enterprise buyers wanted meeting intelligence, but refused to stream sensitive audio to the cloud. Transcription and summarisation had to run entirely on-device across Windows, macOS and Linux.

    Approach
    • Tauri 2 desktop app with a Rust core and Next.js UI, shipped to Windows, macOS and Linux.
    • Real-time dual-source audio pipeline: EBU R128 loudness normalization, RNNoise neural noise suppression and Silero VAD.
    • Fully on-device Whisper/Parakeet speech-to-text on ONNX Runtime, GPU-accelerated across Metal, CoreML, CUDA, Vulkan, ROCm and optimized CPU.
    • Authentication handled entirely in the Rust process, so bearer tokens never enter the webview.
    Impact
    • 3 platform builds: Windows, macOS, Linux
    • 6 GPU acceleration backends
    • Audio never leaves the machine
    • 9 local and hosted LLM backends
    RustTauri 2Next.jsWhisperParakeetONNX RuntimeAudio DSP
    Browser Automation · AI Qualification · CRM

    LeadGenPro — From Keyword Search to CRM-Ready Leads

    Liquid Technologies · 2026
    Challenge

    Sales teams needed a steady flow of qualified leads from LinkedIn, Reddit, Twitter/X and Hacker News, but each source has its own rate limits, anti-bot defenses and data shapes.

    Approach
    • A Playwright browser-automation microservice performing stealth LinkedIn authentication with security-checkpoint recovery, persistent session reuse and structured profile extraction via LinkedIn's internal API.
    • An 11-queue BullMQ/Redis pipeline with per-platform rate limiting to keep every source inside its limits.
    • A provider-agnostic AI qualification layer (OpenAI, Anthropic, Google Gemini) scoring and classifying leads automatically.
    • A two-stage contact-enrichment waterfall — BetterContact, then Apollo.io as fallback — with automatic sync to GoHighLevel CRM.
    Impact
    • 4 sourcing platforms in one pipeline
    • 11 parallel BullMQ queues
    • Two-stage enrichment waterfall
    • AES-256-GCM credential storage
    ReactNestJSPythonFastAPIPlaywrightBullMQRedisDocker
    Voice AI · Automation · Agentic

    AI Voice Agent Platform — Cutting Lead Response from Hours to Minutes

    Teknloje Solutions · 2025
    Challenge

    Inbound leads sat unanswered for hours over weekends and after hours. The business needed 24/7 automated first contact without adding headcount to the sales floor.

    Approach
    • An n8n automation layer monitors inbound emails around the clock and extracts leads via LLM parsing.
    • Twilio + Retell AI trigger AI outbound calls the moment a lead is detected, with qualification handled conversationally.
    • Every interaction syncs to the CRM, keeping the sales pipeline current without manual entry.
    Impact
    • Lead response: hours → under 2 minutes
    • 45% better sales funnel throughput
    • 60% fewer support tickets
    • 24/7 inbound coverage
    TwilioRetell AIn8nLLM ParsingWebhooksCRM Integration
    05 · Work

    Projects

    A selection of AI systems I have designed and shipped — meeting intelligence, lead generation, recruitment, and conversational platforms. Each card opens a short breakdown of what the product does, the impact it had, and the technology behind it.

    Featured projects

    06 · Background

    Education

    Bachelor of Science in Computer Science

    FAST National University of Computer and Emerging Sciences (FAST NUCES)

    Karachi, Pakistan · August 2021 — May 2025

    One of Pakistan's top-ranked CS programs.

    07 · Learning

    Certifications

    📜

    Supervised Machine Learning

    Coursera · Andrew Ng · 2024–2025

    📜

    Advanced Learning Algorithms

    Coursera · Deep Learning, TensorFlow · 2024–2025

    📜

    Data Cleaning & Processing

    DataCamp · Python · 2024

    📜

    Astera Bootcamp: Data Integration

    2023

    08 · Contact

    Let's Work Together

    Open to full-time AI Engineer, Generative AI Engineer, LLM Engineer, and Applied AI Engineer roles. Available for both on-site (Karachi) and remote positions.

    Typically respond within 24 hours.