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Handshake

Senior Software Engineer, LLM Platform

San Francisco, CA

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hirly's read of this role

Role family
Engineering
Seniority
Senior
Stated salary
$176,000 – $220,000 per year
Country
US
Work mode
On-site / unstated
First seen by hirly
10 Sept 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

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 .

Original posting on Handshake's site ↗

Listed on hirly, a job board. hirly is not the employer: Handshake is hiring for this role.

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