My Tax Men
Website:
mytaxmen.com.au
Company:
https://www.linkedin.com/company/mytaxmen
Seniority: Mid-Senior level
Industries: Accounting
Job details:
Senior Software Engineer – Full Stack, AI/ML & Intelligent Document Processing
Job Type: Part-Time, with potential to transition to Full-Time
Experience Level: Senior, 5+ Years
Work Arrangement: Remote
Reports To: Engineering Manager / CTO
How to Apply
If you are an experienced software engineer with strong full-stack development skills and hands-on experience integrating AI/ML, OCR, or Intelligent Document Processing technologies, we would like to hear from you.
Please send your updated CV/resume to: avleensb@innovexai.ae
Please include:
- Updated CV/Resume
- GitHub, portfolio, or relevant project links, if available
About the Role
We are seeking a highly experienced and innovation-driven Senior Software Engineer to join our growing engineering team.
This is a unique opportunity for an engineer who excels across the full application stack and has practical experience leveraging and integrating Artificial Intelligence (AI), Machine Learning (ML), and Intelligent Document Processing (IDP) into production-ready software.
You will architect and implement end-to-end solutions that make applications smarter, more intuitive, and capable of automatically understanding and processing complex, unstructured business documents such as contracts, invoices, reports, onboarding forms, and operational records.
We are looking for someone who brings strong technical maturity, excellent system-design capabilities, high coding standards, and the ability to seamlessly integrate external or internal AI services into reliable software products.
Key Responsibilities1. Full-Stack Application Development
- Design, develop, test, deploy, and maintain scalable full-stack web applications.
- Take ownership of features from technical design through production deployment.
- Build modern frontend applications using React, TypeScript, HTML, and CSS.
- Develop robust backend services using Python, FastAPI/Django, Node.js, or TypeScript-based frameworks.
- Design efficient database schemas and data models.
- Integrate frontend applications with internal and third-party APIs.
- Build reusable components, services, and libraries.
- Identify and resolve performance, scalability, and reliability issues.
2. Intelligent Document Processing & AI Integration
- Architect and implement production-ready Intelligent Document Processing (IDP) workflows.
- Integrate AI-powered document extraction applications and APIs into production software.
- Work with technologies such as:
- AWS Textract
- Google Cloud Document AI
- Microsoft Azure AI Document Intelligence / Form Recognizer
- OCR technologies
- LLM APIs
- LangChain or similar AI orchestration frameworks
- Open-source document intelligence models
- Build workflows covering:
- Document ingestion
- OCR
- Document classification
- Layout analysis
- Entity extraction
- Data validation
- Data normalization
- Human-in-the-loop verification
- Downstream system integration
- Improve document extraction accuracy, processing speed, reliability, and cost efficiency.
- Handle low-confidence AI predictions and extraction failures effectively.
3. Backend Architecture & API Development
- Design scalable backend architectures using microservices or well-structured monolithic systems.
- Develop secure, high-performance RESTful and/or gRPC APIs.
- Build backend orchestration services for document uploads, AI processing, validation, and data persistence.
- Integrate third-party APIs and AI services.
- Implement authentication, authorization, encryption, input validation, and security controls.
- Develop asynchronous processing and queue-based workflows where appropriate.
- Implement robust error handling, logging, monitoring, and retry mechanisms.
- Document APIs and technical interfaces.
4. Frontend Engineering
- Build modern, responsive, and intuitive interfaces using React and TypeScript.
- Create seamless document upload and submission experiences.
- Develop interfaces allowing users to review, validate, correct, and approve extracted information.
- Build dashboards and document-processing workflow interfaces.
- Implement state management using Redux, Zustand, or equivalent technologies.
- Optimize frontend performance, accessibility, responsiveness, and usability.
5. Data Processing & Engineering
- Work extensively with Python and its data-processing ecosystem.
- Use Pandas and NumPy for data manipulation, transformation, validation, and analysis.
- Develop data pipelines supporting document processing and AI workflows.
- Develop data-cleaning and normalization processes.
- Work with structured and unstructured data.
- Optimize data-processing workflows for performance and scalability.
6. Database & Storage Engineering
Work with both relational and NoSQL databases, including technologies such as:
- PostgreSQL
- MySQL
- MongoDB
- Redis
- Vector databases
Responsibilities include:
- Database schema design
- Query optimization
- Indexing
- Data migrations
- Transaction management
- Caching
- Data integrity
- Document and metadata storage
7. AI/ML Engineering
- Apply practical AI/ML concepts to production software systems.
- Understand training, fine-tuning, evaluation, and inference workflows.
- Work with document classification, entity extraction, NLP, OCR, and LLM-based systems.
- Prepare and clean datasets used for AI/ML systems.
- Evaluate AI model outputs and establish quality and accuracy metrics.
- Implement prompt engineering and structured-output strategies.
- Evaluate emerging AI models and technologies.
- Improve AI-powered product capabilities through experimentation and iteration.
8. Cloud, DevOps & Deployment
- Deploy and maintain applications using AWS, Google Cloud, or Microsoft Azure.
- Containerize applications using Docker.
- Work with Kubernetes or other container orchestration technologies where required.
- Develop and maintain CI/CD pipelines.
- Implement application monitoring, logging, alerting, and performance tracking.
- Troubleshoot production and infrastructure issues.
- Follow cloud security, scalability, availability, and cost-optimization best practices.
9. Technical Leadership & Architecture
- Contribute to system architecture and technical direction.
- Make pragmatic technology and architecture decisions.
- Design scalable and maintainable distributed systems.
- Identify technical risks and recommend solutions.
- Establish coding standards and engineering best practices.
- Conduct code reviews and provide technical feedback.
- Mentor other engineers where appropriate.
- Promote automated testing, documentation, maintainability, and clean architecture.
Required Skills & QualificationsProfessional Experience
- Minimum 5+ years of professional software engineering experience.
- Proven experience building and deploying production-grade web applications.
- Strong full-stack development experience.
- Experience owning software features from development through deployment and maintenance.
Frontend
Strong proficiency with:
- React.js
- TypeScript
- JavaScript
- HTML5
- CSS3
- Responsive web development
- Component-based architecture
- Redux, Zustand, or equivalent state-management solutions
Backend
Strong experience with one or more of:
- Python
- FastAPI
- Django
- Node.js
- TypeScript
- NestJS
- REST APIs
- gRPC
Python & Data Processing
- Strong Python programming skills.
- Practical experience with Pandas and NumPy.
- Experience processing, transforming, validating, and analyzing data.
- Ability to build reliable data-processing pipelines.
AI/ML & Intelligent Document Processing
Hands-on experience with:
- Intelligent Document Processing
- OCR
- Document classification
- Layout analysis
- Entity extraction
- Structured data extraction
- AI-powered document processing APIs
- LLM integrations
- AI/ML inference workflows
Candidates should have practical production experience, rather than only theoretical knowledge of AI/ML.
Databases
Strong understanding of:
- SQL databases
- NoSQL databases
- Database architecture
- Schema design
- Query optimization
- Indexing
- Data migrations
- Caching
Software Engineering Fundamentals
Strong knowledge of:
- Object-oriented programming
- Data structures and algorithms
- Web architecture
- Distributed systems
- RESTful API design
- Authentication and authorization
- Application security
- Performance optimization
- Automated testing
- Git and version control
- Clean code and software design principles
Cloud & DevOps
Experience with at least one major cloud platform:
- AWS
- Google Cloud Platform
- Microsoft Azure
Plus practical experience with:
- Docker
- CI/CD
- Cloud deployments
- Application monitoring
- Logging
- Infrastructure troubleshooting
Preferred Qualifications
- Experience deploying or managing Large Language Models (LLMs).
- Experience fine-tuning or evaluating LLMs or open-source AI models.
- Experience with open-source IDP/document intelligence models.
- Experience with vector databases.
- Knowledge of semantic search and embeddings.
- Experience with Retrieval-Augmented Generation (RAG).
- Experience with LangChain or similar AI orchestration frameworks.
- Experience building AI agents or agentic workflows.
- Experience implementing human-in-the-loop AI systems.
- Experience working with multimodal AI models.
- Experience in a startup or rapid-growth technology environment.
- Open-source contributions.
- Experience designing high-volume document-processing systems.
- Experience working with sensitive business documents and implementing appropriate security controls.
Example Technical Workflow
You may work on systems following a workflow such as:
Document Upload → AI Processing → Extraction → Validation → Structured Data → Business System
A typical workflow could involve:
- User uploads a business document.
- Backend securely stores the document.
- OCR/AI service processes the document.
- System identifies the document type.
- Relevant fields and entities are extracted.
- AI confidence scores are evaluated.
- Extracted information is normalized and validated.
- Low-confidence fields are presented to the user for review.
- Approved data is stored in the database.
- APIs transfer processed information to downstream business systems.
WORK FROM HOME REQUIREMENTS- Stable internet connection (Minimum 20 MBPS) with backup connection
- Laptop/PC with updated OS (Core i5 or higher) + Backup device
- Headset with clear microphone
- Noise-free work environment during work hours
- Willingness to use Time Doctor for productivity tracking
- Not currently employed full-time elsewhere
Click on Apply to know more.
