Artificial Intelligence Specialist

Job Description

Technical Project Lead AI Development

Company: Secninjaz Technologies LLP

Employment Type: Full-Time

Experience Required: Minimum 8+ Years (3+ Years in Leadership Role)

Location: India

About Secninjaz Technologies LLP

Secninjaz Technologies LLP is an ISO 27001-certified cybersecurity company delivering advanced security solutions across fintech, healthcare, government, corporate, and intelligence sectors. Our services include VAPT, SIEM, Zero Trust Architecture, Cloud Security, Fintech Security, Secure Communication Systems, and Enterprise Cyber Defense. As part of our expansion into AI-driven cybersecurity solutions, we are establishing a dedicated AI division to build next-generation intelligent security systems.

Position Summary

The Technical Project Lead AI Development will lead and manage the entire AI division while ensuring successful execution of AI initiatives. This role requires strong technical expertise, strategic thinking, project management excellence, and proven leadership capability. The selected candidate will be responsible for complete ownership of AI strategy, team management, model development, training, deployment, governance, and delivery execution. The candidate must have successfully executed at least five (5) AI/ML projects end-to-end in production environments.

Mandatory Experience Requirements

• Minimum 8+ years of total experience in Artificial Intelligence / Machine Learning
• Minimum 3+ years in a leadership or project management role
• Successfully executed at least 5 AI/ML projects from concept to production
• Experience managing cross-functional AI teams
• Proven experience delivering enterprise-grade AI systems
• Strong background in model training, deployment, and monitoring

Key Responsibilities:

AI Team Leadership & Management

• Lead, manage, and scale the entire AI/ML department
• Hire, train, and mentor AI engineers, data scientists, and ML engineers
• Define technical standards, development processes, and KPIs
• Conduct architecture reviews and performance evaluations
• Build internal AI training and capability development programs
• Ensure timely delivery of all AI initiatives

End-to-End AI Project Execution

• Requirement gathering and business analysis
• Data strategy and collection
• Model architecture design
• Model training and hyperparameter tuning
• Validation and testing
• Production deployment
• Monitoring and optimization

AI Model Development & Training

• Design and develop Deep Learning models (CNN, RNN, Transformers)
• Develop NLP and Large Language Models (LLMs)
• Build Generative AI applications
• Create predictive analytics systems
• Develop anomaly and threat detection systems
• Handle large-scale datasets and distributed training
• Optimize model accuracy, scalability, and efficiency
• Implement retraining pipelines and performance improvement cycles

MLOps & Production Deployment

• Design and manage CI/CD pipelines for ML systems
• Deploy models using Docker and Kubernetes
• Implement model versioning and lifecycle management
• Monitor model drift and implement automated retraining
• Ensure high availability, scalability, and performance

AI Security & Compliance

• Implement secure AI architecture aligned with Zero Trust principles
• Protect AI systems against adversarial attacks
• Ensure compliance with ISO 27001 and data protection standards
• Integrate AI systems with SIEM, SOC, and cybersecurity platforms

Required Technical Skills

• Strong expertise in Python
• TensorFlow / PyTorch
• Scikit-learn
• NLP, LLMs, Generative AI
• MLOps tools (MLflow, Kubeflow, Airflow)
• Docker & Kubernetes
• Cloud platforms (AWS, Azure, GCP)
• Experience with large-scale data processing

Leadership Competencies

• Strategic AI roadmap planning
• Strong team-building and mentoring capability
• Decision-making and execution excellence
• Strong problem-solving skills
• Excellent communication and stakeholder management

Accountability & Performance Expectations

• Complete ownership of the AI department
• Delivery of AI projects within timelines
• Model performance, accuracy, and reliability
• Production stability and monitoring
• AI innovation aligned with Secninjaz business objectives