About MAIT:
MAIT is an AI-native intelligence platform for technology procurement and contract management.
Built on years of advisory work across complex IT supplier landscapes, MAIT codifies benchmarking, contract intelligence, and negotiation expertise into a scalable platform.
The platform is currently in structured Beta, with early proof-of-value demonstrated across large enterprise IT spend portfolios. We are now focused on operationalising and scaling this foundation through a small number of focused Client Design Partnerships.
Founder based in Amsterdam; core product and engineering team being built in Gurgaon.
The Mission:
Build the engineering foundations that transform a strong Beta product into a secure, reliable, and repeatable enterprise-grade platform.
Lead the first AI & Platform pod in Gurgaon and establish the delivery discipline, architectural standards, and security culture required to scale MAIT into broader enterprise deployments.
This is a hands-on leadership role with significant ownership and room to grow as the engineering function expands.
What You'll Own:
You will own engineering discipline & architectural integrity that makes MAIT dependable.
1) Delivery & Execution:
- Lead a pod of 26 engineers (growing over time).
- Translate roadmap into well-scoped, measurable increments.
- Establish clear sprint ownership and weekly shipment rhythm.
- Improve predictability: planned vs shipped.
2) Reliability & Quality:
- Strengthen CI/CD, testing strategy, and release hygiene.
- Raise code review standards and definition of done.
- Reduce regressions through disciplined quality gates.
- Improve observability (logs, metrics, traces, alerting, incident response).
- Implement feature flags, controlled rollouts, and rollback readiness.
3) AI Engineering Discipline:
- Build structured, repeatable AI workflows (schemas, validation, fallbacks).
- Establish evaluation harnesses (golden sets + regression checks).
- Version prompts/models/pipelines with transparency on changes.
- Define clear boundaries between deterministic and probabilistic logic.
4) Architecture & Security Foundations:
- Design scalable system architecture for document-heavy, AI-assisted workflows.
- Own secure-by-design principles across data handling, access control, and enterprise-grade safeguards.
- Ensure auditability and traceability (outputs linked to evidence and source).
- Enforce architectural discipline as the system evolves.
What Success Looks Like:
First 30 Days:
- Establish delivery cadence and ownership clarity.
- Tighten code review discipline and definition of done.
- Improve release hygiene and operational visibility.
First 60 Days:
- Predictable weekly releases.
- Reduced regressions through stronger testing coverage.
- Initial AI evaluation harness in place for critical workflows.
First 90 Days:
- Higher-confidence releases with fewer incidents.
- More structured, traceable AI-assisted workflows.
- Strengthened foundations for enterprise-scale deployment.
Must-Have Profile:
- 712 years building and operating production software.
- Hands-on engineer: active in code and code reviews.
- Led a small engineering pod with delivery accountability.
- Experience designing scalable system architecture.
- Strong engineering discipline: CI/CD, testing strategy, release practices, observability.
- Solid understanding of secure software design principles (auth, access control, data protection).
- Experience shipping SaaS products in real customer environments.
- Comfortable in early-stage / scale-up environments: evolving scope, high ownership, ambiguity.
Strong Advantages:
- AI product engineering experience (LLMs, RAG, eval harnesses).
- Experience with document-heavy systems (extraction, search, provenance).
- Enterprise SaaS exposure (RBAC, audit logs, SSO, multi-tenancy).
- Startup or early-stage scale experience.
The Leadership Traits We Value:
- Product-minded and systems-thinking.
- Comfortable saying no when discipline demands it.
- Able to push back constructively including with founders.
- Focused on long-term architecture, not just short-term velocity.
- Motivated by building foundations that scale.
Growth Opportunity:
This role begins as Engineering Manager - AI & Platform, leading the first core pod in Gurgaon.
As MAIT scales beyond Beta and expands its engineering function, there is clear scope to grow into broader engineering leadership responsibilities.
We are looking for someone who wants to build the foundation, and grow with it.
Compensation:
35L - 50L CTC
Meaningful ESOP allocation aligned to long-term scale goals.
Why Join Now
- Early-stage ownership with real architectural influence.
- Enterprise-grade AI challenges (not experimental prototypes).
- Direct access to founder and product strategy.
- Opportunity to shape engineering culture from day one.
