368,634open jobs
9,437companies
50,578added this week
Browse all
Salary
$158k – $339k per year (Estimated)
Location
In office (San Francisco)
Seniority
Staff
Employment
Full-Time
Overview
Company
Impact
Profile match
Prime Intellect is an artificial intelligence infrastructure company headquartered in San Francisco, California, and founded in 2023. The company provides a decentralized platform for training, evaluating, and deploying large-scale AI models, featuring tools for reinforcement learning, agent development, and a global compute marketplace. It operates globally by aggregating computing resources from various providers to enable researchers and developers to build open-source models and autonomous agents.

Forward Deployed AI Strategy Lead

Own Your Intelligence

Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.

Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.

Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators - including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.

The Role

The most important AI products of the next decade will not be built by simply renting GPUs or calling an API.

They will be built by teams that can define the right tasks, construct the right environments, measure the right outcomes, run the right post-training loops, and deploy models that improve on real workflows.

Prime Intellect gives customers that capability. Your job is to make it real.

As a Forward Deployed AI Strategy Lead, you will work directly with strategic customers to identify high-value AI workflows, translate them into evals and post-training opportunities, scope technical deployments with Applied Research, and turn early experiments into long-term revenue.

You are part customer owner, part product strategist, part AI systems thinker, and part commercial operator.

You will not sit between the customer and the technical team as a messenger. You will sit with both sides and help invent the answer.

What You’ll Do

Own Strategic Customer Deployments

You will lead high-priority customer workstreams from first technical discovery through POC, deployment, expansion, and case study.

You will work with customers who are trying to build agents, automate complex workflows, improve model performance, reduce inference cost, build domain-specific evals, or run frontier-scale post-training.

You will help them answer:

  • What should we train or evaluate?

  • What does success actually mean?

  • What workflows are worth turning into environments?

  • What data or traces are needed?

  • What should be automated, supervised, or measured?

  • Which model should be adapted?

  • What is the path from prototype to production?

Turn Ambiguity Into Scope

Customers rarely arrive with a perfectly defined problem.

You will take messy conversations, scattered artifacts, internal docs, product goals, and technical constraints, and turn them into crisp scopes that Applied Research and Engineering can actually execute.

You will define:

  • Use cases

  • Success metrics

  • Eval design

  • Environment requirements

  • Integration needs

  • Milestones

  • Commercial structure

  • Risks and dependencies

  • Expansion path

Partner Deeply With Applied Research

This role works hand-in-hand with Applied Research.

You will bring customer signal into the research and product roadmap, helping the team identify which evals, environments, agents, and post-training recipes matter most in the field.

You will help prioritize work that can both advance the frontier and unlock meaningful customer outcomes.

You should be excited to spend time around questions like:

  • How do we convert real-world workflows into reliable RL environments?

  • What makes an eval useful instead of decorative?

  • When is a verifier good enough?

  • What makes a task trainable?

  • Where does managed RL outperform prompting or manual workflow design?

  • How do we prove performance improvement to a skeptical customer?

Build the Repeatable Motion

Every strategic deployment should make the next one easier.

You will help build the operating system for Prime Intellect’s applied AI motion:

  • Discovery templates

  • Customer qualification frameworks

  • POC structures

  • Proposal language

  • Pricing and packaging inputs

  • Reference architectures

  • Case studies

  • Technical narratives

  • Deployment playbooks

You will help turn one-off customer wins into a repeatable category.

Drive Revenue

This is a customer-facing role with real revenue responsibility.

You will work with leadership to move customers through qualification, legal, scoping, proposal, procurement, POC, deployment, and expansion.

You should be comfortable owning senior customer relationships, creating urgency, writing crisp follow-ups, navigating internal and external stakeholders, and making sure important deals do not die in ambiguity.

What We’re Looking For

We are looking for people who are unusually strong across technical understanding, customer empathy, product judgment, and execution.

You might be a strong fit if you have experience in:

  • Forward deployed engineering or technical GTM

  • AI product strategy or applied AI

  • Solutions architecture for highly technical products

  • Early-stage startup operating roles

  • Product management for AI, infra, devtools, or enterprise software

  • ML engineering, applied research, or AI engineering with customer exposure

  • Venture/investing roles with deep technical and commercial work in AI

You should have:

  • Strong intuition for AI products and workflows

  • Ability to understand technical systems without needing every detail pre-digested

  • Excellent written and verbal communication

  • Comfort operating with executives, researchers, engineers, and operators

  • High agency and low ego

  • Ability to run multiple complex customer workstreams

  • Taste for what makes a deployment valuable

  • Strong commercial instincts

  • Deep curiosity about post-training, agents, evals, RL, and AI infrastructure

  • Ability to make progress before the playbook exists

Bonus Points

  • Experience with RL, SFT, evals, agents, MCP, LangGraph, DSPy, Stagehand, Browserbase, or tool-use workflows

  • Experience working with enterprise AI teams or frontier AI companies

  • Ability to read traces, product docs, API docs, or technical specs and turn them into a deployment plan

  • Experience writing proposals, customer memos, technical scopes, or launch narratives

  • Founder or early startup experience

  • Strong network across AI startups, research labs, or enterprise software buyers

Why This Role

This is one of the highest-leverage roles at Prime Intellect.

The frontier is moving from models to systems: agents, environments, evals, training loops, and deployment infrastructure. Most companies know they need to adapt models to their own workflows, but they do not know how to turn that ambition into a working system.

You will be the person who helps them get there.

You will work on customer problems that are technically real, commercially urgent, and strategically important. You will help shape the product, close the revenue, and define the emerging category of full-stack post-training infrastructure.

This is a role for builders who want to be close to the frontier and close to the market.

What We Offer

  • Competitive cash compensation and meaningful equity

  • Flexible work in San Francisco or hybrid-remote

  • Visa sponsorship and relocation support

  • Professional development budget

  • Team off-sites and conference attendance

  • Direct exposure to frontier AI labs, leading AI startups, and enterprise AI teams

  • A rare opportunity to help define how the next generation of AI systems are trained, evaluated, and deployed

Ready to Build the Interface Between Frontier AI and the Real World?

Apply to help Prime Intellect turn ambitious customer workflows into post-training systems, revenue, and the foundation for open superintelligence.

Free account
Stop reading job ads. Get the ones that fit.
One free account turns this page into a shortlist built around your stack, your level and your pay.
Match on every job. Stack, seniority, pay and location, scored against your profile.
368,634 open roles. Read straight off company career pages, refreshed every day.
Unlimited applications. Every one you send is tracked in one place, on-site or on a company board.
3 tailored CVs a month. Rewritten for the exact job you are applying to. Included free.
Create a free account
Free forever. No card. Under a minute.

Your match

How well do you fit this role?
Two answers are enough for a real match. No account needed.
Check my fit
Answers stay in this browser until you create an account.

Recommended for you based on this role

Similar stack
Same company
San Francisco
$98k – $195k per year (Estimated) • In office • Full-Time • 7+ years exp • Wellington
Java
Python
SQL
Java
Spring Boot
Databases
Apache Kafka
Databricks
Neo4j
AI/ML
Flink
Spark
Frontend
GraphQL
DevOps
Azure
CI/CD
Datadog
Dynatrace
Kibana
Kubernetes
OpenShift
Platform Engineering
Splunk
Amazon ECS
Apply
$69k – $171k per year (Estimated) • Remote/Hybrid • Full-Time • 3+ years exp • Bachelor's Degree • Bogotá
SQL
Databases
Databricks
AI/ML
dbt
LLM
NLP
Context Engineering
Analytics
Power BI
Tableau
Apply
$20k – $49k per year (Estimated) • Remote • Full-Time • Bachelor's Degree
Python
Ruby
SQL
Databases
Amazon Neptune
Neo4j
AI/ML
Hallucination
LangChain
LangGraph
LLM
Model Context Protocol
Spark
AI Agents
LLM Guardrails
DevOps
Ansible
AWS
Azure
CI/CD
Docker
GCP
GitHub Actions
GitLab CI
Jenkins
Kubernetes
Rest API
Terraform
GitHub
GitLab
QA
Playwright
Postman
Selenium
Swagger
Apply
Founding Engineer 1 day ago
$180k – $250k per year • In office • Full-Time • 3+ years exp • New York
Node JS
Python
TypeScript
JavaScript
Node JS
BullMQ
Databases
Redis
AI/ML
AI Agents
LangGraph
LLM
Multimodal AI
LangChain
Anthropic
Deepgram
LiveKit
LLM Guardrails
OpenAI
Text-to-Speech
Frontend
Next.js
React.js
DevOps
Vercel
Apply
$25k – $42k per year • Equity 0–0.2% • Remote • Full-Time • 3+ years exp
Bash
Go
JavaScript
Python
TypeScript
DevOps
AWS
Azure
CI/CD
Datadog
Docker
GCP
GitHub Actions
GitLab CI
Grafana
Incident Management
Kubernetes
Platform Engineering
Prometheus
Terraform
Amazon CloudWatch
GitHub
GitLab
IAM
Cybersecurity
Least Privilege
Apply
$180k – $350k per year • Equity • In office • Full-Time • 5+ years exp • San Francisco
Python
Rust
Databases
Databricks
AI/ML
LangChain
OpenRouter
Perplexity
Together AI
OpenAI
Post-training
Red Teaming
SFT
AI Agents
Function Calling
DevOps
Cloudflare
Datadog
eBPF
GCP
Kubernetes
Service Mesh
Cybersecurity
Falco
FedRAMP
ISO 27001
SOC 2
Threat Modeling
Zero Trust
Management
Zapier
Apply
$150k – $300k per year • Equity • In office • Full-Time • San Francisco
TypeScript
JavaScript
Databases
Databricks
AI/ML
AI Agents
DSPy
LangChain
LangGraph
LLM
OpenRouter
Perplexity
Ray
Reinforcement Learning
RLHF
SGLang
Synthetic Data
Together AI
vLLM
GRPO
LLM Evaluation
OpenAI
Post-training
SFT
Function Calling
Model Context Protocol
Frontend
Next.js
React.js
DevOps
Cloudflare
Datadog
Docker
Grafana
Kubernetes
Prometheus
Terraform
Management
Zapier
Apply
$184k – $372k per year (Estimated) • In office • Full-Time • San Francisco
Python
Rust
TypeScript
JavaScript
Python
FastAPI
Databases
Databricks
AI/ML
LangChain
OpenRouter
Perplexity
Together AI
OpenAI
Post-training
SFT
TPU
Function Calling
Frontend
Next.js
React.js
Tailwind CSS
DevOps
Ansible
Cloudflare
Datadog
GCP
Grafana
Kubernetes
Prometheus
Rest API
Terraform
WebSockets
Management
Zapier
Apply
$150k – $300k per year • Equity • In office • Full-Time • San Francisco
Go
Python
Rust
TypeScript
JavaScript
Python
FastAPI
Databases
Databricks
AI/ML
LangChain
OpenRouter
Perplexity
Together AI
OpenAI
Post-training
SFT
TPU
Function Calling
Frontend
Next.js
React.js
Tailwind CSS
DevOps
Ansible
Cloudflare
Datadog
GCP
Grafana
Kubernetes
Prometheus
Rest API
Terraform
WebSockets
Management
Zapier
Apply
$150k – $300k per year • In office • Full-Time • San Francisco
Python
TypeScript
JavaScript
Python
FastAPI
SQLAlchemy
Databases
Databricks
AI/ML
Fine-tuning
LangChain
LLM
LoRA
OpenRouter
Perplexity
QLoRA
RLHF
SGLang
TensorRT
TensorRT-LLM
Together AI
vLLM
PEFT
NCCL
NVLink
OpenAI
Post-training
SFT
Function Calling
Frontend
Next.js
React.js
shadcn/ui
Tailwind CSS
tRPC
Radix UI
DevOps
Ansible
Cloudflare
Datadog
GCP
GitOps
Google Cloud Run
Google GKE
Grafana
Helm
KEDA
kubectl
Kubernetes
Loki
OpenTelemetry
Prometheus
Rest API
Terraform
Management
Zapier
Apply
$293k – $385k per year • In office • Full-Time • San Francisco
AI/ML
OpenAI
Apply
$180k – $260k per year • Remote/Hybrid • Full-Time • 8+ years exp • Bachelor's Degree • San Francisco
Python
AI/ML
ChatGPT
OpenAI
OpenAI Codex
Cybersecurity
FedRAMP
Apply
$180k – $210k per year • Equity • In office • Full-Time • San Francisco
Node JS
JavaScript
Databases
PostgreSQL
DevOps
PagerDuty
Web3
TRM Labs
Management
Slack
Apply
$252k – $335k per year • Remote/Hybrid • Full-Time • 8+ years exp • San Francisco
AI/ML
ChatGPT
Human-in-the-Loop
OpenAI
OpenAI Codex
DevOps
SLI/SLO/SLA
Apply
$223k – $424k per year (Estimated) • In office • Bachelor's Degree • San Francisco
AI/ML
AI Agents
LLM
Recommender Systems
Apply
See all jobs
This is one of many
368,634 more open roles from verified company boards, updated every day.