Hiring full-time in the US
- 3-6 months to hire and onboard
- $150K-$250K+ in total comp
- Significant ESOP expectations
- Benefits, payroll, admin overhead
- Long notice periods if it doesn't work out
Hire AI Engineers
Stop searching. Start building.
Hiring great engineers in the US takes 3-6 months and costs a fortune. Ours are available now, AI-native, and ready to work within days - not months.
Days
To get started, not months
3-mo
Minimum commitment - no long lock-ins
2 weeks
Hands-on trial before you commit
US overlap
Available through noon ET every day
The Hiring Problem
Hiring in the US is slow, expensive, and uncertain.
Every month you spend recruiting is a month you're not building. And even when you hire, onboarding takes another 2-3 months before someone's truly productive.
Contracting through Tequity
- Start within days - engineers available now
- Fraction of US hiring cost
- No equity, no benefits overhead
- 3-month minimum, flexible from there
- 2-week hands-on trial before committing
Who You're Getting
Not just available. Actually excellent.
We don't outsource hiring. Every engineer at Tequity is trained, vetted, and held to a standard.
AI-native
Fluent in LLM APIs, agentic workflows, and AI tooling. Not just users of AI - actively building with it daily.
Excellent communicators
Strong written and spoken English. Comfortable in async and live collaboration with US based teams.
US time overlap
5+ hours of overlap with US East Coast every day. Enough overlap for standups, reviews, and real-time collaboration.
High ownership
They don't wait to be told what to do. They take problems end-to-end and flag blockers early.
Ready immediately
We almost always have engineers available to start. No pipeline delays, no notice period waiting.
Flexible commitment
Start with 3 months. Extend as you go. Scale up or down based on what the product needs.
Engineers in Production
Where our engineers have shipped real systems.
Client name withheld
Breaking the Language Barrier in Healthcare with Real-Time AI Translation
End-to-end HIPAA-compliant engineering for a US health-tech company building a real-time clinical translation engine - sub-second latency, hallucination detection, and edge-case-language support, all in production.
50,000+ voice minutes of real-time medical translation per month
MonkSpaces
AI Real Estate Agent for MonkSpaces Commercial Leasing
Deployed an autonomous AI agent that qualifies leads, answers queries, and schedules tours — reducing sales team workload by 60%.
60% reduction in sales team workload
Port of Corpus Christi
Unifying Port Operations Data at the Port of Corpus Christi
Tequity is delivering POCC's operational visibility platform on Azure and Power BI - data lake on Terraform, AIS and JDE pipelines live, executive dashboards underway. A real public-sector data integration build, end to end.
Azure + Microsoft Fabric environments provisioned with Terraform
Intellomatic (Sovereign Solutions)
Digitizing Field Sales Operations with Intellomatic
A multi-year recurring engineering engagement on Intellomatic's field sales platform - covering React Native modernization, geofencing upgrades, VAPT clearance, and tenant-specific builds for enterprise customers including Adani.
5,000+ Daily Active Users across enterprise deployments
AI Capabilities
Built for the AI era - not just catching up to it.
Our engineers aren't just using AI tools to write faster code. They understand AI at a systems level - how to build with it, deploy it, and make it production-ready.
LLM API integrationAgentic workflowsAgent orchestrationRAG pipelinesOpen-source modelsFine-tuningLangChain / LangGraphVector databasesAI observabilityPrompt engineering
LLM integration and pipelines
Comfortable building on OpenAI, Anthropic, Gemini, and open source models. Know when to use which.
Agentic workflow development
Building multi-step AI agents, tool use, memory systems, and orchestration layers.
RAG and vector infrastructure
End-to-end retrieval-augmented generation pipelines with chunking, embedding, and retrieval optimization.
Open-source model deployment
Growing comfort with Llama, Mistral, and other open source implementations for self-hosted use cases.
How It Works
From first call to first PR in days.
We keep it simple. No lengthy procurement, no drawn-out negotiations.
1
Tell us what you need
Role, stack, experience level, and timeline. We'll shortlist matching engineers within 24 hours.
2
Interview our engineers
You interview the shortlist. Technical, cultural, communication - evaluate them exactly as you would a full-time hire.
3
2-week hands-on trial
Work with your chosen engineer on a real task for two weeks. No commitment until you're sure.
4
Start building
Sign a 3-month contract and get going. Extend, scale, or adjust as the product evolves.
Roles Available
Every role your product team needs.
From product strategy through to QA. All available on a contract basis.
AI / ML Engineer
Varies by experience
From $6,000/mo
Senior Engineer
7+ years
From $5,000/mo
Mid-Level Engineer
3-6 years
From $3,500/mo
Product Manager
5+ years
From $5,000/mo
Product Designer
3-6 years
From $4,000/mo
Platform Architect
10+ years
From $10,000/mo
From the Blog
Related Reading
Business
How to Hire AI Engineers (What to Look For Beyond the Resume)
AI engineering is a new discipline. The standard software engineering interview process doesn't find the best candidates.
Deepak Bhagya
Co-Founder & Head of Delivery
Business
Contract Engineers vs In-House: When to Choose What
The build-vs-hire decision is one of the most consequential choices for early-stage startups. Here's our framework.
Ajay Kumar
Co-Founder & Director
General
Why Startups in the US Should Work With Tequity
Offshore development gets a bad reputation. Here's why the model works differently when your partner specialises in AI products and operates with product-first thinking.
Ajay Kumar
Co-Founder & Director
LET'S TALK
Your next engineer is already available.
Tell us what you need. We'll have a shortlist ready within 24 hours.