Senior Tech Lead AI Platform Engineering

About NeuraMach.AI

NeuraMach.AI is an AI-native engineering company building production-grade AI platforms, agentic systems, RAG solutions, machine-learning applications and intelligent digital products.

Role Overview

We are looking for a Senior Tech Lead – AI/ML and Platform Architecture to own the technical direction and delivery of complex AI-enabled platforms. This is a hands-on leadership role combining platform architecture, AI/ML engineering, cloud systems, integrations and team management.

Key Responsibilities

Design scalable, multi-tenant and multi-region application architectures.

Define service boundaries, APIs, data flows and integration standards.

Lead the implementation of AI agents, RAG, tool calling and pre-trained language-model integrations.

Guide the development, training, testing and deployment of machine-learning models.

Design model-serving, versioning, monitoring and rollback workflows.

Lead cloud deployment, containerisation, CI/CD, observability and reliability practices.

Review critical code, database designs, infrastructure changes and technical decisions.

Lead backend, AI/ML, frontend, mobile, DevOps and QA engineers.

Translate business requirements into practical architecture and delivery plans.

Support client-facing technical discussions, demonstrations and production releases.

Required Skills

5+ years of relevant software, platform or AI/ML engineering experience.

Strong hands-on Python and backend-development experience.

Experience designing distributed systems, APIs and event-driven architectures.

Strong PostgreSQL and data-modelling knowledge.

Experience with Docker, cloud platforms and production deployment.

Practical experience with machine learning and model inference.

Experience with RAG, vector databases, LLM APIs and agentic workflows.

Understanding of multi-tenant application security and role-based access.

Proven experience leading engineers, reviewing code and owning releases.

Strong stakeholder-management and communication skills.

Good to Have

PyTorch, scikit-learn, LightGBM, ONNX or time-series modelling experience.

LangChain, LlamaIndex, MCP or structured tool-integration experience.

Kubernetes, infrastructure as code and production observability.

Edge AI, IoT, telemetry or offline-first system experience.

React, React Native or Flutter architecture awareness.

Experience with enterprise workflow, asset-management or industrial software.

How to Apply

Interested candidates are requested to share their updated resume at:

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Please mention the following details in your email:

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Candidates may also include links to their GitHub, portfolio, LinkedIn profile, or relevant projects.

Subject Line: Application – [Role Name] – [Your Name]