AI Engineer-2

Job Description

To lead the architecture, development, deployment, programming and training of complex AI models, AI agents and AI systems. This advanced role involves overseeing all aspects related to AI, with a focus on the deployment of agentic systems. The role includes traditional machine learning and data processing tasks, as well as designing, fine-tuning, and deploying advanced large language models, conversational agents, and agentic systems. The senior engineer also mentors junior team members, contributes to architectural decisions, and drives innovation in AI practices. The ideal candidate combines strong technical leadership with deep expertise in Large Language Models (LLM) applications, tooling, and Machine Learning Operations (MLOps) best practices. Are you someone who can

• Assist in training, testing, and fine-tuning ML and LLM models as part of larger projects • Help collect, clean, and preprocess datasets for use in AI pipelines • Work on small components of AI systems such as prompt crafting, inference scripts, or evaluation tasks • Perform exploratory data analysis and create visualizations to support modeling efforts • Collaborate with senior engineers to understand system requirements and deployment workflows • Write clear, well-documented code and participate in code reviews • Conduct basic research into AI tools and libraries and summarize findings for the team • Participate in team meetings and contribute to a learning-focused, inclusive development culture • Lead architecting, development, deployment, programming and training of complex AI models, AI agents and AI systems. • Oversee the building of robust, scalable data pipelines for training, validating, and deploying AI models. • Optimise model performance, manage complex issues such as bias and hallucinations, and refine prompt strategies and evaluation techniques. • Integrate AI solutions into production environments with a focus on scalability, observability, reliability, and security. • Collaborate closely with product, engineering, and infrastructure teams to ensure successful deployment of AI-powered features. • Mentor junior engineers and contribute to team knowledge-sharing and AI best practices. • Stay current with advancements in AI research, tooling, and agentic system orchestration to drive continuous innovation. • Control expenditure and identify process improvements to contain and reduce costs. • Creates solutions to meet customer demands. • Establish mutually beneficial relationships with stakeholders that support thought leadership, innovative and integrated practice solutions. • Participate in planned activities that are appropriate for own development. • Provide guidance, share knowledge and expertise and guide employees to find their own solutions. • Manages risks in own area of responsibility. • Provide subject matter expertise and thought leadership in area of expertise.

You will be an ideal candidate if you

• Have a Bachelor of Science degree in a relevant field • Have 1 to 2 years of experience in AI • Are proficient in Python and familiar with frameworks like TensorFlow or PyTorch

You will have access to

• Opportunities to network and collaborate • Challenging work that pushes boundaries • A culture of innovation and continuous learning

We can be a match if you are

• Curious & courageous – driven by a desire to learn and explore • Obsessed with mastery – always striving to improve and excel • Passionate about ethical AI and responsible innovation

Key Responsibilities

• Design, develop, and maintain full stack applications that integrate with AI agents built in Copilot Studio. • Build and optimize conversational flows, triggers, and actions using Copilot Studio and Power Automate. • Integrate AI agents with external APIs, databases, and enterprise systems. • Collaborate with cross-functional teams to deliver intelligent, user-centric solutions. • Stay current with AI trends and rapidly evolving platforms, continuously learning and applying new tools.

Required Skills & Experience

• Proficiency in Python and basic understanding of key libraries (e.g., NumPy, Pandas, scikit-learn) • Familiarity with foundational machine learning concepts such as classification, regression, and clustering • Basic understanding of deep learning and neural networks, especially transformer models • Exposure to machine learning frameworks such as PyTorch or TensorFlow (projects or coursework acceptable) • Interest in LLMs, conversational AI, or agentic systems (some hands-on experience preferred) • Familiarity with version control tools (e.g., Git) and basic softw