Forward Deployed Engineer, AI

ClarityPay, New York City

The role

ClarityPay is seeking Forward Deployed Engineers to embed with the teams that run the company and turn how they work into dependable, AI-native systems. You will sit with process owners in finance, credit and portfolio risk, servicing and collections, and operations; scope the problem with them before building; ship agents, controls and automations into production; and stay through adoption as the named secondary owner of the process. You will join the Data & AI organization, working alongside engineers in New York and India on a shared platform, and alongside Product and Engineering you will build external-facing AI solutions for merchants and partners on the ClarityPay platform.

All jobs

Forward Deployed Engineer, AI

ClarityPay, New York City

Posted pay

$145K–$195K

a year

Compared with similar jobs

This base pay is below the median for software engineering jobs in New York with no level in the job title.

Median: $200K a year
Other jobs in the group: 1,200

We compare the middle of each posted range. This is base pay as posted. The group does not include this job.

Location: New York City
Work type: Hybrid
Level: Not given
Experience: 2+ years
Skills in the job text: Python
SQL
A/B testing
ClickHouse
Databricks
Posted: 27 days ago
Last check: 9 h ago
Job type: Software engineering, ML / AI engineering

Apply on the ClarityPay site Sign in to save

The ClarityPay site opens in a new tab.

ClarityPay

Open tech jobs: 3
With posted pay: 67%

About ClarityPay: funding, hiring and pay

ClarityPay

About ClarityPay: funding, hiring and pay

Check my fit

Compare your résumé with this job. See where you match, what is missing and which lines to change.

The role

What you will do

Key Responsibilities

Embed with process owners to map how the work actually runs, scope the problem with them before building, and agree success criteria and a baseline up front.
Own delivery end to end – discovery, technical scoping, system design, build and production rollout — and stay through adoption as the named secondary owner of the process.
Choose the simplest dependable solution: simplify or remove a step before automating it, then pick a scheduled job, a triggered job, or a bounded agent with a defined mandate, action set, escalation owner and pause conditions.
Write evaluations for everything you ship: prove the output is correct before a team depends on it, and re-check it as models, data and processes change.
Instrument what you build, and the processes around it, with detective (“day-zero”) controls — thresholds, exception inventories and alerting, each with an action path and a named owner — so a breach surfaces the same day, not at month-end.
Build external-facing AI solutions for merchants and partners with Product and Engineering; anything external ships through Engineering’s review and deployment standards.
Codify reusable patterns, evals and harness standards so the second deployment is faster than the first; prefer reusable capabilities over one agent per task, and bring field signal back to the platform roadmap.
Work inside ClarityPay’s controls for AI — evaluate before exposure, bound the exposure, keep a person at the gate — and propose where a human must review, where automation may act unattended, and what gets logged.
Own the value case: set impact hypotheses and baselines, measure before and after, and report to executives on business impact, total effort saved (including review and maintenance), control quality and reuse.
Continually promote and apply ClarityPay values; be a role model of trust and integrity.

What Success Looks Like in Your First 6–12 Months

Desktop and spreadsheet-based reporting processes are inventoried, baselined and moved onto AI agentic systems running on governed data, with a person at the gate where judgment is needed.
Recurring performance reporting – portfolio, collections, servicing and finance — is produced by agents from governed metrics rather than manual pulls, on time and traceable to source.
Day-zero controls are live in your first processes, each with a threshold, an action path and a named owner, so breaches surface the same day.
The effort returned is measured against the baseline, net of review, exceptions and maintenance, and reported to executives.
At least one external-facing solution for merchants or partners is in production and adopted.
The patterns, evals and agent-harness standards you built are reused by the next deployment.

Forward Deployed Engineer, AI

The role

Forward Deployed Engineer, AI

The role

What you will do

Key Responsibilities

What Success Looks Like in Your First 6–12 Months

What you need

Nice to have

How You’ll Know This Role Is Right for You

Pay and benefits

About ClarityPay

Similar jobs at other companies

Lead Forward Deployed Engineer (AI)

Forward Deployed Engineer

Forward Deployed Engineer

Forward Deployed Engineer (FDE)

Forward-Deployed AI Engineer

Forward Deployed Engineer

ClarityPay

Compared with similar jobs