aCommerce - Technical Specialist - AI Engineering

• Build and integrate AI features into internal tools, microservices, and automation workflows. • Develop LLM‑powered assistants, RAG systems, and knowledge tools using models like Claude, GPT, and Gemini. • Create APIs, pipelines, and services that make AI reliable, scalable, and safe. • Improve developer productivity through AI‑augmented coding, testing, and documentation tools. • Contribute to the company’s AI roadmap and help identify high‑impact AI opportunities. • Evaluate new AI tools, models, and platforms — and recommend what we should adopt. • Help define best practices for prompt engineering, model usage, and safe deployment. • Support teams in adopting AI responsibly, including training, documentation, and internal guidelines. • Work with architects to ensure AI systems follow governance, auditability, and data‑handling standards. • Partner with product, engineering, and operations teams to translate business needs into AI solutions. • Lead design discussions for new AI‑powered features and internal platforms. • Help build a culture of experimentation and continuous improvement around AI. • Capabilities • At least 5 years of software engineering experience. • Proven experience working on agentic applications with the ability to articulate the tradeoffs between different approaches • Strong skills in Python, Node.js/TypeScript, or Go. Good awareness of SQL • Hands-on experience with LLM APIs and context engineering. • Familiarity leveraging vector databases, RAG pipelines and memory systems • Experience building APIs, microservices, or event‑driven systems. • Experience with enterprise SDLC tooling including version control, CI/CD systems, testing methodologies as they pertain to generative and agentic applications. • Interest in AI strategy, evaluation, and responsible AI practices. • Curiosity, problem‑solving mindset, and willingness to explore new tools. • Experience with delivering applications to Kubernetes runtime environments a plus • Experience using workflow engines, automation, or internal developer platforms.