AI Transformation Engineer
Build and deploy production AI systems, including agentic workflows, RAG applications, and LLM-powered services. The role requires 5+ years of engineering experience, strong Python skills, cloud and containerization experience, and the ability to lead technical initiatives and mentor engineers.
About the job
Responsibilities
- Design, build, and maintain production-grade AI systems, including multi-agent workflows, RAG applications, workflow automation, and LLM-powered services.
- Lead technical implementation of complex AI initiatives from discovery through deployment.
- Architect scalable backend services, APIs, evaluation pipelines, and retrieval systems.
- Improve reliability, observability, and performance of production AI applications.
- Define engineering standards, reusable components, and AI development best practices.
- Collaborate with business stakeholders to translate problems into scalable AI solutions.
- Evaluate foundation models, frameworks, and prompting strategies.
- Build evaluation frameworks and automated testing strategies for LLM systems.
- Mentor junior engineers through code reviews, technical guidance, and design discussions.
- Participate in architectural planning, sprint planning, technical reviews, and cross-functional initiatives.
- Drive improvements in engineering processes, documentation, and operational excellence.
Requirements
- 5+ years of experience in software engineering, machine learning engineering, AI engineering, or a similar technical role.
- Strong Python development skills and experience building and maintaining production systems.
- Deep understanding of LLMs, prompting techniques, structured outputs, tool calling, function calling, and AI application architectures.
- Experience designing and deploying RAG systems, including chunking, embeddings, retrieval optimization, reranking, and evaluation.
- Experience building agentic workflows with LangGraph, LangChain, OpenAI Agents SDK, or similar frameworks.
- Experience integrating external APIs and enterprise systems.
- Understanding of testing, CI/CD, observability, monitoring, and production deployments.
- Experience with cloud platforms, preferably Google Cloud, and containerized applications.
- Strong debugging, problem-solving, communication, and independent project-management skills.
Compensation & Benefits
- Competitive salary and comprehensive benefits.
- Opportunities for professional growth and training.
- Access to AI tools and a collaborative workplace.
Skills
Python, LLMs, Prompt Engineering, RAG, Embeddings, LangGraph, LangChain, Openai Agents Sdk, APIs, CI/CD, Observability, GCP, Containers, Automated Testing
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