Turn AI opportunities into production-ready solutions with experienced AI engineers specializing in Generative AI, LLMs, AI agents, machine learning, RAG, MLOps, and intelligent automation. Whether companies are looking to build an AI-powered product or integrate AI into an existing enterprise platform, Sphinx enables companies to hire AI engineers who can turn business challenges into impactful, scalable, and secure solutions.
overview
Hire AI Engineers to Build, Deploy & Scale Enterprise Solutions
Hire AI Engineers for the AI Capabilities You Need
Different AI initiatives require diverse engineering skills. Find specialists based on the outcome you want to achieve.
Hire Generative AI Engineers
Develop applications with foundation models and Large Language Models (LLMs) like business applications, content intelligence platforms, intelligent assistants, and enterprise copilots. Our GenAI engineers work by interacting with model APIs, prompt engineering, RAG architecture, structured outputs, tool calling, model evaluation, and enterprise AI integrations.
Hire AI Agent Engineers
Create AI agents capable of reasoning, utilizing tools, communicating with APIs, gathering information and performing multi-step processes. Develop systems that are agentic and can be used for customer services, knowledge management, workflow automation, research, operations, and more complex business processes.
Hire LLM Engineers
Customize, deploy, and fine-tune LLMs for enterprise applications. Implement and engineer robust LLM applications using suitable methods to prompt, select, fine-tune, infer and optimize LLM.
Hire RAG Engineers
Develop AI solutions that integrate foundation models and the specific knowledge held within an organization. Adopt document ingestion, chunking, embeddings, vector search, retrievers, reranking, grounding and response evaluation.
Hire Machine Learning Engineers
Develop predictive models for classification, forecasting, anomaly detection, recommendation systems, and intelligent decision-making. Whether it's feature engineering, deployment, or monitoring, ML engineers can play a vital role in translating business data into actionable insights.
Hire MLOps & LLMOps Engineers
Create the infrastructure and operational practices required to take AI systems into production. Automate model lifecycle management, deployment, monitoring, versioning, evaluation, and continuous improvement.
What Can AI Engineers Build for Your Business?
Move beyond AI experimentation and apply intelligent technologies to real business challenges.
Enterprise AI Copilots
Create smart assistants to assist employees in seeking information, analysis, content creation, document summarization, and business task completion.
AI Agents & Agentic Workflows
Develop AI systems that allow for reasoning, planning, invoking of tools, access to enterprise systems, and carrying out multi-step tasks with proper human supervision.
RAG-Powered Knowledge Systems
Connect LLMs to enterprise documents, databases, and knowledge repositories to provide context-aware responses grounded in organizational information.
Intelligent Process Automation
Combine AI with business workflows to automate repetitive, knowledge-intensive, and decision-support processes.
Predictive Intelligence
Use machine learning to forecast demand, identify anomalies, predict equipment failures, assess risk, and improve operational decisions.
AI-Powered Customer Experiences
Build conversational interfaces, recommendation engines, virtual assistants, personalized experiences, and intelligent support solutions.
Flexible Engagement Models to Hire AI Engineers
Choose the model that matches your AI maturity, project complexity, and engineering capacity.
Our AI Engineer Hiring Process
1
Define the AI Use Case
Share your business challenge, AI opportunity, expected outcome, data environment, and technical requirements.
2
Map the Required AI Skills
We identify the right combination of expertise, whether you need GenAI, LLM, RAG, ML, AI agents, MLOps, or data engineering capabilities.
3
Review Matched AI Profiles
Evaluate shortlisted AI professionals based on technical expertise, relevant experience, project exposure, and domain knowledge.
4
Conduct Technical Evaluation
Interview the candidates that are selected and evaluate their capabilities in addressing your particular AI engineering problems.
5
Build Your AI Engineering Team
Onboard the selected professionals and integrate them with your product, engineering, data, or technology teams.
6
Scale from PoC to Production
Enhance your AI engineering skills with your solution going from experimentation to production and enterprise scale deployment.
AI Technology Stack
Foundation Models & GenAI
• OpenAI
• Anthropic Claude
• Google Gemini
• Meta Llama
AI & ML Frameworks
• PyTorch
• TensorFlow
• Scikit-learn
• Keras
GenAI & Agentic AI
• LangChain
• LangGraph
• LlamaIndex
• Semantic Kernel
RAG & Vector Search
• Pinecone
• Weaviate
• Milvus
• Chroma
MLOps & LLMOps
• MLflow
• Kubeflow
• Weights & Biases
• DVC
Data & AI Engineering
• Python
• Apache Spark
• Databricks
• Snowflake
Why Choose Sphinx to Hire AI Engineers?
AI Engineering Success Stories
Real-world examples of how our AI engineering experts help organizations turn business challenges into successful digital outcomes.
Sphinx Worldbiz are always accommodating our diverse needs and we feel like they are a part of our company rather than an external supplier.
Frequently Asked Questions (FAQs)
What does an AI engineer do?
An AI engineer designs, develops, integrates, and deploys AI-powered applications and systems. Depending on the project, they may work with Generative AI, LLMs, RAG, AI agents, machine learning, NLP, computer vision, or MLOps.
What is the difference between an AI engineer and an ML engineer?
An AI engineer typically works across a broader range of intelligent applications, including Generative AI, LLMs, AI agents, and machine learning. An ML engineer focuses more specifically on building, deploying, and maintaining machine learning models and systems.
When should I hire an AI engineer?
You should consider hiring an AI engineer when you want to build an AI-powered product, integrate Generative AI into an existing application, automate complex workflows, develop predictive models, or move an AI proof of concept toward production.
Can I hire Generative AI engineers?
Yes. You can hire GenAI engineers with expertise in LLM applications, RAG, AI copilots, prompt engineering, agentic AI, model evaluation, and enterprise AI integration.
Can I hire AI engineers to build RAG applications?
Yes. AI engineers can design RAG architectures, which integrate LLMs with their own enterprise data, through the process of document processing, embedding, vector search, retrieval pipelines, and response evaluation.
Can I hire AI engineers to develop AI agents?
Yes. AI agent engineers can build agentic systems capable of interacting with tools, APIs, databases, and enterprise applications to execute multi-step tasks and workflows.
What skills should I look for when hiring an AI engineer?
Yes. AI agent engineers can build agentic systems capable of interacting with tools, APIs, databases, and enterprise applications to execute multi-step tasks and workflows.
Can AI engineers take a project from PoC to production?
Yes. Utilized with proper engineering skills, AI groups can help throughout the entire lifecycle, from validating the use case and prototyping, to application development, deployment, monitoring, evaluation and optimization.
How quickly can I hire an AI engineer?
The timeline will vary based on the specialization required with AI, level of experience, project complexity and the number of resources required. Sphinx’s structured approach ensures the alignment and placement of AI engineering talent according to your needs.
How much does it cost to hire an AI engineer?
The price will vary depending on the experience, specialization, complexity of the project, time of engagement and technology demands. Discuss your needs with Sphinx and receive a custom-made proposal of engagement.