If youre an innovator at heart, passionate about leveraging AI to solve complex problems, and thrive in an environment where experimentation and entrepreneurship are encouragedthis role is for you.
Responsibilities:
Develop and integrate AI-powered solutions to enhance engineering productivity, automate workflows, and improve developer efficiency.
Evaluate and implement state-of-the-art AI platforms (ChatGPT, Claude, Gemini, custom models) to solve engineering and operational challenges.
Design and maintain AI-driven internal platforms such as knowledge management systems, AI-enhanced coding assistants, intelligent automation tools, and AI-powered chatbots.
Work alongside engineering, DevOps, and product teams to embed AI into everyday development workflows.
Lead Proof-of-Concept (PoC) projects, experimenting with LLMs, generative AI, and automation frameworks to create tangible business impact.
Stay ahead of emerging AI trends, researching and implementing cutting-edge AI models and tools.
Build scalable AI infrastructure that integrates with cloud environmen (AWS, GCP, Azure) and engineering toolchains.
Promote a culture of innovation, empowering teams to embrace AI-driven solutions and fostering AI adoption across the organization.
BSc in Computer Science or related degree, or equivalent practical experience.
4+ years of hands-on experience as a software Engineer
Strong proficiency in Python and experience with AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face).
Experience with AI APIs (OpenAI, Anthropic, Google AI, Microsoft AI) and integrating them into engineering workflows
Hands-on experience with developer productivity tools, AI-enhanced automation, and knowledge management systems
Strong problem-solving skills and ability to build AI-powered solutions that engineers love to use.
Nice to Have:
Deep understanding of LLMs, RAG (Retrieval-Augmented Generation), fine-tuning, and prompt engineering.
Experience with data pipelines, embeddings, and vector databases for AI-powered search and automation.
Experience working with cloud-based AI platforms and scalable AI architectures
Knowledge of containerization (Docker, Kubernetes) and CI/CD pipelines for deploying AI applications.
Experience with AI Ops, observability tools, and monitoring AI applications in production.
Familiarity with LangChain, AutoML, MLOps frameworks, and workflow automation tools.
A background in software engineering, DevOps, or developer tooling.
Strong entrepreneurial mindset, able to identify opportunities, move fast, and drive AI adoption in a high-impact environment.
