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sahil_shehzad07

Sahil Shehzad

@sahil_shehzad07
5,0(2)

AI Systems Architect, Full Stack AI Developer, AI Agents and RAG

Pakistan
Anglais, Ourdou
Certaines informations sont présentées en anglais.
À propos de moi
I architect and build production AI systems end to end: the infrastructure, the agents, and the product your users touch. Today I build the AI platform behind a UK document intelligence product: multi-agent pipelines that analyse 1 GB tender packs with zero sampling, RAG over pgvector, running on AWS. What I build: - Custom AI agents and multi-agent systems - RAG chatbots and AI voice agents - n8n automation and MCP integrations - Full-stack AI SaaS on Next.js and Supabase Every build ships with error handling, logging and docs. Send me the problem. I'll send back the architecture.... Plus d’infos

Compétences

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sahil_shehzad07
Sahil Shehzad
hors ligne • 
Temps de réponse moyen de 4 heures

Voir mes services

Automatisations et agents
I will build n8n ai agents, n8n automation and n8n workflows
5,0(2)
Intégrations IA
I will build custom ai agents, multi agent systems and mcp servers

Expérience professionnelle

o_atelier

Lead Agentic AI Developer

o atelier • Freelance

Mar 2026 - Present • 7 mos

Lead architect for enterprise agentic AI platforms at a London-based product group, owning system design from first principles through to production. WHAT I OWN • Architecture of multi-agent AI systems: orchestration, tool calling, structured outputs and grounded generation • RAG and document intelligence at enterprise scale: ingestion, parsing, chunking, embeddings and retrieval • Cloud-native infrastructure on AWS (ECS Fargate, SQS, Lambda, Terraform) and Supabase (PostgreSQL, pgvector, Auth, Storage) • Multi-tenant, organisation-scoped data design with strict access boundaries HOW I BUILD • Configuration-driven platforms: a new industry or use case is a config change, not a rebuild • Self-scaling map-reduce pipelines that process gigabyte-scale document sets with zero sampling • Evaluation, observability and cost control designed in from day one • Clean boundaries between ingestion, query and infrastructure so separate teams ship in parallel LEADERSHIP • Set technical direction and architecture standards across the platform • Led the migration from self-hosted workflow tooling to a managed, event-driven AWS architecture • Translate founder and stakeholder goals into production roadmaps OUTCOMES • Largest corpus processed end to end: 1 GB, 65M words and ~9.5M tokens in one run • One platform serving 12 industry profiles through configuration alone • Single-server bottlenecks removed by moving to managed, auto-scaling cloud services STACK Python, TypeScript, OpenAI GPT, Anthropic Claude, LangChain, LlamaParse, AWS, Supabase, PostgreSQL, pgvector, Docker, Terraform

Meta_Group

Lead AI Automation Engineer

Meta Group • Temps plein

Dec 2024 - Mar 2026 • 1 yr 3 mos

Led AI automation and internal platform engineering for a UAE business group, serving 100+ users across two operations. Owned the full lifecycle: requirements, architecture, build, rollout and support. WHAT I OWNED • Company-wide workflow automation replacing manual, spreadsheet-driven processes • Systems integration across ERP, CRM, third-party APIs and on-site hardware • Multi-tenant, role-based internal platforms built on Supabase and Node.js • AI-assisted workflows for data processing, reporting and operational tasks SYSTEMS DELIVERED • Workforce and operations management platform with role-based dashboards • Automated reporting, alerts and notifications across departments • Data pipelines syncing records between business systems in real time IMPACT • 90%+ of manual operational work eliminated • 99.9% uptime across business-critical systems • Fragmented tools and duplicate data entry consolidated into connected, integrated systems HOW I WORKED • Partnered with management and department heads to prioritise automation by business value • Built for reliability first: monitoring, error handling and role-based access control • Documented every system and trained teams so operations ran without engineering bottlenecks STACK n8n, Python, JavaScript, Node.js, Supabase, PostgreSQL, REST APIs, webhooks, OpenAI GPT

Solutions

Operations and Process Systems Analyst

Solutions • Temps plein

Dec 2022 - Jan 2025 • 2 yrs 1 mo

Drove the transition from manual operations to structured, data-driven and automation-ready systems. This role built the systems-thinking foundation behind every AI platform I design today. WHAT I OWNED • End-to-end process mapping across operational departments • SOP redesign to remove bottlenecks, handoffs and duplicated effort • CRM data governance and hygiene across 10,000+ records • Operational reporting that gave management clear, reliable visibility IMPACT • Standardised workflows that became the blueprint for later automation • Clean, consistent CRM data ready for integration and analytics • Faster, more consistent operations with fewer manual errors HOW I WORKED • Partnered with operations, sales and management to understand how work actually flowed • Turned undocumented, person-dependent processes into clear, repeatable SOPs • Identified automation opportunities and specified requirements for technology rollouts SKILLS Business process analysis, workflow design, SOP documentation, CRM administration, data quality, stakeholder management and operations reporting

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