Paid AML/Compliance Industry Reviewer and Design Partner
Paid AML/Compliance Industry Reviewer and Design Partner
We are developing SDS Intelligence, an early-stage governance-intelligence and decision-support product for professionals working with policies, contracts, controls, approvals, exceptions, and governance documentation.
We are seeking a U.S.-based AML, compliance, financial-crime, risk, audit, or governance professional to participate as a paid industry reviewer and design partner.
We are not looking for favorable feedback. We want candid professional criticism that helps us identify where the product is useful, unclear, incomplete, or potentially misleading.
This is a paid engagement lasting approximately 2 weeks and requiring about 3–5 total hours.
Scope of work
Participate in a 45–60 minute expert discovery interview about your experience reviewing AML, compliance, risk, audit, regulatory, policy, control, or governance materials.
Test an early SDS workflow using SDS-provided, public, or synthetic sample materials only.
The review may include:
evidence-linked findings
governance findings
reviewer decisions and adjudication
amendment or change-impact review
review cases
traceability and auditability
organizational decision-history workflows
Participate in a final review discussion and provide short written feedback covering:
whether findings are understandable and professionally useful
false positives, false negatives, and missing context
where supporting evidence is insufficient
workflow gaps and usability problems
whether findings are traceable, reviewable, and auditable
situations where a human reviewer should reject, modify, or escalate a result
important edge cases or exceptions the system should handle better
recommendations for improving the product before broader professional use
Payment
$500 fixed price through Upwork
$100 — expert discovery interview
$150 — structured SDS workflow testing
$250 — adjudication review, edge cases, final discussion, and written recommendations
Ideal experience
Relevant backgrounds may include:
AML/BSA
financial-crime compliance
banking compliance
internal audit
enterprise or operational risk
regulatory compliance
regulatory counsel
investigations
model risk
fintech compliance
governance and controls review
Experience working with U.S. banks, financial institutions, fintechs, consulting firms, or other regulated financial-services organizations is especially relevant.
Important confidentiality and data restrictions
Only SDS-provided, public, or synthetic materials may be used.
Please do not provide or upload:
SARs or SAR-related information
customer or employee PII
confidential employer information
proprietary bank policies or contracts
restricted regulatory information
customer or client materials
credentials or access to employer systems
You should also confirm that participating in this independent consulting engagement does not violate any obligations to your current or former employer.
Some SDS materials and methodologies are proprietary. Additional confidentiality terms may apply before access to non-public product materials is provided.
SDS is currently an early-stage research and decision-support product. It does not make autonomous compliance decisions, determine whether misconduct occurred, rank financial institutions, or claim production readiness.
You are being compensated for your professional time, independent judgment, and candid critical feedback, regardless of whether your conclusions are positive or negative.
To apply, please include:
Your relevant professional background
Your primary area of expertise
One example of reviewing policy, contract, control, exception, approval, or governance language
Your availability during the next two weeks
Confirmation that you can commit approximately 3–5 hours
Confirmation that you accept the $500 milestone-based fixed price
Confirmation that you can participate without using or disclosing confidential employer, customer, or client information
Confirmation that you are comfortable providing critical feedback, including identifying errors, edge cases, and situations where you would reject or override a system-generated finding