Quick Answer
Shoppeal Tech's analysis of 15 AI product builds shows that a dedicated offshore AI team of 3 engineers (1 senior AI engineer, 1 mid-level, 1 AI QA) costs $12,000–$18,000/month fully loaded compared to $45,000–$65,000/month for an equivalent in-house team in the US or ₹30–50 LPA total cost per engineer in India when recruitment, benefits, and infrastructure are included. The offshore team is operationally ready in 2–3 weeks vs 3–5 months to hire in-house.
$12–18K/mo
Offshore Team Cost
$45–65K/mo
In-House Equivalent
60–70%
Cost Saving
2–3 weeks
Time to Ops
Full Cost of an In-House AI Team (All Hidden Costs Included)
Most comparisons only count salary. The real cost includes:
Base salary: Senior AI Engineer $160-200K, Mid-level $110-140K, AI QA $80-100K. Total: $350-440K/year.
Employer taxes and benefits: 25-35% on top of salary. Add $87-154K/year.
Recruitment: AI engineering roles take 3-5 months and cost 20-25% of first-year salary in recruiter fees. One-time $70-110K.
Infrastructure and tooling: GPU credits, model API costs, monitoring tools, vector DB hosting $2,000-5,000/month.
Management overhead: Engineering manager time, HR, onboarding estimated 15-20% of team cost.
Total year-1 cost for a 3-person AI team: $600,000-$850,000.
Full Cost of a Dedicated Offshore AI Team
Team composition: 1 Senior AI Engineer, 1 Mid AI Engineer, 1 AI QA/MLOps specialist.
Monthly engagement cost (Shoppeal Tech model): $12,000-$18,000/month, fully loaded. Includes salaries, benefits, management, infrastructure, and collaboration tools.
What's included: Daily standups, weekly delivery reviews, access to Shoppeal Tech's AI infrastructure stack (vector DB, model monitoring, eval framework), compliance expertise.
What's not included: Your LLM API costs (OpenAI, Anthropic, etc.) and your production infrastructure (AWS/GCP/Azure).
Annual cost: $144,000-$216,000 vs $600,000-$850,000 in-house. Saving: $384,000-$634,000/year.
When to Choose Each Option
Choose offshore dedicated team when: You need to ship an AI product in < 6 months. You don't yet know your AI architecture long-term. Your AI product is not yet generating revenue to justify in-house hiring. You need compliance expertise (DPDP, SOC2) built into the team.
Choose in-house when: AI is your core product differentiator and IP must stay 100% in-house. You have a working AI product with $5M+ revenue that justifies the hiring investment. You need to iterate extremely rapidly with full architectural control.
Hybrid approach (recommended for scale-ups): Use offshore team to build v1. Once the architecture is proven and the product generates revenue, hire 1-2 in-house engineers to own the architecture keep offshore team for execution and scaling.
| Factor | Dedicated Offshore Team | In-House Team |
|---|---|---|
| Monthly cost (3 engineers) | $12–18K | $45–65K |
| Time to operational | 2–3 weeks | 3–5 months |
| AI compliance expertise | Built-in | Must hire separately |
| Infrastructure included | Yes | No (add $2–5K/mo) |
| Risk if project pauses | Pause engagement | Redundancy costs |
| IP ownership | Full client ownership | Full client ownership |
Frequently Asked Questions
Who owns the IP when using an offshore AI team?
What happens if we want to bring the team in-house later?
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