Level

Together AI

Forward Deployed Engineer, Strategic Inference

Together AI is hiring a Forward Deployed Engineer, Strategic Inference in San Francisco, United States. It pays $270k-$300k a year and Level rates it ; you can apply on Together AI.

Level's read on this job

  • On Level's scale, this forward deployed engineer role is Builds AI ●●●●: the job is building AI systems.
  • Pay on this posting starts 48% higher than the typical forward deployed engineer posting on Level.
  • The posting mentions vLLM, Cursor and Elevenlabs among its tools and skills.
  • Together AI has 83 other open roles on Level.

AI in this role

vllmcursorelevenlabsdecagon
fine-tuning

About the role

As a Forward Deployed Engineer (FDE) focused on Inference, you will be a hands-on technical partner to our most strategic customers — production AI teams looking to leverage high quality models and do inference at scale. For us, FDE is not a replacement for a Solutions Architect; you will partner with our SAs as a deep-domain specialist in inference optimization, fine-tuning pipelines, and production deployment. As key contributors to both the CX, Engineering, and Sales organizations, FDEs add tremendous value by ensuring we can meet the requirements of our most complex POCs, facilitate successful platform adoption, and guide tailored optimization efforts — directly impacting customer success, company growth, and the hardening of our core platform.

Responsibilities

  • Inference Engine Optimization: Select, configure, and optimize inference engine based on hardware, model architecture, and workload profile
  • Configuration & Performance Tuning: Develop configuration updates to win critical POCs, benchmarks, and optimize customer deployments; tune KV cache, apply speculative decoding, determine optimal tensor parallelism, and determine quantization strategy to hit throughput and latency targets.
  • Strategic Customer Alignment: Act as the primary technical point of contact for aligned strategic accounts — monitoring and optimizing endpoint configurations, helping customers get the most out of the platform, and collaborating to ensure we hit critical milestones.
  • Opinionated Onboarding: Establish direct alignment with strategic customers at onboarding; ensure the right inference configurations are in place from day one to improve time-to-value.
  • Product Feedback Loop: Directly influence our software and model roadmap by surfacing insights from the field. Contribute back to the product where needed to support customer requirements or drive a better experience. Drive early feature and research adoption with strategic logos.

Qualifications

  • Experience: 5+ years in a technical role, with a strong focus on system optimization. Recent experience in  inference systems and open-source LLM deployments.
  • Inference Engine Depth: Expert-level, hands-on experience with inference engines (e.g., vLLM, TensorRT-LLM, SGLang); ability to diagnose and resolve performance issues at the engine level.
  • Inference Optimization: Deep knowledge of KV cache tuning, speculative decoding, tensor parallelism, pipeline parallelism, and quantization techniques
  • Model Landscape Awareness: Broad knowledge of state-of-the-art open-source models and strong judgment on model selection for specific customer use cases, hardware profiles, and performance targets.
  • Coding Proficiency: Strong Python skills; comfortable working in production environments
  • Experience leading complex projects with exceptional project management and communication skills

About Together AI

Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month.

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $270,000 - $300,000 OTE + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. 

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our Privacy Policy at https://www.together.ai/privacy

How we rate this

Forward Deployed Engineer, Strategic Inference at Together AI rates 86 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

Fine-tuningvLLMCursorElevenlabsDecagon

Also common in forward deployed engineer jobs at this level

Pay

This job starts at
$270k
Typical forward deployed engineer job
$182k

This posting starts 48% above the typical forward deployed engineer job. See forward deployed engineer jobs

Questions you could be asked

  1. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  2. Walk me through how you've used vLLM in your day-to-day work.
  3. What are the limits of Cursor that you've run into, and how did you work around them?
  4. What's a project where you used Elevenlabs hands-on?
  5. Walk me through how you've used Decagon in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Fine-tuning, vLLM, Cursor, Elevenlabs, and Decagon. 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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