Principal Backend Engineer - AI Platform

Description

DriveNets is looking for an AI Platform Engineer to revolutionize engineering productivity and drive AI-powered innovation across the organization. This role is part of our Platform Engineering initiative, focused on enabling engineers and product teams with cutting-edge AI tools, intelligent automation, and scalable AI platforms.

If you’re an innovator at heart, passionate about applying AI to solve complex engineering problems, and thrive in an environment that values experimentation, ownership, and entrepreneurship—this role is for you.

Responsibilities

• Develop and integrate AI-powered solutions that enhance engineering productivity, automate workflows, and improve developer efficiency across the organization.
• Evaluate, prototype, and implement state-of-the-art AI platforms using latest models and frameworks (e.g., ChatGPT, Claude, Gemini, LangGraph, Librechat, AWS Agentcore Bedrock) to address engineering and operational challenges.
• Design, build, and maintain AI-driven internal platforms, including knowledge management systems, AI-enhanced coding assistants, intelligent automation tools, and AI-powered chatbots.
• Collaborate closely with engineering, DevOps, and product teams to embed AI capabilities into everyday development workflows.
• Lead Proof-of-Concept (PoC) initiatives, experimenting with LLMs, generative AI, and automation frameworks to deliver tangible business impact.
• Research emerging AI trends, tools, and models, and translate them into practical, production-ready solutions.
• Build and operate scalable AI infrastructure that integrates with cloud environments and existing engineering toolchains.
• Promote a culture of innovation by empowering teams to adopt AI-driven solutions and sharing knowledge and outcomes across the organization.
  
  

• BSc in Computer Science or related degree, or equivalent practical experience.
• 7+ 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.
  
  

• 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.
• Published research, open-source contributions, or side projects demonstrating innovative AI applications.