NeuraMach AI Studio - Technical Lead - AI/ML Engineering - Equity Based

Neuramach.ai; Pune District; On-site; Full time

Job description

Job Description:

Own engineering execution. Strengthen the platform. Turn ambitious technology into reliable products.

Company: NeuraMach AI Studio Pvt. Ltd.

Location: Pune On-site

Reports To: Chief Technology Officer

Experience: Typically 7+ years; exceptional zero-to-one builders will also be considered

Compensation: Meaningful ESOP-led founding package; no fixed salary during the current stage

The Product Is Live. Now We Build for Scale:

At NeuraMach AI, we are building AI-native products and solutions designed to transform how people learn, prepare and work.

Our first major platform, ScoreVedaa, is now live in betabringing together personalised strategy, intelligent learning, adaptive practice, exam simulation and performance intelligence.

The product foundation, content ecosystem, AI capabilities and initial cloud infrastructure are already in place. We are now focused on:

• Strengthening production reliability
• Improving engineering quality and release discipline
• Simplifying and scaling the architecture
• Building reusable AI and platform capabilities
• Expanding into the next wave of competitive-exam markets
• Creating a high-accountability engineering organisation

This is a founding role because the engineering execution function, ownership model and future technical team are still being built.

We need a senior engineering leader who can work directly with our CTO and make the technology deliveron the ground, every day.

Your Mandate:

As our Founding Engineering Lead, you will translate technology direction into strong implementation, predictable delivery and reliable production systems.

You will:

• Review critical architecture and code
• Guide implementation decisions
• Resolve production and delivery risks
• Coordinate engineers and technical contributors
• Establish engineering and release standards
• Improve accountability across the team
• Convert technical plans into working products

This is a hands-on role for someone who wants to build, guide and deliver.

Your First Six Months:

1. Establish the Technical Reality:
   • Review the architecture, codebase, infrastructure, AI workflows, data systems, security controls, technical debt and team ownership.
   • Turn the findings into a prioritised execution roadmap.
   • The goal is not to rewrite everything. It is to identify what must be fixed, what should be simplified and what is strong enough to scale.
2. Stabilise Critical Workflows:
   • Take engineering ownership across high-impact systems such as:
   • 1. Authentication and account access
   • 2. Question delivery and content services
   • 3. Exam creation and simulation
   • 4. Answer submission and session handling
   • 5. Performance analytics
   • 6. AI responses and retrieval
   • 7. Payments and subscriptions
   • 8. Administrative systems
   • 9. Logging, monitoring and incident response
   • Ensure that critical user and commercial journeys are reliable, observable and clearly owned.
3. Build Engineering Discipline:
   • Establish practical standards for:
   • 1. Code and architecture reviews
   • 2. Automated testing
   • 3. CI/CD and release management
   • 4. Technical documentation
   • 5. Security reviews
   • 6. Performance monitoring
   • 7. Incident ownership
   • 8. Technical-debt tracking
   • Speed matters, but production quality cannot depend on individual heroics.
4. Strengthen the AI Platform:
   • Work with the CTO and AI contributors to improve:
   • 1. Multi-model LLM orchestration
   • 2. Agent routing and workflows
   • 3. RAG, hybrid search and reranking
   • 4. Context management
   • 5. Prompt and configuration versioning
   • 6. AI evaluation and benchmarking
   • 7. Safety, fallback and recovery controls
   • 8. Latency and model-cost optimisation
   • 9. AI telemetry and observability
5. The central challenge is to turn learner activity, assessment performance, content and behavioural signals into reliable AI-driven guidance, tutoring and recommendations at scale.
6. Lead Engineering Execution:
   • Initially, you will lead a lean mix of internal and external contributors across product engineering and AI.
   • You will clarify ownership, coordinate releases, review critical implementations, mentor engineers, improve accountability and identify hiring gaps.
   • You are not expected to be the deepest specialist in every technical area. We are looking for strong engineering judgement, technical breadth and the ability to build teams with the right specialist depth.
7. What You Will Own:
   • Delivery and architecture implementation
   • Code and release quality
   • Production readiness and reliability
   • Engineering standards
   • Incident follow-through
   • Technical documentation
   • Team execution and accountability
   • Vendor and contractor coordination
   • Technical hiring and evaluation
8. You will own implementation and operational decisions while partnering with the CTO on company-wide architecture, security and long-term technology strategy.
9. You will have the authority to challenge decisions that introduce avoidable risk, delay, cost or .