Generative AI Developer

Role & responsibilities

• Lead the implementation of AI strategies and roadmaps across software development projects, ensuring seamless integration into the software development lifecycle (SDLC).
• Design, develop, and deploy AI/ML and Generative AI solutions that address business and technical challenges.
• Drive AI adoption by identifying opportunities to integrate AI tools and methodologies into engineering practices.
• Train, mentor, and enable development and QA teams to effectively leverage AI-powered coding assistants, testing frameworks, and automation tools.
• Serve as a trusted AI subject matter expert during client engagements by identifying business challenges and recommending innovative, high-impact AI use cases.
• Design, execute, and evaluate Proof of Concepts (PoCs) to validate emerging AI technologies, technical feasibility, and business value.
• Showcase successful AI implementations, PoC outcomes, and best practices to internal stakeholders, leadership teams, and clients.
• Collaborate with cross-functional teams to embed AI capabilities into products and solutions while promoting engineering excellence and innovation.
• Stay current with advancements in Artificial Intelligence, Generative AI, and MLOps to recommend and implement best practices.

Preferred candidate profile

• 3-5 years of experience in software development with hands-on experience implementing AI/ML or Generative AI solutions in production environments.
• Strong understanding of AI technologies across the Software Development Lifecycle (SDLC), including AI coding assistants, AI-driven testing frameworks, and automation tools.
• Experience with MLOps concepts, AI model deployment, monitoring, and lifecycle management.
• Proficiency in one or more programming languages such as Python, Java, or .NET.
• Strong knowledge of Generative AI, Large Language Models (LLMs), prompt engineering, and modern AI frameworks and tools.
• Demonstrated ability to design and deliver AI Proof of Concepts that showcase technical feasibility and business impact.
• Excellent communication and consulting skills with the ability to translate complex AI concepts into clear business value and ROI.
• Experience working directly with clients and stakeholders to gather requirements, present AI solutions, and influence decision-making.
• Strong analytical, problem-solving, collaboration, and stakeholder management skills.
• Passion for continuous learning and driving AI innovation across engineering teams.