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AI Engineer with 1+ years in agentic AI, computer vision, and backend automation.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Engineer building production-grade systems in agentic AI, computer vision, and backend automation. Experienced in turning manual operational workflows into scalable pipelines across order operations, content workflows, and edge AI prototypes. Skilled in Python, LangGraph/LangChain, FastAPI, and cloud deployment.
University of Engineering and Technology Mardan
Bachelor of Science · Computer Software Engineering
N/A – Present
Harp Technologies
AI/ML Engineer (Contract, Remote)
December 1, 2025 – March 1, 2026
India
EARL OF ETON LIMITED
AI Automation Engineer (Remote)
April 1, 2025 – Present
India
Linnworks Supervised Agentic Automation + Van-Sales Mobile Workflow
June 24, 2026 – Present
Built a deterministic order automation system over Linnworks and email with LLM-assisted classification, drafting, and a van-sales mobile app into one end-to-end flow. Automated customer contact through email, reply handling, and Human-in-the-Loop approval for risky order actions.
whatsapp-mcp-assistant (FastMCP, Go, whatsmeow, Python)
June 24, 2026 – Present
Built a production WhatsApp automation server using FastMCP and a Go whatsmeow bridge, exposing real WhatsApp sessions as LLM-callable tools inside Cursor. Enforced Human-in-the-Loop by blocking all outbound messages unless explicitly approved at runtime.
Jarvis: Autonomous Agentic AI PC Voice Assistant (FYP)
June 24, 2026 – Present
Built a mini-Jarvis assistant with full voice-based control of the PC, including reading/explaining context, writing outputs, and executing multi-step tasks with memory. Engineered offline-first voice pipeline and LangGraph multi-agent orchestration using LM Studio + Kaggle GPU offloading.
Agentic RAG Sub-Agents: Multi-Agent Document Intelligence System
June 24, 2026 – Present
Built a production-grade RAG system with hybrid search, Reciprocal Rank Fusion, and Cohere reranking using raw Python SDK no framework abstractions. Implemented pgvector semantic search, metadata filtering, and LangSmith observability for retrieval evaluation
Cultural Fit Analysis
The candidate's project diversity, ranging from personal projects like a WhatsApp assistant and a Jarvis-like voice assistant to academic and professional roles, indicates a strong passion for AI and continuous learning. The focus on practical, production-grade systems aligns well with a results-oriented culture. The breadth of skills across AI/ML, backend, and some frontend/mobile suggests a versatile individual who can contribute to various aspects of a project. The contract and remote roles suggest flexibility and self-reliance.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a problem-solving mindset and an ability to translate business needs into technical solutions. The emphasis on 'Human-in-the-Loop' and 'deterministic order automation' suggests an appreciation for robust, controlled, and reliable systems. The remote work experience indicates adaptability and self-management. However, without direct interview data, specific soft skills like teamwork, leadership, or conflict resolution cannot be fully assessed.