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We are looking for a GenAI Engineer who approaches challenges with a problem-first mindset—focusing on the business need before selecting technical solutions. This role requires someone who can leverage state-of-the-art generative AI models, frameworks, and tools to design, build, and deploy impactful AI applications. You will collaborate with product managers, domain experts, and data engineers to rapidly prototype, validate, and scale GenAI solutions that solve real-world problems across industries.
Job Responsibility:
Problem Framing & Solutioning: Understand business challenges and translate them into well-scoped GenAI opportunities
GenAI Development: Build and fine-tune applications using LLMs, multimodal models, and retrieval-augmented generation (RAG)
Tooling & Systems Integration: Use orchestration tools to combine multiple agents or models into end-to-end workflows
Collaboration & Deployment: Work closely with product managers, UX, and engineering teams to build user-centric solutions
Requirements:
Strong foundation in Python and modern ML/AI frameworks (PyTorch, TensorFlow, Hugging Face)
Hands-on experience with LLMs, RAG pipelines, prompt engineering, and fine-tuning
Familiarity with LangChain, LangGraph, or similar orchestration frameworks
Experience integrating APIs, databases, and cloud platforms (Azure, AWS, GCP)
Ability to frame problems, run quick experiments, and iterate toward solutions
Strong communication skills to explain complex AI solutions to technical and non-technical audiences
Nice to have:
Experience with agentic AI systems (multi-agent orchestration, planning, reasoning)
Knowledge of MLOps for GenAI (CI/CD, monitoring, scaling)
Background in telecom, finance, or enterprise systems