Engineering Sprints, Systems Architecture & Production AI

I work on milestone-based fixed sprints (1 to 4 weeks) with zero scope bloat and direct founder-level communication. Every engagement includes clear milestone deliverables, daily/weekly async updates via Slack/Discord, clean PRs with automated CI checks, and immediate code handover committed directly to your private GitHub or GitLab repository.

I am actively available for new freelance sprints, monthly contracts, and technical advisory roles. Following an initial 30-minute discovery call, I provide a detailed scope and fixed-price proposal within 48 hours and can typically onboard and begin shipping production code within 3 to 7 business days.

You retain 100% ownership of all code, architecture specifications, configurations, and documentation created during the engagement. Everything is committed directly to your private repositories with full commercial rights.

The fastest path: email shaikh.samir.work@gmail.com or use the Contact page with a brief summary of what you need — your product vision, tech stack, and target timeline. I reply within 24 hours to schedule a short discovery call, after which I provide a clear scope and timeline proposal, typically within 48 hours.

Absolutely. You don't need to rebuild your application from scratch. We integrate custom RAG pipelines, streaming AI chatbots, and semantic document search directly into your existing PostgreSQL database (using pgvector), backend API, and frontend components in 1 to 2 weeks.

We stop hallucinations using a 4-layer production RAG architecture: (1) Semantic document chunking and vector indexing in PostgreSQL pgvector, (2) Strict cosine distance thresholds (<= 0.5) to discard irrelevant context, (3) Grounded prompt templates instructing the LLM to decline ungrounded questions, and (4) Structured fallback handlers providing transparent handoffs when information is absent.

Yes. We build production-grade AI chatbots connected directly to your proprietary company knowledge base (PDFs, Markdown documentation, FAQs, Notion databases, or SQL records). The chatbot queries PostgreSQL pgvector with 3072d Gemini embeddings in sub-300ms, delivers streaming answers without hallucinating, and integrates cleanly as an embeddable widget or backend REST API in 1 to 3 weeks.

A production-grade AI system differs from a basic wrapper through 5 critical pillars: (1) Deterministic grounding with strict relevance thresholds, (2) Sub-300ms vector search latency and low-latency streaming responses, (3) Rate limiting per IP and fingerprint to prevent API abuse, (4) In-memory token budget controls and multi-provider failover, and (5) Comprehensive test coverage with automated CI/CD deployment pipelines.

Off-the-shelf chatbot tools lock your proprietary data onto shared third-party servers, charge recurring monthly per-seat and per-message markups, offer limited customization, and struggle with custom business workflows. Hiring a freelance AI developer gives you 100% code and data ownership, zero recurring software platform fees, tailored retrieval algorithms optimized for your specific schema, and seamless integration into your existing authentication and backend systems.

Yes. A substantial portion of my work involves stepping into existing codebases — whether taking over an application after a previous developer left, fixing an MVP that crashes under load, or maintaining a live SaaS. I begin with a structured 3–5 day Codebase Audit to review code quality, database queries, and security before implementing fixes.

The Codebase Audit is a fixed-price ($450) deep-dive into your application. I inspect your architecture, analyze slow database queries, check authentication and security boundaries, identify code quality risks, and deliver an executive report plus a prioritized GitHub backlog with estimated hours to resolve each issue.

Under a fractional retainer (10–20 hours/week), I embed directly into your engineering team as your senior backend and AI developer. We collaborate via Slack or Discord, attend sprint ceremonies if needed, and ship code via GitHub pull requests with automated tests and documentation. It gives you senior engineering velocity at a fraction of full-time hiring cost.

A Forward Deployed Engineer (FDE) bridges deep software engineering and direct client immersion. Unlike isolated developers, an FDE embeds directly with stakeholders to conduct technical discovery on ambiguous requirements, rapidly build and validate prototypes, and harden the solution for enterprise production. Hire an FDE when deploying high-stakes AI features or integrating custom software into client workflows.

Yes. Drawing on production projects like Sahara Tyre (where we automated WhatsApp customer notifications, inventory management, and billing), we build custom WhatsApp Business API workflows, Stripe/Razorpay subscription billing, and robust webhook processors with automatic retries and dead-letter queues.

Our SEO services focus on technical accuracy and measurable search visibility: (1) Technical SEO audits resolving crawl errors, canonical loops, and indexation issues, (2) Keyword mapping for titles, meta descriptions, and semantic headings, (3) Schema.org structured data (Organization, ProfessionalService, Service, FAQPage) for Google rich snippets, (4) Google Core Web Vitals optimization for speed, and (5) Generative Engine Optimization (GEO/AEO) so AI answer engines like ChatGPT and Perplexity cite your content.

Yes. We build end-to-end full-stack applications and local business platforms using Next.js 16, React 19, and Tailwind CSS on the frontend, paired with Node.js, PostgreSQL, Drizzle ORM, and Redis on the backend. This provides single-engineer velocity, zero communication bottlenecks between frontend and backend, and cohesive type safety across the entire stack.