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NVIDIA

Senior AI Engineer, Forward Deployed Engineering

NVIDIA is hiring a Senior AI Engineer, Forward Deployed Engineering in Santa Clara, United States. It pays $200k-$322k a year and Level rates it ; you can apply on NVIDIA.

Level's read on this job

  • On Level's scale, this AI engineer role is Builds AI ●●●●: the job is building AI systems.
  • Pay on this posting starts 9% higher than the typical AI engineer posting on Level.
  • The posting mentions RAG and AI agents among its tools and skills.
  • NVIDIA has 2,600+ other open roles on Level.
  • Posted in the last few days.

AI in this role

ragai-agents

Join the AI & Automation Supply Chain Business Transformations team in NVIDIA Operations to build the next generation of decision intelligence for our supply chain on Palantir Foundry and AIP. As a Senior AI Engineer and Forward Deployed Engineer, you will work directly with planners and supply-chain experts to turn their decision logic into production applications: governed data pipelines, Ontology models, analytical functions, operational interfaces and AI agents that are trusted, tested and used every day. This is a rare opportunity to shape how one of the world's most advanced AI companies runs its own supply chain. If you thrive at the intersection of Palantir engineering, applied AI and supply-chain transformation, join us.


What you will be doing:

  • Build and own production supply-chain applications on Palantir Foundry and AIP, including data pipelines, Ontology models (object, link and action types), analytical functions, operational interfaces (Workshop and OSDK) and controlled actions.
  • Work directly with supply-chain planners and experts to convert business rules, constraints and exception procedures into documented, versioned and testable software.
  • Combine analytical methods, optimization and language models to support operational decisions, selecting the approach that meets each use case's correctness, reliability and performance requirements.
  • Own automated testing and validation across application code, data pipelines, business rules and agent workflows. Establish acceptance criteria with domain experts and enforce checks before release.
  • Use AI coding tools effectively while remaining accountable for code quality: review generated code, validate assumptions and verify behavior against independently defined expected results.
  • Build evaluation datasets from approved scenarios and historical decisions. Test edge cases, repeatability, permissions, failure recovery and changes to models, prompts, tools and data.
  • Define agent autonomy boundaries, human-in-the-loop workflows and escalation strategies for enterprise supply-chain use cases built on AIP.
  • Measure operational results, including decision cycle time, manual effort, exception resolution and decision quality. Capture user corrections and outcomes to guide improvements.
  • Capture design requirements, translate them into user stories, lead technical design reviews and documentation, drive end-to-end integration testing and support UAT and hyper care.

What we need to see:

  • Demonstrated hands-on production delivery on Palantir Foundry and AIP: Python or Pipeline Builder transforms, Ontology design (object, link and action types), Workshop or OSDK applications, AIP Logic and Functions, and Data Connection sources, with ownership after go-live.
  • Working knowledge of Foundry governance and release management: projects and roles, markings, branching, and environment promotion across development, UAT and production.
  • Bachelor's degree in Computer Science or a related field (or equivalent experience).
  • 12+ years of demonstrable experience in software architecture, systems design or enterprise platform engineering.
  • Strong Python and SQL development skills, with experience integrating enterprise systems (ERP, planning, ITSM) through APIs, data connectors or custom services.
  • Proven ability to implement complex business rules and explain how their correctness was established.
  • Strong automated testing, debugging and release practices, including validation of AI-assisted development and LLM-based workflows.
  • Practical experience integrating and evaluating language models, including open models such as NVIDIA Nemotron.
  • Ability to work directly with operational users, resolve ambiguous requirements and deliver maintainable software.
  • Excellent collaboration and communication skills, with the ability to explain complex designs clearly and build trusted partnerships across technical and business audiences.

Ways to stand out from the crowd:

  • Supply-chain, manufacturing, planning or operations research experience.
  • Experience with constraint optimization, simulation and scenario analysis.
  • TypeScript development and advanced Palantir application development.
  • Experience with agentic frameworks and patterns (RAG pipelines, multi-agent orchestration, vector search) and with NVIDIA NeMo Guardrails or GPU-optimized inference stacks.
  • Hands-on experience with containerized deployments, Kubernetes and hybrid cloud/on-prem environments and evidence of measurable improvements from systems used in daily operations.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and creative people in the world working here! If you are driven by impact, passionate about enterprise AI, and inspired to shape decision intelligence for NVIDIA's Supply Chain Operations, we want to hear from you. Apply today!

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 200,000 USD – 322,000 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 6, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

How we rate this

Senior AI Engineer, Forward Deployed Engineering at NVIDIA rates 84 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI agents

Also common in AI engineer jobs at this level

Pay

This job starts at
$200k
Typical AI engineer job
$184k

This posting starts 9% above the typical AI engineer job. See AI engineer jobs

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you decide when an AI agent can act on its own versus asking for approval first?
  3. How would you decide a model or AI system is ready to ship?
  4. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: RAG and AI agents. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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