# Abu Bakar Siddik

> Co-founder & Lead AI Engineer — RAG pipelines, agentic workflows, scalable LLM architectures

Co-founder & Lead AI Engineer. RAG pipelines, agentic workflows, scalable LLM architectures. Previously led Core RAG & AI at AskTuring.ai. Winner, Google Nano Banana Hackathon 2025.

Location: Rajshahi, Bangladesh
Contact: abubakar1808031@gmail.com
Site: https://abubakarsiddik.site

## About

- [About (markdown)](https://abubakarsiddik.site/about.md): Full bio, current role, background.
- [Skills (markdown)](https://abubakarsiddik.site/skills.md): Categorized list of technologies and disciplines.
- [Projects (markdown)](https://abubakarsiddik.site/projects.md): Selected projects with stack, challenge, solution, and impact.
- [llms-full.txt](https://abubakarsiddik.site/llms-full.txt): Full site content in one document for one-shot ingestion.

## Skills

- **AI & Intelligence** — Retrieval, reasoning, and memory systems. Skills: RAG Pipelines, Agentic Workflows, Multi-Agent Systems, LLM Fine-Tuning, Vector Databases, LangGraph, LlamaIndex, OpenAI Agent SDK, Claude Agent SDK, Pydantic AI, Model Context Protocol (MCP), Evaluation Frameworks, Prompt Engineering, Embeddings, Hybrid Search, Reranking, Time-Aware RAG, Memory Systems (short-term, long-term, semantic), Citation Systems, Hallucination Reduction.
- **Backend Engineering** — APIs, databases, and scalable architecture. Skills: FastAPI, Python, NestJS, TypeScript, PostgreSQL, Redis, REST APIs, GraphQL, Hexagonal Architecture, Event-Driven Design, Test-Driven Development, pgbouncer, Connection Pooling.
- **Cloud & MLOps** — Deployment, observability, and scale. Skills: Docker, Kubernetes, AWS EC2, AWS S3, AWS SageMaker, GCP Vertex AI, GitHub Actions, Weights & Biases, Private AI Deployments, Air-Gapped Infrastructure, Self-Hosted GPU Infrastructure.
- **Core Competencies** — Craft, communication, and leadership. Skills: System Design, API Design Patterns, Code Review, Technical Writing, Data Annotation QA, Team Leadership, Mentorship, Public Speaking.

## Experience

- **Co-founder & Lead AI Engineer, Stealth (Legal AI)** (Apr 2026 – Present): Co-founding and leading AI engineering at an early-stage legal tech venture. Building agentic AI software for lawyers — retrieval over case law and contracts, multi-step legal reasoning agents, and production LLM workflows from the ground up.
- **AI Consultant, Chorcha** (Apr 2026 – Present): Making high-quality AI accessible to Bangladeshi students. Architecting AI-powered learning systems and advising on LLM integration, curriculum design, and responsible AI adoption.
- **Applied AI Engineer (L-2), Core RAG & AI Team Lead, AskTuring.ai** (Jul 2025 – Apr 2026): Owned end-to-end architecture for a production RAG platform without vendor lock-in: retrieval, agent orchestration, evaluation, and the LLM provider layer. Scaled from 100 to 10,000+ concurrent users at ChatGPT-level latency. Reduced hallucinations by 98% via hybrid search, reranking, citation extraction, and source-grounding. Built agentic RAG with multi-layer memory (short-term, long-term, semantic), time-aware retrieval, and a citation system spanning documents, web, and memory. Cut chat latency via prepare-then-query pre-computation and reduced database round-trips. Built persistent user memory end-to-end (extraction service, schemas, CRUD, chat integration). Migrated backend to async SQLAlchemy. Built an internal evaluation benchmark and RAG suite tooling — cut evaluation time by 99%. Built image generation and editing pipelines with pixel-level control, integrated into agent workflows as first-class tools.
- **Machine Learning Engineer, Sazim Tech Ltd** (Oct 2023 – Jul 2025): Built production LLM integrations and private on-premise air-gapped AI for enterprise clients. Designed hexagonal multi-provider architecture (OpenAI, Anthropic, local LLMs); LLM evaluation pipelines; 45% safety/jailbreak risk reduction.
- **ML Researcher & Engineer, Intelsense AI** (Sep 2022 – Sep 2023): Built Rasa chatbots for financial services and mobile operators, multilingual restaurant chatbot (English/Banglish/Bangla), Bengali ASR research, and Voice Activity Detection. Led data annotation team for NLP datasets.
- **Data Science Apprentice, Cramstack** (Nov 2021 – Apr 2022): OCR evaluation, text summarization, data visualization dashboards, web scraping.

## Projects

- [CareerKor](https://abubakarsiddik.site/projects/careerkor): AI-powered career tool: generate tailored resumes, cover letters, and track applications from one profile.
- [Axiom Wiki](https://abubakarsiddik.site/projects/axiom-wiki): AI-powered personal knowledge base that compiles documents into an interconnected markdown wiki with MCP support.
- [MagicSpin 360°](https://abubakarsiddik.site/projects/magicspin): Generates interactive 360° rotations from single 2D images. Winner of Google Nano Banana Hackathon 2025. (Winner, Google Nano Banana Hackathon 2025)
- [AI Virtual Try-On](https://abubakarsiddik.site/projects/tryon): A sophisticated image-to-image synthesis pipeline using Diffusion models.

## Blog

- [The Ship You Can't Dock: Architectural Debt in the AI Era](https://abubakarsiddik.site/blog/the-ship-you-cant-dock.md): How architectural debt accumulates when the very ground underneath you is moving, and why building AI systems feels like sailing a ship that can't dock. Tags: architecture, ai, engineering, technical-debt.
- [Scaling to 1,500 Concurrent Users: PgBouncer and Null Pooling](https://abubakarsiddik.site/blog/scaling-to-1500-concurrent-users-pgbouncer.md): How I discovered that application-level pooling doesn't work for long-running AI requests—and what actually does. Tags: postgres, pgbouncer, scalability, backend, ai.
- [Zero Data Retention (ZDR) for LLM Providers](https://abubakarsiddik.site/blog/zero-data-retention-llm-providers.md): A practical guide to keeping your data private when using LLM APIs. Covers zero-retention endpoints, self-hosting, and compliance requirements. Tags: llm, privacy, security, architecture.
- [What Gemma 4 Actually Does Differently](https://abubakarsiddik.site/blog/what-gemma-4-actually-does-differently.md): Gemma 4's 31B model is outscoring systems with 10x more parameters on Arena Elo. Here's the architectural reasoning behind why that's possible. Tags: gemma, google, architecture.
- [Injection Is Not Influence: The Illusion of LLM Memory](https://abubakarsiddik.site/blog/injection-is-not-influence-llm-memory.md): After three years of building LLM applications, I've learned that LLM memory is fundamentally different from human memory. Tags: llm, memory, architecture.

## Contact

- Email: [abubakar1808031@gmail.com](mailto:abubakar1808031@gmail.com)
- GitHub: https://github.com/abubakarsiddik31
- LinkedIn: https://linkedin.com/in/abu-bakar-siddik31
- X (Twitter): https://x.com/abubakar_AIE

## For Agents

- MCP endpoint (Streamable HTTP): https://abubakarsiddik.site/api/mcp
- Agent metadata: https://abubakarsiddik.site/.well-known/agent.json
- Sitemap: https://abubakarsiddik.site/sitemap.xml

Open for strategic AI/ML consulting, technical collaborations, and deep technical discussions.