AI-Native Full-Stack Engineer
Builds production-ready AI functionality across frontend, backend, APIs, admin panels, SaaS platforms, internal tools, and product workflows
Hire AI Engineers
Hire AI-native engineers in as little as 48 hours to build AI features, integrate LLMs, and turn AI-generated prototypes into production-ready software.
Whether you need one senior AI engineer, dedicated AI engineers, or a small AI engineering team, SolveIt helps you add senior AI engineering capacity fast.
AI Product Engineer
Turns AI ideas into clear product scope, aligning user flows, AI behavior, acceptance criteria, technical constraints, and release requirements.
AI Mobile Developer
Adds AI functionality to native iOS/Android and cross-platform Flutter apps: from assistants, smart search, voice, camera, and personalization to secure API integrations, performance.
AI Agent Developer
Builds AI agents for customer support, operations, document workflows, research, and task automation.
LLM / RAG Engineer
Integrates large language models with your product data, documents, knowledge base, and internal systems.
AI Automation Engineer
Automates manual workflows with AI-powered classification, data extraction, routing, reporting, and decision support.
AI DevOps / Production Engineer
Helps deploy, monitor, optimize, and scale production-ready AI systems.
AI QA / Evaluation Engineer
Tests AI outputs, edge cases, regressions, reliability, and release risks before production.
AI-Native Full-Stack Engineer
Builds production-ready AI functionality across frontend, backend, APIs, admin panels, SaaS platforms, internal tools, and product workflows
AI Product Engineer
Turns AI ideas into clear product scope, aligning user flows, AI behavior, acceptance criteria, technical constraints, and release requirements.
AI Mobile Developer
Adds AI functionality to native iOS/Android and cross-platform Flutter apps: from assistants, smart search, voice, camera, and personalization to secure API integrations, performance.
AI Agent Developer
Builds AI agents for customer support, operations, document workflows, research, and task automation.
LLM / RAG Engineer
Integrates large language models with your product data, documents, knowledge base, and internal systems.
AI Automation Engineer
Automates manual workflows with AI-powered classification, data extraction, routing, reporting, and decision support.
AI DevOps / Production Engineer
Helps deploy, monitor, optimize, and scale production-ready AI systems.
AI QA / Evaluation Engineer
Tests AI outputs, edge cases, regressions, reliability, and release risks before production.
AI-Native Full-Stack Engineer
Builds production-ready AI functionality across frontend, backend, APIs, admin panels, SaaS platforms, internal tools, and product workflows
AI Product Engineer
Turns AI ideas into clear product scope, aligning user flows, AI behavior, acceptance criteria, technical constraints, and release requirements.
AI Mobile Developer
Adds AI functionality to native iOS/Android and cross-platform Flutter apps: from assistants, smart search, voice, camera, and personalization to secure API integrations, performance.
AI Agent Developer
Builds AI agents for customer support, operations, document workflows, research, and task automation.
LLM / RAG Engineer
Integrates large language models with your product data, documents, knowledge base, and internal systems.
AI Automation Engineer
Automates manual workflows with AI-powered classification, data extraction, routing, reporting, and decision support.
AI DevOps / Production Engineer
Helps deploy, monitor, optimize, and scale production-ready AI systems.
AI QA / Evaluation Engineer
Tests AI outputs, edge cases, regressions, reliability, and release risks before production.
Why clients trust SolveIt
10+
years of experience
100%
customer satisfaction score
25M+
happy end-users
100+
in-house professionals
50+
reviews on Clutch
100+
solutions released
15%
certified experts
55%
seniors
30%
middles
Featured in
AI engineer roles we can help you hire
You can hire one specialist, add dedicated AI engineers to your team, or form a small AI-native engineering team around a specific product goal.
AI-Native Full-Stack Engineer
Builds production-ready AI functionality across frontend, backend, APIs, admin panels, SaaS platforms, internal tools, and product workflows
AI Product Engineer
Turns AI ideas into clear product scope, aligning user flows, AI behavior, acceptance criteria, technical constraints, and release requirements.
AI Mobile Developer
Adds AI functionality to native iOS/Android and cross-platform Flutter apps: from assistants, smart search, voice, camera, and personalization to secure API integrations, performance.
AI Agent Developer
Builds AI agents for customer support, operations, document workflows, research, and task automation.
LLM / RAG Engineer
Integrates large language models with your product data, documents, knowledge base, and internal systems.
AI Automation Engineer
Automates manual workflows with AI-powered classification, data extraction, routing, reporting, and decision support.
AI DevOps / Production Engineer
Helps deploy, monitor, optimize, and scale production-ready AI systems.
AI QA / Evaluation Engineer
Tests AI outputs, edge cases, regressions, reliability, and release risks before production.
AI tools and technologies our engineers work with
Our AI-native engineers combine modern AI tools with proven product engineering practices, so speed does not come at the cost of architecture, security, QA, or production readiness.
AI approaches and use cases
LLM IntegrationRAGAI AgentsGenerative AINLPSemantic SearchAI Workflow AutomationDocument ProcessingOCRRecommendationsPersonalizationClassificationSummarizationAI-Powered Search
AI-assisted development tools
CursorClaude CodeOpenAI CodexChatGPTGitHub Copilot
Vector databases and data storage
PineconeWeaviateQdrantChromaPostgreSQLMongoDBRedisMySQL
LLM providers and APIs
OpenAIAzure OpenAIAnthropic ClaudeGoogle GeminiMistralOpen-Source LLMs
RAG, agents, and knowledge systems
LangChainLangGraphLlamaIndexLangSmithVector DatabasesEmbeddingsSemantic SearchFunction CallingTool CallingRetrieval PipelinesPrompt ManagementEvaluation Workflows
AI / ML frameworks and libraries
PyTorchTensorFlowKerasScikit-LearnHugging Face TransformersSentenceTransformersXGBoostLightGBMOpenCVSpaCy
Product engineering stack
PythonFastAPINode.jsReactNext.jsFlutterReact NativeTypeScriptSQL
Cloud, DevOps, and production
AWSAzureDockerKubernetesGitHub ActionsCI/CDMonitoringLoggingTest AutomationSentryMLflowDVCSecurity ReviewPerformance OptimizationCost Control
Need AI engineers who can work with your stack?
Match AI Engineers
AI-native engineers vs AI developers vs ML engineers
Different AI roles solve different problems. We help you choose the right profile based on your product, codebase, roadmap, and delivery model.
If you are looking to hire AI-native developers, hire AI product engineers, or hire generative AI engineers, the best choice depends on what you need to ship – an AI feature, a production-ready system, a refactored prototype, or a long-term AI engineering team.
Role
Best for
AI developer
Building AI-powered features and integrations
AI engineer
Designing LLM, RAG, agent, data, and AI system flows
Generative AI engineer
Building GenAI features with LLMs, prompts, retrieval, and automation
ML engineer
Training, tuning, and deploying machine learning models
AI-native engineer
Using AI-assisted workflows to build, refactor, and ship product software faster
AI product engineer
Connecting product logic, UX, backend, AI capabilities, and release readiness
AI developer
Building AI-powered features and integrations
AI engineer
Designing LLM, RAG, agent, data, and AI system flows
Generative AI engineer
Building GenAI features with LLMs, prompts, retrieval, and automation
ML engineer
Training, tuning, and deploying machine learning models
AI-native engineer
Using AI-assisted workflows to build, refactor, and ship product software faster
AI product engineer
Connecting product logic, UX, backend, AI capabilities, and release readiness
What our AI engineers can help you build
Vibe coding cleanup
Clean up AI-built MVPs with stronger structure, backend logic, QA, security checks, and production-ready engineering practices before you scale.
AI features for existing products
Add AI search, recommendations, personalization, content generation, document processing, voice and text features, AI assistants, and AI-powered admin workflows to your current product.
AI prototype refactoring
Turn prototypes built with Cursor, Claude Code, Codex, ChatGPT, Lovable, or Bolt into cleaner, more stable software ready for real users.
AI-generated code review
Get a senior engineering review of your AI-generated codebase to identify architecture gaps, security risks, weak logic, missing tests, and scalability issues.
AI agents and workflow automation
Build AI agents that classify requests, extract data, route tasks, generate summaries, and automate repetitive workflows across support, operations, and back-office teams.
LLM integration and RAG development
Connect LLMs, vector databases, and internal data sources to build document-aware assistants, knowledge tools, and customer-facing AI search experiences.
Have a specific AI use case in mind?
Get AI estimate
Why hire AI engineers from SolveIt?
Talent platforms help you find people. SolveIt helps you add AI engineering capacity that fits exactly your product, codebase, and delivery process.
With SolveIt, you get:
- Product engineering background, not just AI experimentation.
- Experience across mobile, web, backend, integrations, and admin systems.
- Ability to build AI features inside existing products.
Senior AI / ML Full-Stack Engineer
Vetted & Ready to onboard in 48h
- 6+ years in commercial dev
- 3+ years in LLM & RAG
- Flexible formats: one engineer, dedicated AI engineers, pod, feature team, or review sprint.
- Strong fit for funded startups and SMB product teams.
- Focus on production readiness, QA, security, and maintainability.
- Delivery support from a team that has been building digital products since 2016.
Trusted by 100+ clients
AI product engineering cases
AI caregiving mobile & web platform
Relaunched a complex care platform as a unified AI-powered product with mobile and web apps. The solution supports smarter care coordination, emotional support, and scalable growth for caregiving teams and families.
5.0
Read more
AI productivity app
Launched an AI-powered personal assistant across iOS and macOS. The app combines smart planning, voice interaction, and Apple ecosystem integration to help users organize daily tasks faster.
5.0
Read more
Energy saving app
Validated the product idea with a native MVP powered by a custom AI recommendation engine. The app helped users reduce electricity costs by 23% in beta and 26% after launch.
5.0
Read more
Real estate website and client app
Created an AI-powered property search experience that helps users find relevant listings faster. The assistant understands English and Arabic requests, asks clarifying questions, structures search criteria, and suggests alternatives when exact matches are unavailable.
5.0
Read more
See more SolveIt projects
Explore our portfolio
What our clients say
CEO & Founder, RVista Ventures
“What impressed me most about SolveIt was their unique blend of creativity, hunger, and intelligence.”
CEO, Hemie
“Their innovative approach, combined with their commitment to our project's success, truly sets them apart.”
CEO, IT Company
“The responsiveness of the team members was highly commendable. They were all more than willing to jump in, answer questions, and iterate on our deliverables.”
Founder & CEO, ClapClapBoom
“The SolveIt team has been the epitome of professionalism. They're very knowledgeable, great to collaborate with and deliver outstanding quality.”
Head of IT, DentMe
“The project delivered clear, measurable outcomes that demonstrated both visual and business impact. We saw a noticeable improvement in conversion rates after launch”
CEO & Co-Founder, Out Co.
“They are a very communicative and kind team. They were excited about the project and they helped us complete the app quickly and beautifully.”
Project Manager, IT Services Company
“We're impressed by the quality of their service, both in project management and in execution.”
Founder & CEO, Gumb
“They were flexible, pivoting when we needed to change the project scope. We felt like a team with common goals.”
Choose the right AI engineering model
Model
Best for
One AI-native engineer
You need one senior contributor inside your existing product team
Dedicated AI engineers
You need ongoing AI engineering capacity for your roadmap
AI engineering pod
You need frontend, backend, AI, QA, and PM support
AI feature team
You need to ship one specific AI feature
AI prototype refactoring sprint
You have an AI-generated MVP or PoC that needs cleanup
AI code review sprint
You need to understand architecture, security, and scalability risks first
Principal Engineer & Security Lead
Focus
Deep architecture analysis, security gap identification, and scalability risk review
Skills
Senior AI / Full-Stack Engineer
Focus
Seamless integration into your team, end-to-end feature ownership
Skills
AI Systems Architect & Senior Devs
Focus
Turning AI-generated PoCs into clean, enterprise-grade production code
Skills
Targeted Feature Team
Focus
Rapid end-to-end implementation of specific AI capabilities
Skills
Cross-Functional AI Pod
Focus
Full delivery cycle from architecture to production release
Team
AI Engineering Capacity
Focus
Long-term development velocity, continuous delivery
Skills
Principal Engineer & Security Lead
Focus
Deep architecture analysis, security gap identification, and scalability risk review
Skills
Senior AI / Full-Stack Engineer
Focus
Seamless integration into your team, end-to-end feature ownership
Skills
AI Systems Architect & Senior Devs
Focus
Turning AI-generated PoCs into clean, enterprise-grade production code
Skills
Targeted Feature Team
Focus
Rapid end-to-end implementation of specific AI capabilities
Skills
Cross-Functional AI Pod
Focus
Full delivery cycle from architecture to production release
Team
AI Engineering Capacity
Focus
Long-term development velocity, continuous delivery
Skills
Principal Engineer & Security Lead
Focus
Deep architecture analysis, security gap identification, and scalability risk review
Skills
Senior AI / Full-Stack Engineer
Focus
Seamless integration into your team, end-to-end feature ownership
Skills
AI Systems Architect & Senior Devs
Focus
Turning AI-generated PoCs into clean, enterprise-grade production code
Skills
Targeted Feature Team
Focus
Rapid end-to-end implementation of specific AI capabilities
Skills
Cross-Functional AI Pod
Focus
Full delivery cycle from architecture to production release
Team
AI Engineering Capacity
Focus
Long-term development velocity, continuous delivery
Skills
You do not always need a full AI department. Sometimes one senior engineer is enough. Sometimes the right choice is a small AI engineering pod or a focused sprint.
We help you choose the format based on your product stage, roadmap, internal team, and expected outcome.
Choose your AI engineering model
Talk to AI Engineer
Get matched with AI engineers fast
Hiring AI talent can take weeks or months. SolveIt helps you move faster by matching your product needs with the right AI engineering setup.
Share your requirements
Tell us about your product, tech stack, AI goals, timeline, and the type of support you need.
Get a recommended setup
We suggest the right format: one AI-native engineer, dedicated AI engineers, a small pod, a feature team, or a refactoring sprint.
Review relevant profiles
Get relevant AI engineer profiles or a team composition based on your product needs and technical requirements.
Start with a focused scope
Begin with a feature, sprint, review, or integration task to validate fit and move quickly.
AI-native engineering capabilities
From feature delivery to production support, SolveIt can cover the key engineering layers your AI roadmap needs.
Build
Integrate
Stabilize
Scale
Build
AI features, assistants, workflows, and user-facing functionality.
Integrate
LLMs, APIs, vector databases, CRMs, internal tools, and backend systems.
Stabilize
AI-generated code, architecture, tests, security gaps, and release risks.
Scale
Performance, cloud setup, monitoring, cost control, and maintainability.
Build
AI features, assistants, workflows, and user-facing functionality.
Integrate
LLMs, APIs, vector databases, CRMs, internal tools, and backend systems.
Scale
Performance, cloud setup, monitoring, cost control, and maintainability.
Stabilize
AI-generated code, architecture, tests, security gaps, and release risks.
Need AI engineering support across your roadmap?
Build AI Team
AI engineering for your industry
AI-native engineers can support different product and operational contexts – from AI-powered user experiences to internal workflow automation.
How our AI-native engineers join your product team
Step 01
Product and codebase review
We review your product, roadmap, codebase, architecture, and AI goals to understand where extra engineering capacity will create the most value.
Step 02
Engineer or pod matching
We recommend the right engineer profile or team setup based on your technical stack, delivery model, and product priorities.
Step 03
Workflow integration
Our engineers join your tools and processes: Jira, GitHub, Slack, sprint planning, code review, QA, and release management.
Step 04
AI-assisted delivery
We use AI tools where they improve speed and productivity, while senior engineers keep control over architecture, QA, security, and production readiness.
Step 05
Knowledge transfer
You keep ownership of the code, documentation, product knowledge, and technical decisions.
Related services
Need more than AI engineering capacity? Explore related SolveIt services for product strategy, design, development, and dedicated engineering support.
AI development services
Build AI-powered features, assistants, automation, RAG systems, and intelligent product workflows.
MVP development services
Validate your product idea with a focused MVP before scaling into a full product.
Discovery phase services
Define product scope, technical requirements, architecture, risks, timeline, and budget before development starts.
UI/UX design services
Design clear, usable, and conversion-focused digital products for web and mobile users.
Mobile app design services
Create intuitive mobile app experiences for iOS, Android, Flutter, and cross-platform products.
Website redesign services
Improve outdated websites, product interfaces, user journeys, and conversion flows.
Web development services
Build scalable web platforms, portals, admin panels, marketplaces, and customer-facing products.
Front-end development services
Create fast, responsive, and user-friendly interfaces with modern front-end technologies.
Back-end development services
Develop reliable product logic, APIs, databases, integrations, and scalable backend architecture.
Mobile app development and consulting
Build mobile products from idea to launch with strategy, design, development, QA, and release support.
Flutter app development services
Launch cross-platform mobile apps faster with one codebase for iOS and Android.
Cross-platform app development services
Develop mobile apps for multiple platforms while optimizing delivery speed and development cost.
FAQ about hiring AI-native engineers
How fast can we hire AI engineers from SolveIt?
After we understand your product, goals, and technical requirements, we can recommend relevant AI engineer profiles or a pod setup within 2 days. The exact timing depends on the role, stack, availability, and scope.
What is an AI-native engineer?
An AI-native engineer is a software engineer who uses AI tools across the development workflow while staying responsible for architecture, code quality, testing, security, and production delivery.
How is an AI-native engineer different from an AI developer?
An AI developer usually focuses on building AI-powered features or integrations. An AI-native engineer combines product engineering with AI-assisted workflows, using AI tools to move faster while keeping the codebase maintainable and production-ready.
Can we hire dedicated AI engineers?
Yes. You can hire dedicated AI engineers for ongoing product development, AI feature delivery, LLM integration, RAG development, AI workflow automation, or prototype refactoring.
Can your engineers work with our existing product team?
Yes. Our engineers can join your current workflow and collaborate with your internal developers, product managers, designers, QA specialists, and stakeholders.
Can you review or refactor AI-generated code?
Yes. We can review AI-generated prototypes or codebases, identify architecture and security risks, improve maintainability, add missing backend logic, and prepare the product for real users.
Can you build AI features for an existing app?
Yes. We can add AI search, assistants, recommendations, document processing, content generation, workflow automation, and LLM-based features to existing mobile, web, or backend products.
Do you work with short-term AI projects?
Yes. We can support short-term needs such as AI feature delivery, codebase review, prototype refactoring, RAG integration, AI agents, or AI workflow automation.
What AI technologies do your engineers work with?
Our engineers work with LLM APIs, RAG systems, vector databases, AI agents, embeddings, semantic search, OpenAI, Anthropic Claude, Google Gemini, LangChain, LlamaIndex, Python, Node.js, React, Next.js, Flutter, and cloud infrastructure.
Can you help turn an AI prototype into a production-ready product?
Yes. We can review your prototype, stabilize the architecture, rebuild weak parts, add backend logic, improve security, implement QA, and prepare the product for release.