Role Description
Mission -----------
Faros advances those who build. Our platform brings all engineering data into a single pane of glass, giving teams unprecedented visibility and insights across their software development lifecycle. This deep operational context supports engineering leaders today, and is increasingly essential as AI agents begin to operate within real software delivery environments. Our mission: to forge a world where engineering moves at the speed of ideas.
About the Role ------------------
We are seeking a Forward Deployed Engineer to drive high-impact outcomes for our customers by delivering technical solutions, uncovering engineering challenges, and helping shape the future of the Faros platform. We're looking for a curious, technically sharp new graduate to join our Forward Deployed Engineering team. In this role, you'll work directly with customers helping them get real, measurable value out of the Faros platform.
This isn't a typical entry-level job. You'll own real work: building integrations, configuring dashboards, writing data transformations, and solving novel technical problems alongside experienced FDEs and Account Executives. You'll be in front of customers early and expected to iterate fast.
We're specifically looking for people who are already using AI tools in how they build and think, and who are excited about working in an environment where the norms are still being written.
Responsibilities --------------------
Working with Customers
- Work directly with customers to understand their engineering workflows and technical pain points.
- Assist in and eventually lead technical evaluations and POCs of the Faros platform.
- Communicate findings and solutions clearly to both technical and non-technical stakeholders.
Hands-On Technical Delivery
- Build and configure custom integrations, dashboards, and data pipelines to solve customer problems.
- Work across the stack - APIs, data infrastructure, visualization - with guidance from senior FDEs.
- Iterate quickly based on customer feedback and real-world usage.
- Use AI coding assistants and modern tooling as a core part of how you build.
Learning & Product Influence
- Identify patterns across customer engagements and bring insights back to the product team.
- Participate in roadmap discussions with grounded, field-tested observations.
- Grow rapidly: the expectation is that you'll take on increasing ownership over time.
What We Care About ----------------------
- Living by our values over avoiding conflict - We speak honestly, act transparently, and choose the hard right over the easy wrong.
- Transformation over predictability - We pursue work that meaningfully changes what's possible, even when the path is uncertain.
- Intensity over comfort - We bring energy and urgency to the work, especially when it's hard.
- Craftsmanship over throughput - We take pride in how things are built. Quality and coherence matter.
- Ownership over process - We act like founders. If something is broken, we fix it without waiting for permission.
Required Qualifications ---------------------------
- Bachelor or Master's degree in Computer Science, Engineering, or a related technical field
- Programming fundamentals in at least one language (Python, JavaScript, etc.).
- AI-savviness: you already use AI coding assistants, LLM APIs, or AI-powered tools as part of how you build.
What We'll Evaluate -----------------------
- Communication - Can you explain a technical concept clearly to someone who isn't an engineer?
- Ambiguity tolerance - Can you take a vague problem and make it concrete?
- Customer orientation - Do you genuinely care about the person on the other side of the work, not just the technical puzzle?
Compensation Range: $100K - $150K
About Forward Deployed Engineering
Forward Deployed Engineers are embedded directly with customers to build custom solutions, integrate products into existing infrastructure, and bridge the gap between product engineering and customer success. The role combines deep technical skills with the ability to operate in client environments and translate business requirements into working software.
Originally pioneered by Palantir, the FDE model has spread across AI, enterprise SaaS, and cloud infrastructure companies. FDEs write production code, architect integrations, train customer teams, and feed product insights back to the core engineering organization. At companies like OpenAI, Salesforce, and Databricks, FDE teams are treated as elite engineering units that can ship custom solutions in days rather than quarters.
Typical FDE stack: Python, TypeScript, SQL, REST/GraphQL APIs, cloud platforms (AWS/GCP/Azure), and increasingly LLM APIs and AI orchestration frameworks. Strong communication and the ability to context-switch between technical and business conversations are as important as coding ability.
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