Forward Deployed Engineer

Sixtyfour AI Inc.; San Francisco (CA); On-site; USD 150,000 - 190,000; Full time

Benefits offered by this job

Unlimited PTO

Lunch on us in the office

Monthly gym membership reimbursement

Monthly AI tools/productivity reimb.

401k with company match

Health / Dental / Vision

Flexible working hours

Job summary

Sixtyfour AI Inc. is seeking a Forward Deployed Engineer to join our SF-based team. You will work between customers and our core codebase, shipping platform features and deploying solutions inside customer environments.

You will design robust APIs, build agent workflows with LLM-powered components, and own end-to-end delivery from scoping to production use. This role demands strong engineering, customer-facing skills, and high ownership.

Qualifications

• 3–7 years of professional software engineering experience.
• Strong backend development and API design; Python and JavaScript/TypeScript.
• Experience running systems in production with observability, scaling, and on-call ownership.
• Real comfort in front of customers: technical discovery conversations and stakeholder management.
• Comfortable in a fast-paced, early-stage environment with high ownership and ambiguity.

Responsibilities

• Build production code for the core platform and APIs.
• Design robust, scalable APIs powering product and field deployments.
• Build and productionize agent workflows and LLM-powered systems, with evals and guardrails.
• Operate and monitor pipelines in customer environments, including SRE tasks.

Skills

Software engineering

Backend development

API design

Python

JavaScript/TypeScript

Observability

On-call ownership

Customer-facing skills

Tools

Kubernetes

Temporal

Apache Spark

AWS

OpenRouter

Next.js

Vercel

Stripe

Job description

About Sixtyfour

Sixtyfour helps teams understand the people, companies, and entities they interact with, with a primary focus on Compliance (AML/KYB), Trust & Safety, Cybersecurity, and Investigations. Our platform combines agents, LLMs, and large-scale data infrastructure to surface information essential for critical decision-making.

The Role

Forward Deployed Engineers sit between our customers and our codebase. Some days you'll be in a working session with a compliance team learning how they actually run an alert to disposition; other days you'll be in our repos shipping the pipeline that makes that workflow ten times faster.

Roughly half of this job is building the core product alongside the rest of engineering. The other half is deploying, extending, and tuning it inside real customer environments. This is not a support or solutions role, you'll be held to the same engineering bar as everyone else on the team. The difference is that you will be the engineer that customers go to first, and the one who sees their problems firsthand.

What You'll Do

Build

• Ship production code in the core platform alongside the rest of engineering including backend services, APIs, data pipelines, search
• Design robust, well-architected APIs that power both our product and the integrations you deploy in the field
• Build and productionize agent workflows and LLM-powered systems, including evals, guardrails, and cost/latency tuning
• Operate what you build: instrumentation, observability, and SRE work when a pipeline breaks in a customer's environment at an inconvenient hour

Deploy

• Embed with customers to learn their workflows, data, and constraints directly rather than through a requirements doc
• Own technical delivery end to end: scoping, data onboarding, integration, deployment into their infrastructure, and the first weeks of production use
• Bridge the current platform to customers with custom connectors, enrichment steps, migration scripts, internal tooling, etc
• Be the credible technical voice in the room, whether you're talking to an analyst who has never seen an API or to their staff engineer who is skeptical of yours

Close the loop

• Distinguish one-offs from the emerging pattern, and push patterns back into the core platform
• Bring the field back to engineering, product, and leadership as evidence for what to prioritize
• Set honest expectations with customers about what's shipping and when, and hold the line when the answer is "not soon"
• Leave behind runbooks, docs, and internal write-ups so the next deployment is faster than the last

What We're Looking For

• 3–7 years of professional software engineering experience
• Strong fundamentals: you can drop into an unfamiliar codebase, debug a production incident, design a clean API, and reason clearly about data models and failure modes
• Strong backend development and API design experience; proficiency in Python and JavaScript/TypeScript
• Experience running systems in production with observability, scaling, and on-call ownership
• Real comfort in front of customers: you can run a technical discovery conversation, push back on a stakeholder without damaging the relationship, and turn a vague business problem into a scoped technical one
• Judgment about what to generalize and what to leave bespoke, and the discipline to advocate for the former
• Comfortable in a fast-paced, early-stage environment with high ownership and ambiguity
• Willing to be based in or relocate to the San Francisco Bay Area, with occasional travel to customer sites

Our Stack

We'd like to see depth in several of these and a track record of picking up the rest quickly:

Kubernetes · Temporal · Apache Spark · AWS (Glue, EC2, CloudWatch, Data Prepper) · OpenRouter · Next.js and Vercel · Stripe

Nice to Have

• Experience developing agents or building evals for LLM systems
• Prior forward-deployed, solutions architecture, or technical account engineering experience at a product company
• Domain exposure to compliance/AML/KYB, Trust & Safety, fraud, cybersecurity, or investigations
• Experience deploying software into regulated or security-sensitive environments (SOC 2, data residency, VPC or on-prem installs)
• Experience building developer-facing products or platforms (APIs, SDKs, dev tools)
• Prior startup experience, ideally at a similar stage
• Experience working in an AI company

Benefits

• Unlimited PTO
• Lunch on us in the office
• Monthly gym membership reimbursement
• Monthly AI tools/productivity reimbursement
• 401k with company match
• Health / Dental / Vision
• Flexible working hours