Principal AI Engineer

Ovii's Interpretation of the Role

The Principal AI Engineer leads the technical vision and hands‑on delivery of complex generative‑AI and agentic systems, turning ambiguous business problems into production‑ready services. You will own architecture, drive MLOps best practices, and serve as the trusted technical advisor for high‑stakes client engagements.

Role Snapshot

• Technical leader for GenAI systems
• Hands‑on AI software engineer
• Client‑facing solution architect
• Mentor for senior and mid‑level engineers
• Production‑scale AI delivery

Must-Have Requirements

• Python
• Shell scripting
• Google Cloud / Vertex AI
• LangChain or LlamaIndex
• Vector databases (Pinecone, pgvector, Vertex AI Vector Search)
• LLM expertise (Gemini, GPT‑class, LLaMA)
• Prompt engineering
• Agentic system design
• MLOps
• Data engineering
• SQL
• software AI ML engineering
• production AI systems
• technical leadership
• Bachelor's or Master's degree in Computer Science, Engineering, or related technical field

Nice-to-Have Signals

• Classic machine learning (neural nets, training, tuning)
• Foundation‑model or novel‑model work
• classic machine learning
• foundation‑model work

Work Setup

• Work mode: REMOTE
• Remote scope: UNSPECIFIED
• Employment type: Full-Time

Eligibility Gates

• Visa sponsorship: unknown
• Background check: standard hiring verification practices

Not Specified in JD

• Visa sponsorship
• Relocation
• Travel
• Shift requirements
• Security clearance
• Coding test
• Portfolio
• GitHub
• Writing sample
• Cover letter

What You'll Likely Work On

• Define and own architecture for the most complex generative‑AI and agentic platforms, establishing standards for evaluation, observability and responsible AI
• Develop foundation‑model fine‑tuning, novel agentic workflows and advanced RAG pipelines using Python on Vertex AI and orchestration frameworks
• Engineer production‑ready AI services with latency, reliability, cost and scale in mind, applying rigorous MLOps practices
• Design and operate large‑scale multi‑agent reasoning systems, ensuring robustness and preventing cascade failures
• Partner directly with client leadership to translate strategy into AI solutions, shape pre‑sales proposals and act as the technical authority
• Elevate senior and mid‑level engineers through architecture reviews, mentorship and setting a high, teachable engineering bar

Good Fit If You Have

• Enjoys staying at the AI frontier and continuously learning new models and tools
• Thrives in high‑stakes, client‑facing environments where clear communication of technical risk is essential
• Demonstrates strong ownership of end‑to‑end system outcomes, not just code