Specialist- AI Engineering and Automation

Overview

Design, build and deploy Generative AI solutions, working across Finance, Technology and business teams to turn requirements into AI-powered applications.

What you'll do

• Design, develop, test and deploy Generative AI solutions that meet business requirements, ensuring quality, scalability, performance and reliability.
• Build and maintain AI applications using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), agent-based workflows and cloud-native architectures.
• Collaborate with Finance, Technology and business stakeholders to understand requirements and translate them into technical solutions.
• Contribute to adoption of software engineering and AI development guidelines, including coding standards, testing, documentation and responsible AI principles.
• Develop reusable components, APIs and automation frameworks that accelerate AI solution delivery across the organization.
• Participate in solution design discussions, code reviews and architecture reviews to ensure maintainability and scalability.
• Gather user feedback and take part in iterative development cycles to enhance user experience, adoption and business value.
• Work effectively within geographically distributed teams, communicating technical concepts clearly to technical and non-technical audiences.
• Fix and resolve development and deployment issues, calling out risks and dependencies where appropriate.
• Contribute to the evaluation and adoption of emerging AI technologies, frameworks and industry guidelines.

What you'll need

• 4-6 years of software development experience, with hands-on experience building and delivering production-grade applications.
• Strong proficiency in Python and its ecosystem, including modern development practices and frameworks.
• Experience developing applications using Generative AI technologies, including LLMs, prompt engineering, vector databases, RAG architectures or AI agents.
• Proficiency with AWS cloud services and cloud-native application development.
• Experience with modern development environments and tools such as Visual Studio Code, Git, CI/CD pipelines and automated testing frameworks.
• Strong understanding of software engineering principles, system design and API development.
• Familiarity with AI governance, model evaluation, security and responsible AI practices.
• Excellent communication and stakeholder leadership skills, with the ability to explain complex technical concepts clearly and concisely.
• Proven track record of working independently while collaborating effectively within multi-functional teams.

Nice to have

• Experience building AI solutions in finance, tax, risk, compliance or other regulated environments.
• Familiarity with agentic AI frameworks, MCP-based integrations, orchestration platforms or workflow automation technologies.
• Knowledge of web scraping, data extraction and document processing techniques.
• Familiarity with Spec-Driven Development methodologies and modern software delivery practices.
• Exposure to machine learning model deployment, MLOps or AI observability tools.