Muhammad Aneeq

AI Engineer with 2.7+ years of experience building production AI systems across LLM applications, voice AI, agentic workflows, backend APIs, and computer vision. Experienced in designing multi-agent systems, AI evaluation pipelines, real-time conversational AI products, healthcare automation tools, and multi-tenant backend architectures using Python, FastAPI, LangGraph, LangChain, PostgreSQL, Redis, cloud services, and modern LLM providers.

AI Engineer at VisionTact (2026-01 – Present)

• Built core AI systems for TalentSage, a multi-tenant, role-based recruiting platform, developing end-to-end AI pipelines for multi-agent job creation, HR Copilot workflows, resume-to-job evaluation, candidate intelligence, brain tests/tasks, skill-veracity analysis, and human-in-the-loop approval flows using LLMs, LangGraph, FastAPI, PostgreSQL RLS, Redis, and cloud storage.
• Developed Riya, TalentSage's AI interview backend, implementing deterministic interview planning, grounded LLM response generation, transcript/question/event persistence, consent and device gates, LiveKit room/token/recording infrastructure, rubric-based evaluation, integrity-signal handling, and automated HR-facing interview reports.
• Architected VoiceTact enterprise voice agents for real-time customer conversations, designing ASR, NLU, dialogue orchestration, tool-calling, CRM/scheduling/messaging integrations, and TTS workflows to automate calls, lead qualification, appointment booking, follow-ups, and operational voice workflows.

Junior AI Engineer at MTBC CareCloud (2024-07 – 2026-01)

• Developed StratusAI, an enterprise-grade voice-to-voice AI receptionist by architecting low-latency conversational AI pipelines (ASR, LLM, TTS), enabling 24/7 multilingual patient interactions for appointment scheduling, appointment rescheduling, cancellations, medication refill requests, referral management, FAQ handling, and automated call routing through seamless EHR integration.
• Developed AI-powered healthcare systems including Voice-Based PHR System with multi-agent conversational AI, Cirrus AI Notes for clinical transcription (20% documentation time reduction), and AI-driven medical document summarization.
• Created multiple production-ready AI APIs including Text-to-Image generation using diffusion models, Text-to-Speech synthesis, multilingual translation services, and Cirrus Insights platform for personalized health recommendations.

Junior Computer Vision Engineer at Dione Technologies (2024-01 – 2024-06)

• Developed DroneAI, a real-time computer vision system achieving 90%+ vehicle detection accuracy from UAV imagery, along with an advanced crop monitoring solution for aerial agricultural analysis and a precision target tracking system for autonomous applications.

Bachelor of Science in Computer Science (Artificial Intelligence) – Pir Mehr Ali Shah Arid Agriculture University (PMAS-AAUR) (2021-09 – 2025-07)