Basic InformationJob Name Principal Product Developer - USA (B)
Country United States
State California
City Santa Clara
Date Published 22-Apr-2026
Job ID 46654
Travel You may occasionally be required to travel for business
Additional Locations Milpitas - Mountain View - East Foothills - Los Altos - Stanford - Santa Clara
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HEREDescription and RequirementsWe 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, controllability, 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:
- LangGraph and/or LangChain
- LlamaIndex
- Vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus)
- Prompt engineering as a managed, versioned, testable artifact
- Experience deploying and operating LLMs using:
- AWS SageMaker, Vertex AI, or equivalent managed platforms
- Direct API integrations (OpenAI, Anthropic)
- Experience designing multi-agent systems or complex agent workflows.
- Experience commercializing AI features under enterprise constraints (security, compliance, uptime).
- Comfort operating in ambiguity and making decisions with incomplete information.
Whilst these are nice to have, our team can help you develop in the following skills: - 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).
Our commitment to you! BMC's culture is built around its people. We have 6000+ brilliant minds working together across the globe. You won't be known just by your employee number, but for your true authentic self. BMC lets you be YOU!
If after reading the above, You're unsure if you meet the qualifications of this role but are deeply excited about BMC and this team, we still encourage you to apply! We want to attract talents from diverse backgrounds and experience to ensure we face the world together with the best ideas!
The annual base salary range represents the low and high end of the BMC salary range for this position. Actual salaries depend on a wide range of factors that are considered in making compensation decisions, including but not limited to skill sets; experience and training, licensure, and certifications; and other business and organizational needs.
The range listed is just one component of BMC's employee compensation package. Other rewards may include a variable plan and country specific benefits.
At BMC, it is not typical for an individual to be hired at /near the top of the range. A reasonable estimate of the current range is $175,800 - $293,000
