TalentForge — AI Talent That Actually Delivers
AI-Focused Staffing

AI talent is everywhere.
The right AI talent isn’t.

Every company wants AI engineers. Very few know how to find ones with the right domain expertise, verify they can actually deliver, and make sure they’ll stay. Whether you’re a startup shipping your first model, an IT services firm staffing client engagements, or an enterprise modernising at scale — we solve that.

AI

AI + Domain Expertise

We match AI skills to your industry context — not just stack keywords.

48h

First Profiles in 48 Hours

Qualified, interviewed, technically assessed candidates.

Founder-Led Vetting

We’ve built AI companies. We evaluate like co-founders, not recruiters.

The Hard Truth

Why hiring AI talent
keeps failing

The AI talent market is broken in different ways for different buyers. But the root cause is the same.

1

Skills Without Domain Context

Plenty of people list PyTorch on their CV. Very few can apply it to your specific domain — whether that’s fintech fraud detection, clinical NLP, telecom network optimisation, or mining predictive maintenance. Without domain context, AI hires ship demos, not products.

2

Recruiters Can’t Evaluate AI

Traditional staffing firms match resumes to keywords. They can’t tell the difference between someone who completed a Kaggle competition and someone who shipped an LLM system to production. For IT services delivery leads and enterprise CIOs alike, that gap is expensive.

3

Misalignment Kills Retention

The most expensive AI hire isn’t a bad one — it’s a misaligned one. Someone technically strong who doesn’t actually want this role, or whose career goals don’t match the engagement. They leave in six months and you’re back to square one, mid-project.

Who We Serve

Built for how you
actually hire AI talent

Different buyers, different pain points. One shared need: AI talent that’s technically verified, domain-relevant, and ready to deliver.

Startups & Tech Companies

Ship faster with the right AI team

You’re building AI-native products or adding AI to an existing platform. You need engineers who can go from research to production — fast — without the FAANG salary arms race.

  • Senior ML/AI ICs and first technical hires
  • LLM engineers, applied scientists, AI architects
  • Contract-to-hire flexibility for runway-conscious teams
IT Services & Delivery Firms

Staff AI engagements your bench can’t

Your clients are demanding AI and GenAI capabilities. Your bench is full of strong engineers who weren’t trained for ML workloads. You need production-ready AI talent to staff client projects — without the bench cost.

  • Contract AI engineers for client engagements
  • Pre-vetted for production depth, not just certifications
  • No bench cost — deploy directly on active projects
Enterprise & Regulated Industries

AI transformation without the talent bottleneck

Banking, insurance, telecom, mining — you’re modernising at scale but the local AI talent pool is thin and internal hiring takes months. You need a partner who understands both the technology and the risk tolerance.

  • ML engineers with regulated-industry experience
  • AI leadership: Heads of AI, Chief AI Officers
  • Global sourcing for markets with limited local supply
Our Process

We don’t send resumes.
We send the right person.

We’re entrepreneurs and founders of technology companies. We understand what it takes to get the best out of a resource and how it impacts the business. We literally put ourselves in the hiring manager’s shoes to verify if a candidate will fulfil the expectations of the role.
1

Understand the Real Goal

We talk to the hiring manager — not just about the job spec, but about what they’re actually trying to accomplish. What does success look like? What’s the team dynamic? Whether it’s a client delivery engagement, a product build, or an enterprise transformation — the job description is the starting point, not the answer.

2

Source AI + Domain Expertise

We don’t just search for “ML engineer.” We search for someone who can build recommendation systems for e-commerce, deploy NLP pipelines in healthcare, architect RAG systems for enterprise, or build predictive maintenance models for industrial operations. The domain match is what separates a hire from a mis-hire.

3

Interview Every Candidate Personally

We speak to every candidate. We assess technical depth, career expectations, and motivation. A candidate who’s overqualified and bored will leave in six months. A candidate whose career goals don’t align will never perform. We screen for fit, not just skill.

4

Run Technical Assessments

We don’t outsource evaluation. Our founding team has built AI products, scaled engineering organisations, and shipped production systems. We assess system design, code quality, and problem-solving judgment the way a senior engineering leader would — because we are.

5

Verify Career + Role Alignment

Before we present anyone, we confirm the candidate is genuinely motivated for the role and it fits their career trajectory. Happy candidates stay longer, ramp faster, and deliver more. Forced placements don’t.

6

Present the Right Person

You get a shortlist — not a stack of resumes. Every candidate has been interviewed, assessed, and matched against your actual goals. We stand behind every placement because we’ve done the work to get it right.

AI Roles We Place

The modern AI stack,
covered end-to-end

From applied ML to LLM infrastructure to AI leadership — we place the roles that actually ship AI products.

Applied AI / ML

  • ML Engineers
  • Applied AI Scientists
  • Computer Vision Engineers
  • NLP / LLM Engineers
  • Recommendation Systems

AI Infrastructure

  • MLOps Engineers
  • AI Platform Engineers
  • Data Engineers (AI)
  • LLM Infrastructure
  • Vector DB / RAG Systems

AI Product & Design

  • AI Product Managers
  • Prompt Engineers
  • AI Solutions Architects
  • Technical Program Managers
  • AI UX Designers

AI Leadership

  • Head of AI / ML
  • VP of Engineering (AI)
  • Chief AI Officer
  • AI Research Directors
  • Engineering Directors
The Difference

Why companies choose us
over every other firm

We’ve Built AI Companies

Our founding team has built and shipped AI products in healthcare, enterprise software, and automation. We evaluate AI talent the way technical co-founders do — because we are.

Domain Match, Not Keyword Match

An ML engineer who built fraud detection for fintech isn’t the same as one who built claims automation for insurance. We match the domain context, not just the technology stack.

Career Alignment = Retention

We verify that every candidate genuinely wants this role and it fits their career path. That’s how you avoid the six-month resignation cycle that plagues AI hiring across startups, IT services, and enterprise alike.

Not Recruiters.
Technical Operators.

We don’t screen resumes for keywords. We assess whether someone can actually build great AI systems in your specific context — whether that’s a client delivery engagement, a product build, or an enterprise transformation.

“We put ourselves in the hiring manager’s shoes. Every time.”
Global Reach

AI talent where you need it

Three markets, three buyer profiles. Our multi-market presence enables optimised cost, quality, and timezone strategies tailored to how you hire.

🇺🇸

United States

Senior AI engineers, ML leads, and AI executives for tech startups and enterprises building or scaling AI-native products. For teams that need talent on-site or US-timezone-aligned.

StartupsEnterprise TechAI Leadership
🇮🇳

India

Production-ready AI and ML engineers for IT services firms staffing client engagements. Pre-vetted contract talent that deploys directly — no bench cost, no training ramp.

IT ServicesContract StaffingGenAI / LLM
🇿🇦

South Africa

AI talent for large enterprises in banking, insurance, telecom, and mining — industries modernising at scale where the local AI talent pool is extremely thin.

BankingInsuranceTelecomMining
Ready?

Stop interviewing the
wrong AI candidates.

Tell us what you’re building, staffing, or transforming. We’ll come back with candidates who can actually do it.

Start a Conversation →