AI/LLM Full-Stack Engineer to add AI/LLM features to an existing enterprise SaaS platform
Budget: $100.0
FIXED /
⭐ 4.99 (484)
United States
saas, api-integration, postgresql, react-js, typescript, node.js, python
We run an established, enterprise-scale SaaS platform that has been in production for many years with a
large active user base. We are now investing in a major modernization initiative: integrating AI/LLM
capabilities (Claude, OpenAI/GPT-4, and similar models) directly into our existing product to make it
smarter, more automated, and more user-friendly.
This is not a greenfield prototype — you'll be working inside a mature, production codebase, so we need
someone who has done real-world AI integration into existing systems, not just demos or tutorials.
Tech Stack
● Frontend: Next.js / React / TypeScript
● Backend: Node.js and Python (REST/GraphQL APIs)
● Infrastructure: Enterprise-scale, cloud-hosted, multi-tenant
What You'll Be Doing
● Design and implement AI/LLM features into our existing SaaS workflows
● Integrate Claude API (Anthropic) or OpenAI APIs, with an architecture flexible enough to support
multiple/model-agnostic providers
● Build RAG pipelines with vector databases so AI responses are grounded in our platform's data
● Implement prompt engineering, function/tool calling, streaming responses, and agentic
workflows where appropriate
● Ensure enterprise-grade concerns are handled: data privacy, multi-tenancy isolation, rate limiting,
token/cost optimization, latency, observability, and fallback handling
● Build polished, user-friendly AI UX in Next.js
● Collaborate with our existing team, follow our code standards, write clean, tested, maintainable
code
Required Experience
● 5+ years full-stack development (Next.js/React + Node.js and/or Python)
● Proven, shipped experience integrating LLMs (Claude/Anthropic API, OpenAI API, Azure OpenAI,
or open-source models) into existing production systems
● Hands-on with RAG, embeddings, and vector databases
● Strong API design and system architecture skills at enterprise scale
● Understanding of AI security, PII handling, and cost/token management
● Excellent communication in English; able to propose solutions, not just take tickets
Nice to Have
● LangChain / LlamaIndex / Vercel AI SDK experience
● Fine-tuning or model evaluation experience
● Experience with AWS Bedrock / GCP Vertex AI
● Prior work on B2B/enterprise SaaS products
Engagement
Long-term potential for the right person. We'll start with a well-defined initial milestone (paid), and expand
from there. Please include links to AI features you've personally shipped in production.
To filter out generic/AI-generated proposals, start your proposal with the word "Falcon" and briefly
describe the most complex LLM integration you've built.
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