HIRE DEDICATED TALENT

Hire a Dedicated AI Engineer

An AI engineer bridges the gap between AI research and production software. They integrate large language models, build retrieval-augmented generation systems, implement AI workflows, and create production-ready AI applications that solve real business problems.

Find Your AI Engineer View All Roles

How It Works

Tell Us What You Need

Share your product, technical stack, team workflow, and the specific capability you need. We listen before we propose.

We Match the Right Talent

We identify engineers who fit your technical requirements, communication style, and collaboration preferences. You review and approve.

Integrated From Day One

Your dedicated developer joins your team, adapts to your process, and starts contributing from the first sprint.

Direct Collaboration

No communication layers. Your developer works directly with your team — daily standups, code reviews, and sprint planning.

Engagement Benefits

Skip lengthy hiring cycles and recruitment overhead

Scale your team up or down as roadmap needs change

Direct collaboration with your existing team and processes

Clear ownership and accountability for delivered work

Modern engineering practices and code quality standards

Flexible engagement — project-based or long-term

What to Expect

Can evaluate AI feasibility for business problems
Understands AI limitations and failure modes
Builds with proper observability and evaluation
Balances AI capability with production reliability

Key Responsibilities

Integrate LLM APIs (OpenAI, Anthropic, open-source models) into applications

Build RAG systems with vector databases and semantic search

Implement AI-powered features — summarization, classification, extraction

Design AI workflows with proper error handling and fallbacks

Build monitoring and evaluation for AI system performance

Implement prompt engineering and optimization strategies

Create AI-powered search and knowledge retrieval systems

Collaborate with product teams on AI feature requirements

Core Skills

PythonLLM APIs (OpenAI, Anthropic)LangChain / LlamaIndexVector databases (Pinecone, Weaviate, pgvector)RAG patternsPrompt engineeringFastAPI / Node.jsMLOps basics

Common Use Cases

Building AI-powered features for existing products

Implementing document intelligence and processing

Creating knowledge assistants and chatbots

Building semantic search and recommendation systems

AI workflow automation and optimization

Ready to hire a dedicated ai engineer?

Tell us who you need. We will help you find the right fit for your team, product, and workflow.

Tell Us Who You Need