Principal AI Engineer
New
Based in the United StatesFull-TimePrincipal
Salary219,245 - 290,000 USD per year
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Job Details
- Experience
- 10+ years of experience in software engineering, artificial intelligence, or machine learning engineering.
- Required Skills
- PythonSQLGCPData engineeringLLMGenerative AILangChain
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical discipline.
- 10+ years of experience in software engineering, artificial intelligence, or machine learning engineering.
- Proven experience designing and deploying Generative AI and/or agentic AI systems in production environments.
- Strong expertise in Python and shell scripting, with experience building scalable software solutions.
- Deep knowledge of large language models, including GPT-class models, Google Gemini, and open-source models such as LLaMA.
- Advanced experience with prompt engineering, model evaluation, fine-tuning, and AI system optimization.
- Hands-on experience with retrieval-augmented generation, vector databases, semantic search, and information retrieval concepts.
- Experience designing and productionizing AI agents, including tool usage, orchestration, and multi-step reasoning workflows.
- Strong experience with cloud platforms, particularly Google Cloud and Vertex AI.
- Familiarity with AI frameworks such as LangChain, LlamaIndex, or equivalent orchestration technologies.
- Strong software engineering foundation, including clean coding practices, SDLC ownership, and scalable architecture design.
- Strong data engineering and SQL knowledge.
Responsibilities
- Own the architecture and technical direction of advanced Generative AI and agentic AI systems from concept through production.
- Design and build AI solutions involving foundation models, retrieval-augmented generation (RAG), semantic search, and intelligent agent workflows.
- Develop scalable AI platforms that meet real-world requirements for reliability, latency, cost efficiency, security, and governance.
- Build and optimize AI pipelines, including embeddings, fine-tuning, evaluation frameworks, orchestration, and model deployment.
- Architect multi-step reasoning and agentic workflows that enable reliable automation of complex business processes.
- Establish engineering standards around responsible AI practices, observability, evaluation, and system performance.
- Partner with executive stakeholders and clients to translate business challenges into AI architectures and technical strategies.
- Support pre-sales activities by shaping innovative AI solutions and providing technical leadership.
- Mentor engineers through architecture reviews, technical guidance, and best practices for AI engineering.
- Continuously evaluate emerging AI technologies and incorporate relevant advancements into solution strategies.
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