•Design, develop, test, and deploy Generative AI solutions that meet business requirements while ensuring quality, scalability, performance, and reliability.
•Build and maintain AI applications using Large Language Models (LLMs), prompt engineering techniques, 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 effective technical solutions.
•Contribute to the team's 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 participate in iterative development cycles to enhance user experience, adoption, and business value.
•Work effectively within geographically distributed teams, communicating technical concepts clearly to both 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.
We Expect You to Have
•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 to work independently while collaborating effectively within multi-functional teams.
