Awais Naeem

• Direct Neksogix’s technical strategy end-to-end, architecting and delivering 20+ production AI systems across healthcare, education, e-commerce, fintech, automation, enterprise search, RAG, multimodal AI, multi-agentic workflows, and conversational copilots
• Set technical and commercial standards for scalable LLM orchestration pipelines integrating RAG, prompt engineering, vector databases, evaluation frameworks, and cloud-native AI infrastructure
• Built the company's end-to-end Applied AI delivery model — covering data engineering, dataset curation, model evaluation, prompt optimization, deployment, and continuous monitoring in production environments
• Grew and led a team of 12 (8 AI/ML engineers, 4 business developers), securing startup and enterprise clients across healthcare, fintech, travel, HR tech, and e-commerce while owning full P&L and go-to-market strategy
• Own client relationships and business development end-to-end, maintaining a 98% client satisfaction rate through reliable, production-grade AI delivery with emphasis on solution quality, scalability, and business impact.

• Built and supported a C/C++ payment authorization app for Global Payments' banking operations
• Developed PL/SQL scripts to deploy database changes per bank requirements

• Developed a Windows, MacOS and Linux based desktop/server application backend (C/C++) and frontend (Qt) for a Zero Trust Network Access (ZTNA) based cyber-security product named Invisily
• Led a team of 6 software engineers towards the development of architectural changes and new features for Invisily

• Devised two novel algorithms encompassing constrained polynomial optimization to estimate the knee/ankle trajectories via an improved monotonic and linear trajectory of the thigh phase-variable using Discrete Fourier Transform (DFT) based virtual constraint control of powered knee-ankle prosthesis
• Based on realistic prosthesis actuator parameters, achieved a 2.18 ± 0.83 times reduction in the mean trajectory tracking error for three contrasting walking speeds i.e., slow, medium, fast
• Led a multi-disciplinary team of 4 researchers towards the design and development of integrated robotic systems.

• Led, designed, and deployed 70+ production-grade AI, ML, and generative AI systems for startups and enterprises across healthcare, education, e-commerce, fintech, hospitality, and specialty verticals, spanning RAG pipelines, multi-agent systems, voice AI, and predictive analytics
• Owned client engagements end-to-end — requirements gathering, architecture, delivery, and post-launch support — delivering 20+ end-to-end data analytics solutions from data extraction through production deployment and visualization
• Built and scaled multi-tenant SaaS platforms and automation systems (conversational AI, recommendation engines, hiring and workflow automation) using modern Python stacks, LLMs (Claude, GPT), and cloud-native infrastructure (AWS, Docker, Kubernetes)
• Engineered AI automation systems including chatbots and multi-agent workflows that measurably cut manual workload and processing time for client operations, translating technical delivery directly into business impact