You will get FastAPI + LLM Backend Build
Project details
A production-ready AI API in FastAPI — wired to the model you choose, with the auth, rate-limiting, and observability a demo skips. A backend your team can own after handoff.
Anyone can wire an LLM call into an endpoint. The hard part is keeping it up under real traffic: retries, cost and abuse controls, logging failures, and shipping it so your team can maintain it. That gap is the work.
WHAT YOU GET
• A FastAPI service with your LLM integration — model-agnostic (Claude, OpenAI, open-weight)
• Auth, rate-limiting, retries, and error handling built in
• Observability — request logging, token & cost tracking, basic metrics
• Tests, README, clean documented code, and a containerized deploy to your cloud
WHO IT'S FOR
Teams that have validated an AI feature and need it built as a real backend — not a notebook.
WHY ME
25 years of production software for top-ranked global gaming and product-development companies, including a high-traffic platform — plus production AI today. I build the guardrail layer most AI projects skip and leave code your team can run. GCP Professional Cloud Architect.
Message me your endpoint list or a rough spec and I'll confirm scope first.
Anyone can wire an LLM call into an endpoint. The hard part is keeping it up under real traffic: retries, cost and abuse controls, logging failures, and shipping it so your team can maintain it. That gap is the work.
WHAT YOU GET
• A FastAPI service with your LLM integration — model-agnostic (Claude, OpenAI, open-weight)
• Auth, rate-limiting, retries, and error handling built in
• Observability — request logging, token & cost tracking, basic metrics
• Tests, README, clean documented code, and a containerized deploy to your cloud
WHO IT'S FOR
Teams that have validated an AI feature and need it built as a real backend — not a notebook.
WHY ME
25 years of production software for top-ranked global gaming and product-development companies, including a high-traffic platform — plus production AI today. I build the guardrail layer most AI projects skip and leave code your team can run. GCP Professional Cloud Architect.
Message me your endpoint list or a rough spec and I'll confirm scope first.
AI Algorithms
Large Language ModelAI Applications
AI Chatbot, AI Content Creation, AI Mobile App Development, Conversational AI, Machine Translation, Time Series AnalysisAI Models
GPT-3, LLaMAWhat's included $5,000
These options are included with the project scope.
$5,000
- Delivery Time 15 days
- Number of Revisions 1
- MLOps
- Model Deployment
- Model Tuning
- Prompt Engineering
About Nagaraju
AI Implementation Architect - Agentic AI, RAG | 25 yrs enterprise
Hyderabad, India - 6:04 pm local time
What I bring that most contractors can't: senior-enough judgment to own the architecture and business outcome, hands-on enough to write the code and ship it.
Recent and current work:
• Built an AI document-automation platform for a structural/façade engineering consultancy — PDF extraction with full provenance, templated report generation, single stamped deliverable.
• Built a real-time data & analytics platform on Google Cloud — transaction monitoring, behavioral analytics, fraud detection.
• Architected high-traffic distributed systems for a global regulated gaming group — event-driven services, real-time complex-event processing, a European regulatory service delivered in 3 months.
Where I go deep:
• AI/LLM: agentic systems, RAG, embeddings, Vertex AI / Vector Search — plus AI strategy, technical decisions, and initiatives for complex AI needs
• Cloud: GCP architecture & modernization (Google Professional Cloud Architect)
• Backend: Python, Java, distributed systems, microservices, SRE
• Full delivery: design → build → ship, front ends
Stack and domain are not a constraint. 25 years across many technologies means I pick the right stack for the problem rather than forcing a favourite. Domains I've already shipped in include Healthcare, Insurance, Sports Betting/Gaming, GRC/Compliance, HCM, and Business Intelligence — including regulated environments — and I ramp fast into new ones.
I work solo on most engagements and can scale into a vetted senior team for larger builds when a project needs it. If you have a complex software or AI problem that's been stuck, send me the details — I'd rather discuss the specific problem than trade buzzwords.
Beyond enterprise delivery, I've served as a fractional AI partner to early-stage start-ups (Scout7, ValueMatrix) — building AI agents and production workflows — and I run an open-source AI bootcamp I deliver as hands-on corporate team training.
Steps for completing your project
After purchasing the project, send requirements so Nagaraju can start the project.
Delivery time starts when Nagaraju receives requirements from you.
Nagaraju works on your project following the steps below.
Revisions may occur after the delivery date.
Build & Deliver
I confirm the spec, build the FastAPI + LLM service with tests and observability, deploy it, and walk your team through it — refining through revisions until it meets the agreed scope.