Engineer – AI Lab

About the Role: As an Engineer, you will support the successful execution of AI and GenAI initiatives by bridging technical understanding with execution management. While you are expected to be hands-on in coding and working with AI tools, this role also requires you to evaluate technical solutions, coordinate delivery with tech teams or vendors, and keep AI projects on track. You will work in a hybrid capacity balancing a technical mindset with structured project execution. Key Responsibilities: Support development and implementation of AI/GenAI use cases in partnership with internal and external teams. Conduct market research to stay up to date with AI/GenAI trends and tools, and bring insights back to the team for experimentation and innovation Drive UATs, test AI tools, evaluate feasibility of solutions, and contribute to prototyping. Work on code-based tasks such as prompt engineering, basic model integration, or automation workflows. Track project plans, manage dependencies, follow up on timelines, and support project execution end-to-end. Coordinate with business users, engineering teams, and external solution partners to align on requirements and deliverables. Document learnings, test results, configurations, and maintain clear communication across the team. Contribute to AI experimentation and innovation activities by staying current with emerging tools. Who are we looking for? Education: Bachelor s or Master s in Computer Science, Engineering, Data Science, or a related technical field. Experience: 3 6 years of experience in AI/ML, GenAI, or tech-enabled business roles. Experience contributing to tech delivery while coordinating with cross-functional teams. Exposure to AI platforms, APIs, or cloud-based tools is a must. Skills: Working knowledge of Python and GenAI libraries/APIs (e.g., OpenAI, LangChain, Hugging Face). Familiarity with AI concepts like prompt engineering, embeddings, LLMs, and vector DBs. Basic hands-on experience in writing or reviewing code for AI workflows. Strong planning, coordination, and execution ownership across technical and business teams. Attention to detail, documentation, and a disciplined approach to follow-through. Ability to learn fast, ask the right questions, and manage ambiguity