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.
Hire AI Engineers
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
We help you build the right AI capability based on your use case—not just a job description.
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
Sphinx leverages industry-leading AI and machine learning technologies to build intelligent, scalable, and production-ready AI platforms.
Foundation Models & GenAI
Build intelligent applications powered by state-of-the-art large language models from leading AI providers.
Expertise
• OpenAI
• Anthropic Claude
• Google Gemini
• Meta Llama
AI & ML Frameworks
Design, train, and deploy machine learning models using proven, battle-tested open-source frameworks.
Expertise
• PyTorch
• TensorFlow
• Scikit-learn
• Keras
GenAI & Agentic AI
Orchestrate multi-step reasoning, tool use, and autonomous agent workflows on top of large language models.
Expertise
• LangChain
• LangGraph
• LlamaIndex
• Semantic Kernel
RAG & Vector Search
Ground AI responses in your own data with high-performance vector databases and retrieval pipelines.
Expertise
• Pinecone
• Weaviate
• Milvus
• Chroma
MLOps & LLMOps
Track experiments, manage model lifecycles, and operationalize AI models with confidence at scale.
Expertise
• MLflow
• Kubeflow
• Weights & Biases
• DVC
Data & AI Engineering
Process, transform, and manage data at scale to fuel reliable, high-performing AI systems.
Expertise
• Python
• Apache Spark
• Databricks
• Snowflake
Why Choose Sphinx to Hire AI Engineers?
AI Engineering Beyond the Model
Build AI solutions that integrate models, data, applications, APIs, cloud, and enterprise workflows, rather than "sketchy AI experiments."
GenAI & Agentic AI Expertise
Tap into specialized talent for LLM applications, RAG systems, AI copilots, intelligent automation and AI agents.
From Proof of Concept to Production
Get the engineering capabilities required to move from experimentation to scalable deployment, operationalization, monitoring, and continuous improvement.
AI + Cloud + Data Engineering
Combine AI engineering with cloud, DevOps, data engineering, and MLOps skills to enable enterprise AI solutions.
Build Around Your Use Case
Get the right combination of AI skills based on what you are trying to build — not a one-size-fits-all resource model.
Enterprise AI Integration
Integrate AI within your different business workflows, digital platforms, data ecosystems, and enterprise applications.
AI Engineering Success Stories
Check our range of success stories to get a glimpse how our professionals have delivered next-gen solutions.
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.