Principal AI Engineer - AgenticAI

Basic Information

Job Name

Principal AI Engineer - USA (B)

Country

United States

State

California

City

Santa Clara

Date Published

22-Apr-2026

Job

46654

Travel

You may occasionally be required to travel for business

Additional Locations

Milpitas - Mountain View - East Foothills - Los Altos - Stanford - Santa Clara

Looking for more details about our benefits? You can also learn all about them by clicking HERE

Description and Requirements

Career Arc Code

CA-BS

#LI-BS1

Hybrid: #LI-Hybrid

BMC empowers nearly 80% of the Forbes Global 100 to accelerate business value, faster than humanly possible. Our industry-leading portfolio unlocks human and machine potential to drive business growth, innovation, and sustainable success. BMC does this in a simple and optimized way by connecting people, systems, and data that power the world's largest organizations so they can seize a competitive advantage.

We are looking for a Principal AI Engineer to build our next-generation Agentic AI platform from 0-1. This is a hands-on, delivery-driven role for a senior engineer who has shipped AI-powered products into real enterprise environments, understands the trade-offs of production AI systems, and takes full ownership of outcomes - not just models or demos.

You will work alongside our VP of Engineering, VP of AI and product leadership to define and build the core AI systems of the platform. You will spend most of your time designing, coding, and shipping production-grade AI capabilities used by external B2B customers. Success is measured by reliability, cont rollability, cost-efficiency, and customer impact - not novelty.

Here is how, through this exciting role, YOU will contribute to BMC's and your own success:

* 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, orchestration layers, and supporting systems.

* Implement prompt engineering, tool use, memory, evaluation, and guardrails as first-class engineering concerns, not experiments.

* Design agent frameworks that balance autonomy with determinism, observability, and safety.

* Make pragmatic architectural trade-offs across latency, cost, accuracy, scalability, and maintainability.

* Integrate and operate LLMs (commercial and/or open-source) including model selection, fine-tuning strategies, embeddings, retrieval (RAG), and inference optimization.

* Address real-world issues: hallucinations, drift, prompt regressions, failure modes, and customer trust.

* Deploy and operate AI services across cloud platforms (AWS, Azure, GCP), including secure enterprise integrations and customer-specific deployments.

* Design scalable inference and orchestration architectures using containers, APIs, and distributed systems.

* Ensure the platform is shippable, debuggable, and supportable - not fragile or research-grade.

* Act with founder-level ownership: identify gaps, propose solutions, and move forward without waiting for perfect requirements.

To ensure you're set up for success, you will bring the following skillset & experience:

* 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 of at least several of the following:

* Agent frameworks and orchestration

* Prompt engineering and tool-use patterns

* RAG architectures and vector search

* Model evaluation, feedback loops, and monitoring

* Safety, guardrails, and enterprise controls

* Hands-on experience with multiple of the following in real systems:

* Lang Graph and/or Lang Chain

* Llama Index

* Vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus)

* Prompt engineering as…