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Location
In office (Pune)
Seniority
Staff · 7+ years exp

First seen by Alion on Nov 2, 2026.

Overview
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NeuraMach AI Studio is an Indian start-up that builds artificial intelligence and machine learning products. It is hiring an equity-based technical lead for AI and ML engineering to own execution and strengthen its platform. The company is headquartered in Pune, Maharashtra, India.

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

- The central challenge is to turn learner activity, assessment performance, content and behavioural signals into reliable AI-driven guidance, tutoring and recommendations at scale.

5. 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.

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

- You will own implementation and operational decisions while partnering with the CTO on company-wide architecture, security and long-term technology strategy.

- You will have the authority to challenge decisions that introduce avoidable risk, delay, cost or complexity.

Technology Foundation:

1. Current Core Stack:

- React and TypeScript

- Node.js

- Python and FastAPI

- PostgreSQL

- Redis

- Qdrant

- REST and real-time service patterns

- AWS Cognito, S3 and SQS

- Docker and GitHub Actions

- LLM and model-provider integrations

2. Systems Being Strengthened:

- Multi-model AI orchestration

- RAG and hybrid retrieval

- AI evaluation and behavioural telemetry

- Automated testing

- OpenTelemetry-based observability

- Infrastructure and model-cost visibility

- Security, access controls and graceful recovery

- Technologies such as Elasticsearch, Kafka, ClickHouse, Spark, Kong and Kubernetes/EKS may be introduced or expanded only when real scale and operational requirements justify them.

- We need someone who knows when complexity is necessaryand when it should be removed.

What Success Looks Like:

- Within the first 12 months, success should include:

1. A clear architecture and service-ownership model

2. A prioritised technical-debt and risk register

3. Reliable ownership of critical systems

4. A predictable release process

5. Automated testing for critical workflows

6. Defined incident-response and recovery standards

7. AI quality, latency and cost benchmarks

8. Improved production observability

9. Stronger security and cost controls

10. Reusable foundations for future expansion

11. Reduced dependency on individual engineers

12. A stronger and more accountable engineering team

- The objective is not simply to ship more features.

- It is to build an engineering system that can ship faster without becoming fragile.

You Could Be the Right Person If:

- You have owned production systems in a zero-to-one or scale-up environment

- You have led engineers while remaining technically hands-on

- You can review architecture and critical implementations in depth

- You understand modern frontend, backend, data and cloud systems

- You have strong experience with Node.js, Python or comparable technologies

- You understand LLM applications, RAG, vector databases, AI agents or model orchestration

- You can design for reliability, security, maintainability and cost efficiency

- You understand CI/CD, observability, cloud infrastructure and incident management

- You can simplify over-engineered systems

- You make technology decisions based on product and business value

- You can coordinate teams, contractors and external partners

- You are comfortable operating with ambiguity and limited resources

- Experience in EdTech is valuable but not mandatory.

- Strong candidates may come from AI, SaaS, consumer technology, assessment platforms, data products or enterprise software.

- This opportunity may be especially relevant for former technical founders, senior startup engineers, consulting technology leaders or experienced builders looking for a genuine company-building role.

Why Join NeuraMach Now?:

- Work on a live product with real engineering challenges

- Partner directly with the CTO and founders

- Influence how the platform and engineering organisation evolve

- Solve practical AI problems involving personalisation, retrieval, orchestration and adaptive learning

- Participate in the value you create through a meaningful ESOP package

Compensation: Please Read Before Applying:

- This is an ESOP-led founding leadership role with no fixed monthly salary during the current stage.

- Salary commencement will be tied to a clearly defined qualifying fundraise or agreed profitability milestone. The trigger, timing and post-trigger compensation framework will be documented in the final appointment terms before joining.

- Shortlisted candidates will receive transparent visibility into:

1. Indicative ESOP structure

2. Vesting terms

3. Role and commitment expectations

4. Salary-trigger conditions

5. Any milestone-linked grants or incentives

- There is no guaranteed timeline for fundraising, profitability or salary commencement.

- Approved company-related technical tools, cloud resources, business travel and operating expenses will be covered by NeuraMach. Equipment and relocation support, where applicable, will be discussed with shortlisted candidates.

This Role Is Not for You If:

- You require an immediate fixed salary

- You want a leadership title without hands-on responsibility

- You only want to manage an established team

- You avoid production ownership

- You add technology before understanding the problem

- You require perfect requirements before beginning

- You are uncomfortable working closely with a CTO

- You want a predictable corporate role with limited ambiguity

How to Apply:

- Share the following at :

1. Your rsum or LinkedIn profile

2. A product or platform you helped build from zero

3. The most difficult architecture or production problem you solved

4. An AI, SaaS, cloud or data system you took to production

5. An engineering team or delivery process you improved

6. What you would prioritise during your first 90 days

7. Why an ESOP-led founding role makes sense for you

8. Your availability to work on-site from Pune

- Generic applications will not tell us enough.

- Show us what you have built, how you lead engineering execution and why you should help drive NeuraMachs next phase of technology.

- Build the platform. Lead the execution. Help build the company.

- Join NeuraMach AI as our Founding Engineering Lead AI & Platform.

Skills

Machine Learning, Python, Artificial Intelligence, Technical Architect, IT Product Development, CTO

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