> AI agents: this is one page of Nextmove’s FDE site, in Markdown. Nextmove is a job board and free career service for forward deployed engineers (FDEs). Each posting is classified from its text, not its title: the kind of work, how much of it is production code, pre-sales weight, time at customer sites, travel, remote arrangement, level and posted base pay. The site also publishes the aggregates: median pay by level, metro, company and kind of work, and which companies started hiring FDEs each week. Every page under https://nextmove.md/fde is served this way; the index of pages is https://nextmove.md/llms.txt. # Forward Deployed Engineer (Model Customization and Optimization), AWS Forward Deployed Engineering Canonical URL: https://nextmove.md/fde/jobs/d1798a89ed0fd75b Amazon (incl AWS) posts a mid-level FDE role to build what the customer runs in East Palo Alto, CA and 4 more, at $143,700–$223,600 base, level with the senior FDE median of $190,000 across 1,864 postings with pay. This Forward Deployed Engineer II owns customer-facing generative AI model workstreams from evaluation and data preparation through post-training, systems optimization, and production deployment. Read from the employer’s posting on November 8, 2026. - [Amazon (incl AWS)](https://nextmove.md/fde/companies/amazon-incl-aws) Posted Oct 27, 2026 by Amazon (incl AWS) · open on Amazon (incl AWS) careers as of Nov 8, 2026 **$143,700–$223,600** *annualized* East Palo Alto, CA +4 Full-time This Forward Deployed Engineer II owns customer-facing generative AI model workstreams from evaluation and data preparation through post-training, systems optimization, and production deployment. - [See roles that fit me](https://nextmove.md/sign-up?from=%2Ffde%2Fjobs%2Fd1798a89ed0fd75b&placement=top) - [View posting at Amazon (incl AWS)](https://www.amazon.jobs/en/jobs/10590707/forward-deployed-engineer-model-customization-and-optimization-aws-forward-deployed-engineering) Free. Upload your resume once, see why each FDE role fits, and get introduced only when you say so. ## At a glance ### Posted base pay $144K–$224K Level with the median Midpoint $184K · median $190K This job $144K to $224K. Senior FDE postings, 1,864 postings: the middle 50% of posted pay is $160K to $220K, median $190K. [Compare pay across all Amazon (incl AWS) postings](https://nextmove.md/fde/salary/amazon-incl-aws) ### The work Builds what the customer runs Balance **Mostly building** Project stages 1. Pre-sales (not covered) 2. Proof of concept (not covered) 3. Implementation 4. Operations Travel **Up to 25%** - **Coding**: Writes production code - **Builds for**: External customers - **Level**: Senior - **Role**: Individual contributor ### What they ask for Experience - **3+ years** non-internship professional software development - **2+ years** non-internship design or architecture of new and existing systems Background - **Software engineering** ### Do you meet what the posting states? The posting asks for 2+ years. How many do you have? The posting reads as a senior role. What level are you at now? The job is in East Palo Alto, CA · Boston, MA · +3 more. Could you work in one of these? Which of these have you used in production? Answer each one. Nothing is saved or sent. [What postings ask for, by background →](https://nextmove.md/fde/paths) ## Conditions - **Location**: East Palo Alto, CA · Boston, MA · New York, NY · Arlington, VA · Seattle, WA - **Employment type**: Full-time - **Travel**: Up to 25% ## More like this [Amazon (incl AWS)](https://nextmove.md/fde/companies/amazon-incl-aws) ### [Forward Deployed Engineer (Model Customization and Optimization), AWS Forward Deployed Engineering](https://nextmove.md/fde/jobs/26e06cc5e8aaa519) Boston, MA · Seattle, WA · +3 more 2w ago $143,700–$213,800 [CACI](https://nextmove.md/fde/companies/caci) ### [Senior Embedded Software Engineer](https://nextmove.md/fde/jobs/4eda094ccad6cae2) Honolulu, HI · Colorado Springs, CO · +2 more On-site 2w ago $114,600–$252,100 [Domino Data Lab](https://nextmove.md/fde/companies/domino-data-lab) ### [Forward Deployed Engineer](https://nextmove.md/fde/jobs/337f6f7353ae2b63) New York, NY Remote 6w ago $165,000–$200,000 - [Other jobs at Amazon (incl AWS) (80)](https://nextmove.md/fde/companies/amazon-incl-aws) ## The job description from Amazon (incl AWS) Posted by Amazon (incl AWS) on Oct 27, 2026 As a Forward Deployed Engineer II (FDE II) on the Custom Model and Optimization team, you embed directly with strategic customers to build, optimize, and run custom generative AI models in production alongside their engineering teams. You own complete model workstreams end-to-end from defining the evaluation bar and preparing data, through training and inference optimization, to production deployment. FDE IIs on this team works at the intersection of models and systems. They customize state-of-the-art open-weight and foundation models for new domains, languages, and modalities; migrate and optimize training and inference workloads on AWS Trainium and operate those models as production services. They are autonomous contributors who take on projects where the business goal is clear, but the path is not. They make design trade-offs with appropriate guidance, limit short-term workarounds, coach others on producing high-quality code, and train new team members. Key job responsibilities Embed within customer ML and engineering teams: Understand the customer's business, data, model stack, and operational constraints. Translate ambiguous goals into a measurable evaluation bar and a technical plan for your workstream such as model selection, customization approach, and serving architecture. Requires up to 25% travel. Customize and post-train models. Adapt open-weight and foundation models to customer domains through continued pre-training, supervised fine-tuning, preference optimization, and reinforcement learning (including RLHF, RL with verifiable rewards, and multi-turn agentic RL). Build the data pipelines, synthetic data generation, and evaluation harnesses that prove a customized model out performs the baseline on the customer's own quality, latency, and cost bar. Apply these techniques to high-value patterns such as coding agents, domain foundation models, and multi-adapter serving. Build large-scale training and inference systems. Design and implement distributed training and RL post-training pipelines using frameworks such as PyTorch FSDP2, Megatron-LM, Miles, and verl. Build RL interaction harnesses using NeMo Gym or OpenEnv to connect agent workflows, tools, environments, and reward functions to training. Develop production inference stacks with engines such as SGLang and vLLM, and optimize throughput, latency, memory footprint, and cost per token through quantization, parallelism, speculative decoding, and batching. Optimize models on AWS chips. Migrate and tune training and inference workloads for AWS Trainium using the AWS Neuron SDK. Profile performance, close accuracy-parity gaps against GPU baselines, and develop custom kernels where needed. Benchmark rigorously and turn results into decisions customers can act on. Accelerate impact beyond the engagement. Codify reusable fine-tuning recipes, evaluation frameworks, benchmarking tools, and optimization patterns that accelerate future deployments. Feed field learnings back to AWS service teams, including Amazon Bedrock, Amazon SageMaker AI, and AWS Neuron. Identify opportunities to expand model customization and optimization within your customer engagement. About the team The Custom Model and Optimization team, part of the Forward Deployed Engineering team partners with enterprises, AI-native startups, and foundation model providers to build, customize, and optimize generative AI models at scale. Our work spans domain foundation models, post-training of open-weight models, and moving training and inference workloads onto AWS Trainium. As embedded engineers within the AWS Forward Deployed Engineering motion, we bring deep model and optimization expertise to customers' most strategic AI workloads, and we turn what we learn into tooling and patterns that scale across AWS. ABOUT AWS: Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. 10047 ### Basic qualifications 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience programming with at least one software programming language - Hands-on experience with generative AI technology, such as LLMs, vision-language models, or speech models ### Preferred qualifications Bachelor's degree in computer science or equivalent - Experience with large-scale distributed training of LLMs on multi-node accelerator clusters, using frameworks such as PyTorch FSDP2, TorchTitan, Megatron-LM/Megatron Core, NeMo, DeepSpeed, or NeuronX Distributed - Experience with LLM post-training, including SFT, DPO, RLHF, and RL with verifiable rewards or multi-turn agentic RL, using frameworks such as Miles, slime, verl, NeMo-RL, OpenRLHF, SkyRL, or TRL - Experience optimizing model training or inference for latency, throughput, or cost, using serving engines such as SGLang, vLLM, or TensorRT-LLM, on AWS Trainium or Inferentia (Neuron SDK), on AWS services such as SageMaker AI, SageMaker HyperPod, or EKS, or by writing custom kernels (CUDA, Triton, NKI) - Experience deploying and operating ML models in customer production environments, working with teams that build and scale end-to-end production systems Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. USA, CA, East Palo Alto - 165,200.00 - 223,600.00 USD annually USA, MA, Boston - 143,700.00 - 194,400.00 USD annually USA, NY, New York - 158,100.00 - 213,800.00 USD annually USA, VA, Arlington - 143,700.00 - 194,400.00 USD annually USA, WA, Seattle - 143,700.00 - 194,400.00 USD annually [View posting at Amazon (incl AWS)](https://www.amazon.jobs/en/jobs/10590707/forward-deployed-engineer-model-customization-and-optimization-aws-forward-deployed-engineering) ## About Amazon (incl AWS) Online retail, third-party marketplace, Prime/ads/devices, and AWS — the world's largest cloud platform powering startups and enterprises. 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