Principal AI Engineer (AI)

TL;DR

Principal AI Engineer (AI): Building and optimizing an Agentic AI platform from scratch with an accent on designing, coding, and shipping production-grade AI capabilities. Focus on architectural trade-offs, integrating LLMs, and addressing real-world issues like hallucinations and drift.

Location: Hybrid in Santa Clara, California, United States. Additional locations include Milpitas, Mountain View, East Foothills, Los Altos, Stanford.

Salary: $171,825–$286,375

Company

BMC empowers nearly 80% of the Forbes Global 100 to accelerate business value through industry-leading solutions.

What you will do

• Design, build, and evolve agentic AI systems that reason, plan, execute, and adapt in production environments.
• Take AI-driven features from concept to production in a true 0–1 product environment.
• Write and review high-quality production code (Python-first) across AI pipelines, inference services, and orchestration layers.
• Implement prompt engineering, tool use, memory, evaluation, and guardrails as first-class engineering concerns.
• Integrate and operate LLMs (commercial and/or open-source) including model selection, fine-tuning strategies, embeddings, and RAG.
• Deploy and operate AI services across cloud platforms (AWS, Azure, GCP) including secure enterprise integrations.

Requirements

• 10+ years of professional software development experience, with significant time shipping B2B products used by external customers.
• Strong software engineering foundation with expert-level Python and experience designing production systems.
• Proven experience building, deploying, and operating AI-powered products in production, not just prototypes or research.
• Hands-on experience with LLMs and GenAI systems in real applications (e.g., agents, copilots, automation, decision systems).
• Deep understanding and hands-on experience with agent frameworks, prompt engineering, RAG architectures, model evaluation, safety, and enterprise controls, including LangGraph, LangChain, LlamaIndex, and vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus).
• Experience deploying and operating LLMs using AWS SageMaker, Vertex AI, or direct API integrations.

Nice to have

• Contributions to open-source GenAI tooling or internal frameworks used at scale.
• Experience with Supervised fine-tuning, Parameter-efficient tuning methods (LoRA, QLoRA), reinforcement learning (RLHF), and preference optimization (PPO, DPO, GRPO).
• Experience deploying LLMs at scale (Kubernetes, model serving, GPU optimization).

Culture & Benefits

• BMC’s culture is built around its people, allowing you to be your true authentic self.
• Opportunity to work with over 6000 brilliant minds across the globe.
• Commitment to equal opportunity employment regardless of race, age, sex, creed, or other characteristics.
• Competitive annual base salary range with additional rewards that may include a variable plan and country-specific benefits.