Senior Software / AI Engineer at Ralds & Agate

Job Responsibilities

• Define and drive the objective and roadmap for AI software engineering in alignment with business goals.
• Design, implement, and manage software programs with a focus on AI applications and next-generation large language models.
• Lead and scale high-performing engineering teams focused on AI/ML, software development, DevOps, and MLOps.
• Ensure best practices in software engineering, including coding standards, architecture, testing, and documentation.
• Develop and deploy advanced machine learning models, including multimodal AI systems and autonomous AI agents.
• Work with massive sparse expert models and implement longer contextual memory techniques for improved AI performance.
• Implement natural language processing (NLP) advancements for enhanced user experiences.
• Build and optimize AI models for performance, scalability, and efficiency using cloud based resources.
• Implement explainable AI (XAI) practices to ensure transparency and ethical AI development.
• Develop small language models (SLMs) for edge computing and specialized applications
• Create and implement GenAI observability tools and cybersecurity solutions.
• Collaborate with cross-functional teams to integrate AI solutions into existing products
• Stay updated with emerging AI trends including any-to-any multimodal AI, edge AI, and humanoid robotics.
• Participate in data augmentation techniques to improve AI training efficiency Job

Requirements
Education / Business Degree:

• Bachelor’s Degree in Computer Science, Software Engineering, or a related field.

Work Experience:

• 7 - 10 years of relevant working experience in software engineering, AI/ML and 4+ years in senior engineering leadership roles.

Training / Certificates:

• Certified JavaScript Developer.
• Go Lang Developer Certification.
• Microsoft Certified: Azure Solutions Architect Expert.
• AWS Certified Solutions Architect – Associate/Professional.
• Dynamic Programming Algorithms Specialization.
• MongoDB Certified Developer Associate.
• Microsoft Certified: Azure AI Engineer Associate.
• DeepLearning.AI – Large Language Models with Transformers.
• Emotional Intelligence for Leaders.
• People Management Skills.
• Stakeholder Engagement & Management.
• Strategic Communication for Leaders.
• Agile Leadership Training.

Competencies, Skills & Attributes:
Knowledge:

• Knowledge of machine learning algorithms: linear/logistic regression, decision trees, random forests, SVMs, kmeans, etc.
• Knowledge of large language models (LLMs): pretraining, fine-tuning, prompt engineering.
• In-depth understanding of software architecture and system design. • Strong knowledge of RESTful API design and integration.
• Knowledge of DevOps pipelines and container security.
• Understanding of SQL and NoSQL databases: MySQL, MongoDB, Redis.
• Familiarity with ethical principles in AI: fairness, bias, accountability, transparency.
• Knowledge of AI use cases across industries (e.g., NLP chatbots, recommendation engines, fraud detection, computer vision).
• Knowledge of people management and mentoring best practices.

Skills:

• Proficiency in programming languages: Must Have C++ or JavaScript & Rust; Good to have – GoLang.
• Cloud expertise: AWS, Azure, Git and DevOps.
• Strong knowledge of Microservice Architecture, RabbitMQ, and Dynamic Programming.
• Database experience: MySQL, MongoDB, and Redis • Understanding of full-stack development and software engineering concepts.
• Commitment to fostering a culture of collaboration, accountability, and continuous learning.
• Experience with large language model development and fine-tuning.
• Knowledge of multimodal AI systems and autonomous agent development.
• Excellent communication and stakeholder management skills.
• Strategic thinker with the ability to translate business needs into technical solutions.
• Passion for AI ethics, innovation, and building technology that impacts lives.
• Proven ability to lead and mentor high performing engineering teams.
• Strong decision-making and problem-solving capabilities.
• Ability to align technical initiatives with organizational goals
• Experience managing through change and driving transformation
• Commitment to fostering a culture of collaboration, accountability, and continuous learning

Behavioural Attributes:

• Able to connect engineering initiatives to broader business goals.
• Constantly seeks new and better ways to apply AI and software to solve problems.
• Takes full responsibility for the success or failure of initiatives.
• Follows through on commitments and holds self and team to high standards.
• Open to others’ ideas, promotes team input, and fosters collective success.
• Can communicate complex technical concepts in a clear and accessible way.
• Willing to experiment, iterate, and embrace cutting-edge technologies.
• Take full responsibility for the success or failure of initiatives.
• Follows through on commitments and holds self and team to high standards.
• Follows through on commitments and holds self and team to high standards.
• Works effectively with cross-functional teams (Product, Data, Security, Business).
• Provides clear direction, mentorship, and supports team growth.
• Responds constructively to change and leads others through uncertainty.
• Open to others’ ideas, promotes team input, and fosters collective success.