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Full-Stack & AI Engineer who ships end-to-end LLM products—from architecture to deployment. I’ve solo-built and launched AI SaaS products and delivered production RAG pipelines and LLM workflows with a strong focus on reliability, cost control, and evaluation-driven improvements. I turn ambiguous requirements into production-grade systems using LangChain, FastAPI/Next.js, vector databases, and robust observability/eval frameworks. I enjoy hardening AI pipelines with safety checks, caching, and measurable quality improvements while collaborating cross-functionally to ship fast.…Full-Stack & AI Engineer who ships end-to-end LLM products—from architecture to deployment. I’ve solo-built and launched AI SaaS products and delivered production RAG pipelines and LLM workflows with a strong focus on reliability, cost control, and evaluation-driven improvements. I turn ambiguous requirements into production-grade systems using LangChain, FastAPI/Next.js, vector databases, and robust observability/eval frameworks. I enjoy hardening AI pipelines with safety checks, caching, and measurable quality improvements while collaborating cross-functionally to ship fast.

Mohammed Faizan

AI Engineer, Full Stack Developer, AI Developer, +3

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Full-Stack & AI Engineer who ships end-to-end LLM products—from architecture to deployment. I’ve solo-built and launched AI SaaS products and delivered production RAG pipelines and LLM workflows with a strong focus on reliability, cost control, and evaluation-driven improvements. I turn ambiguous requirements into production-grade systems using LangChain, FastAPI/Next.js, vector databases, and robust observability/eval frameworks. I enjoy hardening AI pipelines with safety checks, caching, and measurable quality improvements while collaborating cross-functionally to ship fast.…Full-Stack & AI Engineer who ships end-to-end LLM products—from architecture to deployment. I’ve solo-built and launched AI SaaS products and delivered production RAG pipelines and LLM workflows with a strong focus on reliability, cost control, and evaluation-driven improvements. I turn ambiguous requirements into production-grade systems using LangChain, FastAPI/Next.js, vector databases, and robust observability/eval frameworks. I enjoy hardening AI pipelines with safety checks, caching, and measurable quality improvements while collaborating cross-functionally to ship fast.

Available to hire

Full-Stack & AI Engineer who ships end-to-end LLM products—from architecture to deployment. I’ve solo-built and launched AI SaaS products and delivered production RAG pipelines and LLM workflows with a strong focus on reliability, cost control, and evaluation-driven improvements.

I turn ambiguous requirements into production-grade systems using LangChain, FastAPI/Next.js, vector databases, and robust observability/eval frameworks. I enjoy hardening AI pipelines with safety checks, caching, and measurable quality improvements while collaborating cross-functionally to ship fast.

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Work Experience

Team Lead – Software Engineering at Adaptive AI Ventures

October 1, 2025 - Present

Led delivery of production AI systems and LLM workflows end-to-end, owning architecture-to-deployment. Improved reliability and sped up delivery by instituting structured design reviews and scalable engineering practices. Mentored engineers on RAG pipelines, LLM development, and prompt engineering to raise overall output quality. Coordinated with product and engineering stakeholders to ship AI features on tight timelines while reducing production issues and iteration cycles.

AI Engineer at Adaptive AI Ventures

December 1, 2023 - October 1, 2025

Built and improved RAG pipelines across OpenAI, Gemini, Llama2, and Mistral, increasing response accuracy by ~30%. Developed LLM-powered document intelligence workflows that reduced manual processing time by ~95%. Designed end-to-end AI systems covering data ingestion, retrieval, LLM processing, output validation, and evaluation. Created an eval harness to track accuracy, latency, and reliability across AI services. Deployed scalable AI services using Docker, Kubernetes, and GCP/AWS and automated data extraction/processing to improve operational efficiency by ~70%.

Founder & Full-Stack AI Engineer at ResumePros

January 1, 2023 - October 1, 2025

Built an AI SaaS that converts a generic resume into a job-specific, ATS-ready resume via a multi-stage LLM workflow (extraction → deterministic scoring → gap analysis → optimization). Made scoring explainable by pairing LLM extraction with deterministic TypeScript scoring across skills/keywords/experience/ATS match. Reduced hallucinated experience using an evidence-gathering questionnaire engine plus coverage checks. Hardened the pipeline with prompt-injection safety by isolating untrusted resume/JD content from system instructions. Created an LLM evaluation harness (schema validity, hallucination checks, scoring accuracy) and a feedback loop converting user edits into test cases. Instrumented AI observability (model, latency, cost, error tracing) and cut spend via input fingerprinting, cached regeneration, and regeneration caps. Shipped full SaaS solo: Next.js, MongoDB, NextAuth, Stripe billing (quotas, credits, refunds), admin dashboard, and Playwright PDF export.

Founder & Full-Stack AI Engineer at ResumePros AI

January 1, 2023 - Present

Built an AI SaaS that converts a generic resume into a job-specific, ATS-ready resume via a multi-stage LLM workflow (extraction → deterministic scoring → gap analysis → optimization). Made scoring explainable by combining LLM extraction with deterministic TypeScript scoring for skills, keywords, experience, and ATS match. Prevented hallucinated experience using an evidence-gathering questionnaire engine and coverage checks on the final output. Hardened the pipeline with prompt-injection safety by isolating untrusted resume/JD content from system instructions. Created an LLM eval harness (schema validity, hallucination checks, scoring accuracy) with a feedback loop converting user edits into test cases. Implemented AI observability (model, latency, cost, error tracing) and reduced spend via input fingerprinting, cached regeneration, and regeneration caps. Shipped the full SaaS solo using Next.js, MongoDB, NextAuth, and Stripe billing (quotas, credits, refunds), including admin da

Founder & Full-Stack Engineer at Knacktor

January 1, 2023 - Present

Live GitHub platform for visual DSA learning where executed Python drives synchronized, line-by-line algorithm visualizations. Tested the concept with 20 pilot users and iterated for clarity and beginner comprehension. Implemented a real-code simulation engine converting executed Python lines into visual steps with live variables and complexity counters. Scaled content using a data-driven pipeline (structured files → tracing → validation → MongoDB) without building new UI for each problem, and prevented misleading visuals using validation gates such as trace validation, DSL linting, dry-runs, and coverage checks. Optimized delivery using a DB-canonical architecture with gzip-compressed traces and lazy-loaded solution approaches.