Principal AI Engineer

Team: AI/ML

Location: Remote

Commitment: Full Time

Workplace Type: remote

Salary:

This position may be hired at multiple levels. Final leveling is determined during the interview process based on a candidates experience, skills, and interview outcomes, and the applicable salary range will align with the final level assigned.

Compensation is determined based on factors including experience, expertise, interview performance, and geographic location, where applicable.

What You Will Do:

• Set technical direction: Own architecture for our most complex GenAI and agentic systems end-to-end, and set the standards — evaluation, observability, responsible AI — that the practice builds to.

• Build at the frontier, hands-on: Stay in the code where it matters most — foundation-model and embedding fine-tuning, novel agentic workflows, advanced RAG and semantic search — using Python on Google Cloud (Vertex AI), LangChain/LlamaIndex, and vector search (Vertex AI Vector Search, Pinecone, pgvector).

• Engineer for production: Design for latency, reliability, cost, and scale from day one; apply MLOps discipline so systems are served efficiently, monitored, and continuously improved — and actually reach production, where most AI work stalls.

• Lead multi-step reasoning at scale: Architect and operate agentic workflows that automate complex reasoning reliably, with the design and verification discipline that keeps multi-agent systems from cascading into failure.

• Advise clients and shape deals: Work directly with client leadership to understand strategy, propose state-of-the-art approaches, and shape solutions in pre-sales — the technical authority in the room.

• Multiply the team: Elevate senior and mid-level engineers through architecture reviews, mentorship, and setting a high, teachable bar for AI-augmented engineering.

Your Technical Toolkit:

• Core Languages: Mastery of Python and shell scripting; fluency across the modern AI engineering stack.

• AI/LLM Ecosystem: Deep, current expertise with Google Gemini, GPT-class, and open models (LLaMA); advanced prompt engineering, fine-tuning, and evaluation.

• Agentic Systems: Proven experience designing and productionizing agentic and multi-step reasoning systems (MCP, tool use, orchestration) — not just prototypes.

• Data & Search: Expertise in vector databases (Vertex AI Vector Search, pgvector, Pinecone) and semantic search at production scale.

• Infrastructure: Deep hands-on experience with Google Cloud / Vertex AI and architecting scalable, resilient software systems.

• Frameworks: Strong command of LangChain, LlamaIndex, or equivalent orchestration layers — and the judgment to know when not to reach for them.

• Engineering foundation: A first-class software engineer — clean, maintainable code, full SDLC ownership, and the architectural judgment to lead others.

Basic Qualifications:

• Bachelors or Masters degree in Computer Science, Engineering, or a related technical field.

• 10+ years in software / AI / ML engineering, with a substantial track record of AI systems delivered to production at scale.

• Demonstrated technical leadership — owning architecture and setting direction across engagements or teams, not just individual deliverables.

• Proven track record of deploying GenAI and/or agentic products to production environments.

• Experience with classic machine learning (neural nets, training, tuning) strongly preferred; foundation-model or novel-model work a distinct plus.

• Strong data engineering and SQL knowledge.

• Senior client-facing experience — translating technical complexity into business value for executive stakeholders.

Personal Attributes:

• Ownership at scale: You take responsibility not just for your code, but for the outcome of the system and the success of the team building it.

• Curiosity: The AI landscape changes weekly; you stay at the frontier and bring the team with you.

• Consultative authority: You earn the trust of client leadership and are the calm, credible technical voice in a high-stakes room.

• Ethics: You hold the line on responsible AI development and data privacy.