5
Client projects shipped
Open for freelance & contract
I design and ship AI systems that hold up in production.
Multi-agent orchestration, RAG copilots, MCP tools, and FastAPI backends — for founders and teams who need a builder, not a slide deck.
35d
Zero-to-one e-commerce rebuild
3d
Monolith-to-services onboarding
Remote
US, EU & India timezones
01
What I take on
Scoped builds and embedded seats. Pick a lane — or mix them.
Multi-agent systems
CrewAI and LangGraph setups with a manager that delegates to specialists — IDV, OCR, research, ops — instead of one bloated prompt.
- Supervisor / specialist graphs
- Custom MCP tools with JSON Schema
- Eval hooks for tool-call reliability
RAG & internal copilots
Grounded Q&A over your docs, ledgers, Slack, and tickets — with citations, not vibes.
- Ingestion + chunking pipelines
- Tool-routed retrieval (not one giant index)
- Streamlit or web UI for the team
APIs & MCP tooling
FastAPI services, SSE streams, and MCP servers so models can actually do work against your stack.
- Production FastAPI / Flask APIs
- Auth, rate limits, structured logs
- MCP servers for Claude, Cursor, custom agents
Text-to-SQL & data apps
Natural-language access to warehouses and Postgres so operators stop waiting on an analyst.
- LangGraph query planners
- Guardrails + dry-run SQL
- Read-only dashboards for non-technical users
Cloud & deployment
Containerized services on AWS, GCP, or Azure — Docker, Kubernetes, Terraform — with boring, repeatable deploys.
- Docker / K8s packaging
- CI-friendly env & secrets
- Cost and latency pass before handoff
Fractional AI engineer
Part-time or contract embedding: architecture reviews, agent debugging, and shipping the next milestone with your team.
- Weekly build cadence
- Written decisions, not tribal knowledge
- Handoff docs your team can own
Related: AI agent development · RAG development · MCP development · Python development · Backend development · LLM development
02
Selected work
Pick a project. The stage keeps the story short — switch with the list or arrows.
03
Client feedback
One voice at a time. Click a name, or let it play.
04
How we work
Short loop. You own the repo from day one.
01
Scope
A short call on the problem, data, constraints, and what 'done' looks like. You get a written outline — stack, risks, and a first milestone.
02
Build
Weekly demos, not a big reveal. Agents, APIs, and UIs land in a repo you own, with notes on why each decision was made.
03
Ship
Deploy, docs, and a runbook. Eval hooks where they matter. No mystery notebooks left behind.
04
Support
Optional retainer for the next slice — new tools, model swaps, or sitting with your team while they take the wheel.
Engagements
Sprint
2–6 weeks
A bounded system: one agent loop, one RAG copilot, one API. Fixed scope, weekly demos.
Part-time
Ongoing
Embedded builder on your cadence. Architecture, shipping, and reviews without a full-time hire.
Contract
Project or retainer
When you need production ownership — deploys, MCP tools, and a handoff your staff can run.
Frequently Asked Questions
Freelance AI engineering, contract work, and how to get started.
What does Ram Bikkina build?
Ram designs and ships production AI systems: multi-agent orchestration (CrewAI, LangGraph), RAG and internal copilots, MCP tools and servers, FastAPI backends, text-to-SQL data apps, and cloud deployments for founders and product teams.
Does Ram take freelance AI engineering projects?
Yes. Ram works on freelance and contract engagements — scoped sprints, part-time embedded seats, and project retainers — with weekly demos and handoff in repos clients own.
Does Ram work on contract engagements?
Yes. Contract work includes fixed-scope builds (agents, copilots, APIs) and ongoing retainers for production ownership, deploys, and MCP integrations.
Can Ram build AI agents?
Yes. Ram builds supervisor-led multi-agent systems with specialist delegation, custom MCP tools, eval hooks, and production APIs — not one-off prompt demos.
Can Ram build MCP servers?
Yes. Ram builds Model Context Protocol servers and tool integrations so Claude, Cursor, and custom agents can call your APIs and internal systems with structured schemas.
Can Ram build RAG applications?
Yes. Ram builds grounded Q&A over docs, ledgers, Slack, and tickets with ingestion pipelines, tool-routed retrieval, citations, and team-facing UIs.
Can Ram build Python and FastAPI backends?
Yes. Ram ships FastAPI and Flask services with auth, rate limits, structured logging, SSE streams, and deployment-ready packaging.
Can Ram help build an AI product from an idea?
Yes. Engagements start with a short scope call and written milestone; Ram delivers working software in your repo with docs and deploy paths — typical fit is an AI MVP or first production slice.
Does Ram work remotely?
Yes. Ram is based in Hyderabad, Telangana, India and works remotely with US, EU, and India timezones.
Is Ram available for fractional AI engineering?
Yes. Fractional / part-time embedding covers architecture reviews, agent debugging, and shipping the next milestone alongside your team.
What technologies does Ram use?
Python, FastAPI, Flask, CrewAI, LangGraph, LangChain, MCP, OpenAI and other LLM APIs, FAISS, Streamlit, Docker, Kubernetes, AWS/GCP/Azure, and standard data tooling depending on the project.
How can I contact Ram?
Email itsrambikkina@gmail.com, call +91 70958 38715, or use the contact form below. GitHub: github.com/Ramc26.
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Next step
Tell me what you're trying to ship.
I read every note. Typical reply within one business day. For a faster start, include stack, deadline, and whether this is a sprint or an ongoing seat.