$200K – $400K/yr
● Top 10% pay versus similar roles
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Pay vs market · Bottom quarter
This job's pay ($198,000 a year at the midpoint) is higher than about 25% of 77 salary-listed Senior Software Engineer jobs in San Francisco in the last 12 months; their median is $220,000.
Role overview
About Handshake Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions. In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We’ve grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month. Why join Handshake now: Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel Partner hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions Work together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders Build a massive, fast-growing business with billions in revenue About Handshake AI Human data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale. About the Role Handshake is hiring a Senior LLM Platform Engineer to join our Data and ML Platform team. This team supports Handshake’s core career marketplace and Handshake AI (HAI) by building the shared data, ML, and LLM infrastructure behind production workflows. This infrastructure-heavy role primarily owns our shared LLM control plane: LiteLLM gateways, provider integrations, shared clients, access controls, observability, cost attribution, capacity management, and hosted or self-hosted inference. You’ll also contribute to adjacent platform systems for workflow orchestration, model serving, shared cloud infrastructure, and developer enablement—working closely with Backend Platform, HAI engineering, data science, and FDEs. What You’ll Do Build and operate our LiteLLM-based AI gateways and shared LLM clients. Own provider and model onboarding, routing, failover, rate limits, and capacity planning. Build self-service virtual-key, model-access, budget, and credential-management workflows. Establish SLOs, observability, cost attribution, and alerts for production LLM traffic. Safely qualify and roll out new models, providers, SDKs, and gateway configurations. Support hosted and self-hosted inference through a consistent platform interface. Partner with product, AI, and FDE teams to turn recurring delivery problems into paved-platform capabilities. Contribute to the broader Data and ML Platform, including workflow orchestration, model serving, shared cloud infrastructure, and developer tooling. Participate in team on-call and support, improving runbooks, automation, and reliability across owned platform services. What We’re Looking For Strong production software engineering experience in Python, TypeScript, Go, or a similar language. Experience building or operating high-throughput API gateways, proxies, or multi-tenant platform services. Hands-on experience with Kubernetes, Terraform, CI/CD, and production service ownership. Practical experience with LLM provider APIs, including streaming, long-running requests, retries, timeouts, cancellation, and rate limits. Experience with authentication, quotas, credential management, tenant isolation, and auditability. Experience building observability for distributed systems and leading production incident response. Experience with usage metering, cost attribution, capacity planning, or FinOps. Experience with data or ML platform systems such as BigQuery, Airflow, streaming pipelines, model serving, or ML observability. Strong judgment in ambiguous environments and a bias toward simple, reliable systems that scale. Bonus Experience LiteLLM, Portkey, or a comparable multi-provider AI gateway. vLLM, Modal, Ray, Triton, PyTorch, or GPU-backed serving. Temporal or another durable-execution system for long-running LLM requests. Evaluation, batch inference, fine-tuning, RL, or other post-training infrastructure. Agent runtimes, sandbox infrastructure, MCP, tool use, or coding-agent infrastructure. Our Stack Python, TypeScript, Go, LiteLLM, FastAPI, PostgreSQL, Redis, GCP, Kubernetes, Terraform, Spacelift, BigQuery, Airflow, Dataflow/Beam, Datastream, OpenAI, Anthropic, Gemini, OpenRouter, vLLM, Modal, Anyscale/Ray, Datadog, Arize, Temporal, Cloudflare, and Tailscale Perks Handshake delivers benefits that help you feel supported—and thrive at work and in life. The below benefits are for full-time US employees. 🎯 Ownership: Equity in a fast-growing company 💰 Financial Wellness : 401(k) match, competitive compensation, financial coaching 🍼 Family Support: Paid parental leave, fertility benefits, parental coaching 💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend 📚 Growth: $2,000 learning stipend, ongoing development 💻 Remote & Office: Internet, commuting, and free lunch/gym in our SF office 🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days 🤝 Connection: Team outings & referral bonuses Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers .
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Role market pulse
Live jobs
1,038
Posted 30d
704
30d movement
+291.1%
Remote share
31%
Salary listed
85%
Salary trend 1Y
Not enough history
What they are looking for
Qualification
About the Role Handshake is hiring a Senior LLM Platform Engineer to join our Data and ML Platform team; This team supports Handshake’s core career marketplace and Handshake AI (HAI) by building the shared data, ML, and LLM infrastructure behind production workflows; This infrastructure-heavy role primarily owns our shared LLM control plane: LiteLLM gateways, provider integrations, shared clients, access controls, observability, cost attribution, capacity management, and hosted or self-hosted inference; What You’ll Do Build and operate our LiteLLM-based AI gateways and shared LLM clients
Department · Engineering
Hiring company
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