Production AI agents, built around your product
Saif Qureshi — AI Product Engineer and founder of SolutionPlus, shipping production AI since 2023: agents, retrieval, and full-stack products for companies and enterprises.
- End-to-end delivery: agents, retrieval, observability, and cost-aware ops across React, Node, and data layers.
- Trusted on systems running up to $2M/month in Meta spend — grounded integrations, audits, and live production AI.
- Monthly Meta ad spend supported
- $2M+
- Agent tools & workflows shipped
- 30+
- Years shipping software · since 2017
- 9+
Shipped with
- Parker AI
- Get Magic
- Bewerbung.AI
- SolutionPlus
- Medwing
- Modus Create
- Hopprfy
01Selected work
Production AI, shipped
Real systems in real use — marketing intelligence, assistants, and SaaS. Each one has the stack, the outcomes, and a full write-up.
Parker AI
06/2023 – PresentMulti-agent platform that turns TikTok, Instagram, and Meta signal into shippable creative for high-spend DTC brands.
- Powering creative strategy for brands at up to $2M/month Meta ad spend.
- Idea turnaround compressed from days to minutes.
Get Magic
2023 – 2024AI co-pilot for getmagic.com and embedded assistant surfaces — enterprise extension workflows with RAG, memory, and real tool actions.
- Reduced research and drafting time per assistant ticket.
- Standardised reuse of playbooks across the assistant team.
Bewerbung.AI
2023 – 2024Agent-driven Lebenslauf and Anschreiben, job-fit coaching, Lambda PDF export, and analytics — tuned to the German hiring market.
- Made high-quality German Bewerbungen accessible without expensive coaches.
- Cut time-to-application from hours to minutes with agent-assisted Anschreiben and trustworthy PDF exports.
QuickBilling
2024 – PresentSolo-built SaaS to send invoices and quotes in minutes, track opens, manage expenses, and share secure client links — with a public OpenAPI.
- Live product from zero → production with marketing, app, docs, and API surfaces.
- Positioned for freelancers and small businesses: fast send, professional presentation, expenses + invoicing in one workspace.
More builds
Browse the complete index- getSimplePayFinTech · ShopifyShopify app and checkout extensions for US bank-pay — merchant admin on Polaris, payment customization functions, and ACH positioning at getsimplepay.io.2022 – 2024
- ManzilFinTech · WealthGoals-based halal investing from the Aghaz monorepo — React Native app, Express/Postgres API, Plaid funding, admin ops; now Manzil Invest at manzil.ca.2021 – 2025
- Bindr.ukProduct BuildBuilt the product end-to-end with a team of three — React, Node, GraphQL, Jitsi, and StreamChat.09/2021 – 06/2022
- Microservices ChatArchitectureDocker/Kubernetes microservices with Firebase-backed realtime chat, Redis IPC, and a dynamic web crawler.2017 – 2019
02What I build
Six ways to work with me
Senior, hands-on engineering from architecture to production — scoped as 2–12 week milestones, each backed by systems already running in production.
AI platforms & agent orchestration
Multi-agent workflows with planning, memory, typed tool calls, and human checkpoints — from creative-strategy platforms to assistant co-pilots.
- Ship agent runtimes where tool calls are typed, traced, and bounded by production rails.
- Orchestrate long-running work on durable workflow engines (e.g. Temporal) alongside real-time product surfaces.
- Deliver Slack-, dashboard-, and extension-first UX so outputs land where teams already work.
Shipped examples
Hybrid RAG & retrieval engineering
Vector + relational retrieval, semantic chunking, and re-ranking so LLM outputs stay grounded when catalogues and documents get large.
- Design hybrid stores (e.g. Qdrant + Postgres) with query-aware re-ranking and consistent serialisation.
- Tune embedding and chunking pipelines for long-form social, ads, and document content.
- Pair retrieval changes with evals and tracing so quality regressions are measurable.
Shipped examples
Data ingestion & API integrations
Schedulers, retries, and normalised pipelines from ads APIs, social platforms, and internal services — built for scale and observability.
- Run multi-source ingestion with backoff, dead-letter queues, and clear ownership of failures.
- Integrate Meta Marketing API and social surfaces with rate-limit-aware, token-safe clients.
- Produce stable schemas that feed analytics, retrieval, and downstream AI features.
Shipped examples
Embedded AI & browser assistants
Chrome extensions and sidepanel experiences with in-browser RAG and real actions via tool gateways — not another detached chat tab.
- Ship Plasmo extensions that respect page and selection context for assistant workflows.
- Use on-device stores (e.g. IndexedDB RAG) when sensitive context should stay local.
- Connect assistants to CRM, calendar, email, and internal APIs through scoped MCP-style adapters.
Shipped examples
Product engineering & SaaS delivery
Full-stack delivery from editor UX and PDF correctness to billing, credits, and SEO-strong marketing sites.
- Build document and workflow products with export fidelity and monetisation (e.g. Stripe, credits, email nudges).
- Launch solo or small-team SaaS with tenant boundaries, APIs, and operational discipline.
- Ship consultancy and catalogue sites with performance and SEO baselines the team can extend.
Shipped examples
Cost, evals & production safety
Model routing, budgets, caching strategy, and auditability so AI products survive real traffic, reviews, and finance scrutiny.
- Instrument LLM calls with traces, prompt versions, and cost/latency visibility (e.g. Langfuse).
- Balance token spend and retrieval depth without sacrificing response quality.
- Apply prompt-safety patterns, PII hygiene, and least-privilege tool scopes for enterprise-ready behaviour.
03How I work
From first call to a system your team owns
One senior engineer from architecture to production. Here is exactly what working together looks like.
Step 1: Free 30-minute call
Walk through what you are building, where you are stuck, and what a sensible next milestone looks like. No pitch deck required.
Step 2: A scoped milestone
Work is scoped as a 2–12 week milestone with clear deliverables, a shared definition of done, and the evals that prove it.
Step 3: Built for production
Typed, traced tool calls, evals on every model change, cost and latency dashboards, and human checkpoints on risky actions.
Step 4: A handoff your team can run
Runbooks, dashboards, and documentation so your engineers can operate and extend what we shipped.
Direct access
You talk to Saif — no sales layer, no juniors learning on your budget.
Replies within a business day
A straight answer even when the timing or scope is not a fit.
One to two engagements at a time
Focused attention; SolutionPlus extends capacity for larger builds.
Most engagements start with the call. It is free and there is no obligation.
Book the free call04Engineer · Founder · Operator
Product engineer by craft, founder by habit
Building production AI agents since 2023 — before “agentic” was a buzzword — on full-stack and product delivery since 2017: shipped, measured, maintained.
Chapter one
From full-stack to founding AI teams
Roots in full-stack and mobile delivery with US / UK / EU product teams — then founding AI engineer at Parker AI since 2023, and founder of SolutionPlus. Same discipline, higher stakes: contracts, tests, and ops for systems that reason.
- Recent depth in agents, retrieval, and embedded assistant UIs wired to ads, CRM, calendars, and internal APIs.
- “Outcomes you can defend, maintain, and scale — not demos.”
Track record
- Founder of SolutionPlus — production AI systems for companies and enterprises
- Founding AI Product Engineer at Parker AI since 2023 — agents in production before “agentic” was a buzzword
- Shipping software since 2017 — consulting and product roles
- Solo-built and operated SaaS (QuickBilling) — billing, tenants, API, docs
- Hands-on with Temporal, Qdrant, Supabase, Langfuse, and MCP-style tools
- Cost-aware AI delivery and quality instrumentation from day one
- Bachelor's in Computer Science — Government College University Lahore (2015 to 2019)
Toolkit
AI and agents
- Multi-agent systems
- MCP tools
- Agentic workflows
- RAG
- Guardrails
- LLM integration
Data and retrieval
- Qdrant
- Supabase
- PostgreSQL
- MongoDB
- Redis
- Hybrid search
Cloud and infrastructure
- AWS
- GCP
- Cloudflare Workers
- Docker
- Serverless
- Observability
Frontend and product
- React
- Next.js
- TypeScript
- Plasmo
- Vite
- IndexedDB
Backend and APIs
- Node.js
- Express
- GraphQL
- REST APIs
- OAuth and SAML
- Microservices
Automation and delivery
- Temporal
- Langfuse
- GitHub Actions
- n8n
- Stripe APIs
- Cost optimization
05Track record
Roles that shaped the work
From founding-engineer roles at AI-native startups to consulting for US, UK, and EU product teams — each role links to its stack, highlights, and outcomes.
- 06/2023 – PresentFounding AI Product EngineerCurrentParker AI · Remote · Berlin, GermanyBuilding the AI-native creative-strategy platform for high-spend Meta advertisers.
- 2023 – 2024 (consulting)Senior AI Engineer · Magic AssistantGet Magic (getmagic.com) · Remote · USABuilding the AI co-pilot that scales Magic’s 24/7 executive-assistant service.
- 2023 – 2024 (consulting)Senior Engineer · AI Resume & CoachingBewerbung.AI · Remote · Berlin, GermanyBuilding Germany’s AI-powered application platform — résumé, cover letter, coach, and Bewerbung flow.
- 11/2023 – PresentFounder & Founding EngineerCurrentSolutionPlus.io · Remote · Berlin, GermanyFounder of SolutionPlus.io — a software solutions company delivering web, mobile, and AI products for clients.
- 12/2022 – 06/2023Senior Software EngineerMedwing · Berlin, GermanyHealthcare hiring platform — full-stack feature delivery on Next.js and AWS.
- 10/2021 – 12/2022Senior Software Engineer (Full Stack)Modus Create · Remote · USAEnterprise consulting — Business Service Intelligence for Device Ops and platform optimisation.
06The thesis
Strong opinions, shipped systems
Six things I believe about production AI — each one paid for with real incidents. Quote them, argue with them, share them.
Demos are cheap. Production is the product.
Most AI projects die between the demo and deployment. I build for the part after the applause — evals, cost guardrails, retries, and runbooks.
Agents earn their place — or they don’t ship.
If it’s deterministic, hard-code it. Agents are for planning, tools, and memory across steps. Boring on purpose everywhere else.
Retrieval is where hallucinations are born.
Wrong chunks, stale data, ranking that ignores intent. Fix retrieval before blaming the model.
Every LLM call should have a price tag.
Traced, versioned, budgeted. If you can’t say what a task costs, you can’t scale it.
The best assistant lives where the work happens.
Not in another tab. In Slack, in Gmail, in the browser — beside the workflow, inside the permissions.
Founders should ship.
SolutionPlus, QuickBilling, Bewerbung.AI — I don’t just advise product. I carry the pager for it.
07Quick answers
Questions buyers actually ask
What does Saif Qureshi do?
Saif Qureshi is a Berlin-based AI product engineer and founder of SolutionPlus. He designs and ships production AI systems — AI agents, RAG pipelines, embedded assistants, and full-stack AI products — for companies and enterprises that need them running in production, not stuck in demos.
Who hires Saif?
Startups, scale-ups, and enterprise teams that need senior AI engineering without a full-time hire: agent orchestration, retrieval systems, LLM integrations, and the product engineering around them. He takes on one to two focused engagements at a time.
Where is Saif based?
Berlin, Germany — working remotely with clients worldwide from the EU timezone, with overlap across Europe, the UK, the US East Coast, and async-friendly coverage beyond that.
How does an engagement start?
With a free 30-minute call to walk through what you are building, where you are stuck, and what a sensible next milestone looks like. From there, work is scoped as 2–12 week milestones with clear deliverables, evals, and handoff.
What has Saif built?
As founding AI product engineer at Parker AI since 2023, multi-agent marketing intelligence on Mastra and Temporal serving brands at up to $2M/month in Meta ad spend. As founder of SolutionPlus, production AI platforms for companies and enterprises. Solo, the QuickBilling invoicing SaaS and Bewerbung.AI for the German hiring market — plus 30+ shipped agent tools and workflows.
Why hire a founder-engineer instead of an agency?
One senior pair of hands from architecture to production: no handoffs, no juniors learning on your budget, no slideware. Saif takes one to two focused engagements at a time, scoped as 2–12 week milestones with evals, cost guardrails, and a handoff your team can operate.
Are you available alongside your current roles?
Yes. Saif is the founding AI Product Engineer at Parker AI and the founder of SolutionPlus — and takes on a limited number of focused engagements where senior, hands-on delivery matters. For larger builds, SolutionPlus extends delivery capacity beyond just him.
What does “production AI” mean in practice?
Systems that survive real traffic and real scrutiny: typed and traced tool calls, evals on every model change, cost and latency dashboards, human checkpoints on risky actions, and runbooks your team can operate. Demos are easy — maintained systems are the job.
Something else on your mind? Ask directly
08Start a conversation
Tell me what you’re building
Book a free 30-minute call to walk through what you are building, where you are stuck, and what a sensible next milestone looks like — whether that is agents, retrieval, integrations, or getting to production.
Discovery call, no pitch deck required
Just your context and questions. We will look at your stack, constraints, and outcomes, and you will leave with a clearer picture of scope, risks, and what “done” should mean for your team.
Book a free 30-min callOpen to AI platform, assistant, and integration-heavy projects where delivery quality and operational clarity are critical.