Hire Generative AI Developers
Hire generative AI developers to build secure, scalable, and business-ready applications powered by large language models. Add pre-vetted GenAI engineers to your team for custom AI assistants, RAG systems, content generation, workflow automation, and enterprise AI solutions.
Hire GenAI DevelopersHire GenAI Developers for Advanced AI Solutions
Our generative AI developers design, build, integrate, and optimize GenAI solutions around your business data and workflows. Hire dedicated generative AI engineers for complete support, from model selection and prototyping to deployment, monitoring, and continuous improvement.
Generative AI Consulting
Build a practical GenAI roadmap based on your business goals, data readiness, technical environment, and budget. Our consultants identify suitable use cases across content generation, knowledge retrieval, document processing, customer support, and workflow automation while defining the right model, architecture, deployment strategy, and success metrics.
Generative AI Model Engineering
Hire generative AI developers to architect and build scalable GenAI solutions using transformer-based models, model APIs, and open-source architectures. We develop memory-aware applications, structured prompt workflows, human-in-the-loop controls, and multi-step AI systems that convert natural-language requests into reliable application actions.
Generative AI Model Adaptation
Adapt foundation models to support your domain terminology, business rules, output formats, and application requirements. Our GenAI engineers use prompt optimization, retrieval augmentation, supervised fine-tuning, and model distillation where technically and legally appropriate, while preserving output quality, latency, and deployment flexibility.
Multimodal AI Development
Build GenAI applications that understand and generate content across text, images, audio, video, and documents. Our developers combine multimodal models, cross-modal embeddings, speech technologies, and vision-language capabilities to create visual search, document intelligence, media analysis, and interactive AI experiences.
RAG Pipeline Development
Connect generative AI models with approved enterprise knowledge sources through retrieval-augmented generation. We build ingestion pipelines, embedding workflows, vector search, metadata filtering, semantic retrieval, reranking, and context assembly to produce responses grounded in relevant business information.
Model Integration and Deployment
Integrate generative AI capabilities into web applications, mobile apps, SaaS products, CRMs, ERPs, and internal systems through secure APIs. Our developers implement model routing, access controls, fallback logic, output validation, streaming responses, and cloud or private deployment based on your infrastructure requirements.
Generative AI Model Fine-Tuning
Fine-tune suitable models using domain-specific datasets, terminology, instructions, and expected output patterns. Our engineers apply methods such as supervised fine-tuning, LoRA, and QLoRA to improve response relevance and consistency while controlling infrastructure requirements and training costs.
Generative AI Performance Optimization
Improve model latency, throughput, reliability, and inference cost for production workloads. Our GenAI engineers optimize prompts, retrieval settings, context windows, caching, batching, model routing, and deployment configurations while benchmarking output quality against defined evaluation criteria.
Generative AI Support and Maintenance
Maintain the performance and reliability of your GenAI application after deployment. Our team monitors retrieval quality, output consistency, model behavior, latency, token usage, and integration health while supporting prompt updates, model migrations, security improvements, regression testing, and knowledge-base refreshes.
Discover Our Generative AI Success Story
See how our generative AI developers turn repetitive, content-heavy processes into faster and more manageable digital workflows.
AI Product Details – An AI-Powered Shopify SEO Automation App
AI Product Details is a Shopify app that helps merchants automate SEO-optimized product titles, descriptions, tags, and meta fields using advanced AI models. Designed for stores with large inventories, it enables fast, scalable, and customizable content creation.- Automatically generate SEO-friendly content in bulk with webhook support.
- Customize tone, language, and formality to match your brand voice.
HireBeep - An AI-Driven Talent Acquisition Platform
HireBeep is an online recruitment software that helps businesses streamline hiring by automating candidate screening, job posting, and applicant tracking. The platform uses AI to identify top talent quickly and reduces time-to-hire.- Post jobs across multiple sites and manage applicants in one place.
- Track progress, collaborate with your team, and make data-driven hiring decisions.
Summrised - AI-Powered Book Summary and Podcast App
Summrised is an AI-driven content platform that transforms books into engaging summaries and podcasts using GPT-4 and text-to-speech technology. It helps creators and readers consume knowledge faster through automated insights and audio storytelling.- Extract key themes and generate structured summaries.
- Convert books into full podcast episodes with TTS.
CalCounts – An AI-Powered Calorie Tracking App
CalCounts is a smart nutrition and fitness app that helps users achieve health goals by tracking meals, macros, and calories using AI. The app simplifies healthy eating with barcode scanning, food photo analysis, and goal-based meal planning.- Scan food, barcodes or upload meal photos to get instant calorie and macro breakdowns.
- Track progress, plan meals, and stay on top of your fitness goals with AI-powered insights.
Cellarco – A Gamified Product Learning App
Cellarco is a gamified education platform designed for retail associates to learn about products through interactive content like videos, quizzes, and brand sheets. It features an AI-powered chatbot for real-time, contextual product support.- Learn via interactive videos, quizzes, and sell-sheets.
- Get instant answers with AI-driven product assistant.
Technology Stack of Our GenAI Developers
Hire generative AI engineers skilled in leading models, frameworks, vector databases, cloud platforms, and deployment technologies required for production-ready GenAI applications.
Programming Languages
-
Python -
JavaScript -
TypeScript -
Java -
SQLite
Large Language Models
-
GPT-3 -
Anthropic/Claude -
Llama -
Mistral -
Gemini
GenAI Frameworks
-
LangChain -
Hugging Face Transformers -
LlamaIndex -
Semantic Kernel
Vector Databases
-
Pinecone -
Weaviate -
Milvus -
pgvector -
Chroma -
FAISS
AI Agent Frameworks
-
LangGraph -
AutoGen -
CrewAI -
Semantic Kernel
Backend and APIs
-
Fast API -
Flask -
NodeJS -
RESTful APIs -
GraphQL
Cloud AI Platforms
-
Azure AI Foundry -
AWS -
Google Vertex AI
Data and Storage
-
PostgreSQL -
MongoDB -
Redis -
ElasticSearch -
Amazon S3
Deployment and Monitoring
-
Docker -
Kubernetes -
MLflow -
Github -
Jenkins
Flexible Hiring Models for GenAI Developers
Choose an engagement model based on your GenAI project scope, delivery timeline, internal capabilities, and need for ongoing model improvement.
Dedicated Developers
For long-term projects, hire dedicated developers who work as an extension of your team. This model gives you full control, scalability, and consistent delivery aligned with your business goals.
- Transparent monthly pricing
- Full-time or part-time engagement
- Direct communication & control
- Quick onboarding in 24 hours
Time & Material
Perfect for evolving projects where requirements change frequently. Pay only for the time and resources utilized, ensuring flexibility and cost efficiency.
- Pay-as-you-go model
- Flexible scope & iterations
- Transparent hourly billing
- Ideal for MVPs & experimentation
Fixed Cost (Project-Based)
Best suited for clearly defined projects with fixed scope, timeline, and budget. Get predictable outcomes with structured planning and milestone-based execution.
- Fixed budget & timeline
- Clearly defined deliverables
- Milestone-based payments
- Low risk with predictable outcomes
Hire GenAI Developers in 24 Hours
Share your GenAI use case, required technical skills, preferred models, integrations, project scope, and timeline with our team. We will shortlist matched generative AI developer profiles for your review, arrange direct technical interviews, and help you onboard the selected engineer within 24 hours, subject to profile availability and final approval.
Share Your Requirements
Tell us about your use case, preferred models, data sources, integrations, security requirements, technology stack, and project timeline.
Review Matched Profiles
Receive relevant profiles of pre-vetted generative AI developers selected according to your technical and business requirements.
Conduct Technical Interviews
Interview shortlisted developers and assess their experience in LLMs, RAG, AI agents, prompt design, integrations, evaluation, security, and deployment.
Select Your GenAI Developer
Choose an individual engineer or dedicated generative AI development team that fits your project, communication needs, and engagement model.
Begin Development in 24 hours
Complete onboarding and provide approved access to repositories, data sources, development environments, documentation, and communication tools.
Why Choose Codiant’s GenAI Developers?
Build your generative AI solution with an experienced technology team, flexible hiring options, and complete support from initial discovery through deployment.
1500+
Project launched450+
Inhouse Engineers19+
Years of Experience70%
Repeat Clients & Referrals
Top Mobile App Development Company in USA, UK, Australia (Good Firms)
Best User Experience Company 2023 (Software Suggest)
Best Website Development Company for Online Success 2023 (CyberNews)
Why Hire Generative AI Developers from Codiant?
Finding developers who understand both GenAI experimentation and production software can be difficult. When you hire generative AI developers from Codiant, you get pre-vetted professionals who can build, integrate, evaluate, deploy, and improve GenAI applications around your business requirements.
Hire GenAI developers experienced in large language models, RAG, AI agents, prompt engineering, vector databases, APIs, cloud platforms, and application development.
Get support across discovery, architecture, prototyping, data preparation, development, integration, evaluation, deployment, monitoring, and optimization.
Hire one remote generative AI developer or expand to a dedicated generative AI development team as your requirements evolve.
Build GenAI applications with role-based access, permission-aware retrieval, output controls, auditability, monitoring, and integration with enterprise systems.
Work directly with dedicated or offshore generative AI developers who align with your preferred communication tools and working hours.
Continue improving output quality, retrieval performance, latency, reliability, token usage, model selection, and application performance after deployment.
Frequently Asked Questions
A Generative AI developer can build AI assistants, RAG systems, content-generation tools, AI agents, enterprise search platforms, document-processing solutions, and multimodal applications. They can also integrate GenAI features into your existing web, mobile, SaaS, CRM, or ERP systems.
Look for experience with Python or TypeScript, LLM APIs, prompt engineering, RAG, vector databases, embeddings, AI agents, model evaluation, cloud deployment, and application integration. The developer should also understand output validation, access controls, monitoring, latency, and inference-cost optimization.
Yes. You can hire Generative AI developers to enhance, troubleshoot, or scale an existing application. They can assess your current architecture, improve prompts and retrieval pipelines, integrate new models, add GenAI features, optimize performance, strengthen security controls, or prepare a prototype for production deployment.
Yes. Generative AI developers can build applications using commercial models such as GPT, Claude, and Gemini, as well as suitable open-source models such as Llama and Mistral. Model selection should reflect your use case, output requirements, data policies, infrastructure, latency, and budget.
Codiant can help you begin onboarding a dedicated Generative AI developer within 24 hours. Share your project requirements, review matched profiles, interview shortlisted engineers, and select the right candidate. The final timeline remains subject to profile availability, interview completion, and your approval.
The cost is based on the developer’s experience, required GenAI skills, project duration, team size, technical complexity, and engagement model. Dedicated monthly hiring suits ongoing development, time-and-material works for evolving requirements, and fixed-cost engagement is suitable for projects with clearly defined deliverables.
