Generative AI & LLMs
Hire AI developers to build assistants, grounded search and useful AI workflows, with experience in retrieval, model evaluation and application integration.
Hire Dedicated AI Developers for Generative AI Projects
Tell us the model, data, platform and product outcome you need. We’ll help you hire AI developers who fit the work your team needs next.
- NDA protected
- Global timezone overlap
- Flexible engagement
Companies we have worked with
48-hour shortlist targetAfter requirements are understood, subject to availability.
Interview firstAssess technical fit before choosing an engineer.
One specialist or a teamShape the engagement around your roadmap.
Skills our AI engineers bring
From the first data pipeline to production deployment, bring the right engineering expertise into your team.
Machine learning
An ML developer turns structured data into forecasting, ranking and recommendation systems, with reproducible experiments and evaluation against your goals.
Natural language processing
Make documents and conversations useful. Add specialists for semantic search, classification, entity extraction and domain-specific text processing.
Computer vision
Hire AI engineers for image and video understanding, from visual inspection to object detection, with testing for real operating conditions.
Data engineering & analytics
Give AI product development a reliable foundation with ingestion, transformation, data quality checks and pipelines connecting experiments to production.
MLOps & cloud deployment
An ML developer can take models beyond the notebook with serving, versioning, monitoring and automated delivery. Plan access, rollback and inference costs from the start.
What your AI team can build
Start with the problem your users need solved. Match the engineering skills to your data, industry and operating environment.
Knowledge assistants
Enterprise & education
AI developers help teams search company documents and find answers with source references, permissions and a route to human support.
Intelligent operations
Banking & financial services
Support document processing, analyst workflows and risk signals, with audit trails and human review built into the requirements.
Research & imaging workflows
Healthcare & life sciences
Discuss engineering support for machine learning in drug discovery, research data and imaging, under your scientific team’s direction and validation.
Predictive product features
Retail & manufacturing
Add AI developers for recommendations, semantic product search, demand forecasting and visual inspection in the systems your teams already use.
Help support teams find the right answers.
See how AI devs could connect company guides to the questions people ask at work.
01 / The problem
Support agents search through separate documents to answer a customer’s question.
02 / The approach
Bring selected guides into an assistant that retrieves relevant information and shows its source.
03 / The intended outcome
Put the answer and the supporting guide in one place, with a clear route to a person when needed.
Customer support assistantExample
How can a customer reset their password?
✳
Use the password reset guide.
Ask the customer to choose “Forgot password” on the sign-in page. They can use the email link to set a new password. If they cannot access their email, contact the support team.
Make the answer reviewable.
- 01Use company documents
Staff can open the selected source guide and check the original instructions.
- 02Respect access permissions
People see information they are allowed to access in the underlying system.
- 03Ask a person when needed
Questions that the documents cannot answer are routed to the appropriate team.
Build around the way people work.
- Ask questions in everyday language
- Open the document behind an answer
- Send unresolved questions to a person
- Keep company guides up to date
Engineers who work as part of your team.
Technical fit matters. So do the way people collaborate, the ownership you retain and the support around the engagement.
Matched to the actual work
Share your product, data, stack and seniority needs. We focus the shortlist on AI developers whose engineering experience matches the actual work.
Interview before you choose
Explore technical decisions, communication and working style with shortlisted engineers before agreeing the engagement.
Your tools. Your workflow.
Your artificial intelligence developer contributes through your repositories, code reviews and sprint rituals. Your team sets daily priorities and owns delivery.
Support as your team evolves
Our staffing solution adapts team size, duration and collaboration hours to your roadmap, with onboarding and replacement support under the agreed terms.
A clear path from requirement to teammate.
Make room for technical fit, shared expectations and a considered start.
- 01
Define the work
To hire AI developers, share your use case, stack, data context, seniority and collaboration hours. We align on the expertise your team needs.
- 02
Meet your shortlist
Review relevant profiles and interview the engineers. Assess technical thinking and communication against your actual role.
- 03
Agree the engagement
Confirm the engineer or team, duration, pricing, confidentiality, IP ownership and onboarding responsibilities.
- 04
Build together
Our AI developers join your sprint rhythm and code reviews, with eThing available for staffing support as your roadmap evolves.
Choose how we work together
Match the team structure to the work ahead.
Individual Specialist
Add an ML developer or another AI specialist to fill a defined skill gap in your existing engineering team.
Dedicated AI Team
Combine AI developers, application engineers and data specialists in a dedicated team aligned with your roadmap.
Project Contract
Use contract staffing for a defined initiative, with engineering scope, duration and collaboration agreed before onboarding.
Examples of AI talent we can help you find.
We shape the shortlist around your requirements. These profiles illustrate the types of expertise you can discuss.
Senior Generative AI Engineer
LLMs · RAG · AI applications
Machine Learning Engineer
Model development · MLOps · data
AI Application Engineer
Product engineering · integrations · Python
Plan your next AI hire with confidence.
The process, engagement and ownership details to discuss before you start.
01How quickly can I receive AI developer profiles?
Our shortlist target for AI developers is within 48 hours after we understand your requirements. Timing depends on the specialist role, candidate availability and your interview process; the engineer’s start date is agreed separately.
02Can I interview AI engineers before hiring?
Yes. Review profiles and interview AI developers on your shortlist to assess technical decisions, communication and fit with your team before choosing an engagement.
03Can you add GenAI and LLM features to our existing product?
Yes. Share your architecture, data sources, evaluation needs and deployment environment. We can match an ML developer or a GenAI specialist to your application and integration work.
04How do engineers work with our internal team?
Through staff augmentation, engineers work in your repositories, code reviews and sprint process. You retain daily technical direction and delivery priorities, while eThing supports the engagement.
05Can I hire one specialist, a team or for a short-term project?
You can hire AI developers individually, as a dedicated team or through contract staffing for an agreed project period. The proposal sets out skills, duration, collaboration hours and candidate availability.
06Can we scale the team, and what happens if the fit is not right?
Discuss changes in team size as your roadmap evolves. Replacement support, notice periods and any associated terms are agreed in your engagement, so expectations are clear before work starts.
07How much does an AI engineering engagement cost?
Pricing depends on seniority, specialist skills, team size, collaboration hours and duration. Share your requirements for a tailored staffing solution. Scope and commercial terms are agreed before onboarding.
08How do you handle IP, confidentiality and data access?
We agree confidentiality, intellectual property, permitted tools and data access during contracting. Your team defines access permissions and any restrictions on external model providers. Required agreements and security onboarding are completed before engineers access your systems.
09How does staff augmentation compare with AI development companies?
Many artificial intelligence development companies manage a defined project and its delivery. With an embedded engineer, your team retains technical direction. We clarify scope, delivery responsibilities and ownership before proposing an engagement.
Tell us what you want to build.
We’ll help you find the AI talent.
Bring your roadmap, your requirements or your next engineering challenge.