Software Product Pre Sales Engineer Senior Manager - FinCrime

Accenture•Miami, FL

11d•$112,900 - $271,000

About The Position

The Senior Manager, Pre-Sales supports complex software sales cycles by delivering product demonstrations, responding to technical and functional requirements, and developing reusable pre-sales assets. The role combines product expertise and client-facing skills to support pipeline conversion across direct client engagements, partner opportunities, and industry events. The position focuses on Fincrime OS, including KYC/CDD/EDD, AML alert investigation, sanctions and watchlist adjudication, case management, agent workflows, entity resolution, and regulatory reporting. The role designs and presents solution architectures and end-to-end demonstrations, explains AI agent behavior and model governance, assesses data and integration requirements, and scopes pilots and proofs of value. It also provides sizing input to the commercial team and shapes solutions for managed services, SaaS-style, and AI-as-a-Service deal models. The role works closely with sales, pre-sales, product, legal, delivery, partner, technical, risk, and compliance stakeholders. Travel may be required from 0–80%, depending on client and business needs. Accenture lists annual salary ranges that vary by location and offers a market-competitive benefits suite.

Requirements

At least 8 years of pre-sales, solution consulting, or technical sales support experience in enterprise software, including contributions to complex sales opportunities, RFP responses, and solution demonstrations.
At least 8 years of experience with enterprise software delivery models, such as SaaS, licensing, and managed services, and integration approaches.
At least 12 months of demonstrated pre-sales experience supporting AI-native software products built on LLMs, agentic workflows, or machine-learning platforms, with evidence of demonstrations delivered or RFP contributions.
At least 1 year of hands-on AI coding or development experience.
Bachelor's degree or equivalent, or at least 12 years of work experience; candidates with an associate's degree must have at least 6 years of work experience.
Deep functional knowledge of Fincrime OS across KYC/CDD/EDD, AML alert investigation, sanctions and watchlist adjudication, analyst workbenches, case management, rules, workflow orchestration, financial crime agents, and SAR and regulatory reporting support.
Working knowledge of fraud operations, including fraud-alert investigation, case handling, and connections between fraud and AML processes.
Ability to explain the distinction between financial crime agents, rules-based detection, and ML detection, including the role of deterministic rules and workflow and the traceability of agent findings to source data and documents.
Understanding of entity resolution and validation, ownership and control structures, and how entity data quality affects screening and investigations.
Ability to design and present deployment architecture integrating transaction monitoring and screening engines, onboarding and core banking systems, document management, external data sources, identity and single sign-on, and downstream case and reporting systems.
Understanding of file, API, and event-based data ingestion, including client-specific adapters that map formats into a canonical data model.
Familiarity with cloud-native AI architectures on a major cloud provider, including serverless and containerized compute, managed LLM inference, event streaming, environment isolation, observability, and data residency.
Experience engaging technical, risk, and compliance stakeholders, including financial crime technology, enterprise architecture, security, model risk, data, compliance operations, and third-party risk teams.
Familiarity with AI-agent model risk management, including SR 11-7 and PRA SS1/23 alignment, agent versioning and validation, independent challenge, ongoing monitoring, model cards, and per-decision explainability.
Ability to demonstrate agent quality using labeled historical cases, present recall and precision against an agreed recall-first quality bar, show evidence citations and decision rationale, and explain policy configuration, review, approval, and versioning.
Familiarity with financial crime agent data requirements, data-quality assessment, and data preparation before go-live.
Experience scoping financial crime operations pilots and proofs of value, including defining processes and case populations, agreeing holdout sets and success criteria, running parallel evaluations, and presenting results.
Experience shaping solution models for managed services, SaaS, and AI-as-a-Service, including operating models, analyst involvement, SLAs, capacity, platform scope, and client responsibilities.
Experience leading technical responses to RFPs, security questionnaires, and due-diligence reviews.
Experience presenting technical solutions to mid-level and C-suite stakeholders.
Strong written and verbal communication skills, including producing high-quality proposal content under time pressure.
Organized and detail-oriented, with the ability to manage multiple concurrent opportunities.
Self-motivated and resilient, with the ability to thrive in a fast-paced environment.

Nice To Haves

Hands-on experience configuring or building AI agents, including Python, prompt and agent configuration, building and running evaluation sets, and interpreting agent traces to explain behavior to clients.
AI certifications, such as Microsoft AI-900/AI-102, Google Cloud Professional ML Engineer, AWS Certified ML Specialty, or DeepLearning.AI specialisations.

Responsibilities

Support assigned opportunities through discovery, demonstrations, RFP responses, solution scoping, and proposal preparation.
Deliver tailored product demonstrations to client stakeholders and translate product features into business value.
Facilitate client workshops to identify requirements, validate solution fit, and shape the solution approach.
Prepare RFP, RFI, security-questionnaire, and due-diligence responses with product, legal, and delivery teams.
Support proofs of concept, document outcomes, and incorporate learnings into the pre-sales playbook.
Support channel and technology partners with product demonstrations, technical guidance, positioning, and additional pre-sales depth for partner-led opportunities.
Represent the business at industry events and trade shows, demonstrating products, engaging prospects and clients, and documenting leads and follow-up actions.
Develop and maintain reusable pre-sales materials, including demo scripts, solution blueprints, proposal modules, competitive battle cards, and ROI templates.
Keep current on product updates, competitors, and industry trends, and share insights with the sales team.
Contribute to onboarding new team members on product and solution knowledge.
Work with the sales lead and AD Pre-Sales to align opportunity strategy and solution approach.
Maintain accurate records of pre-sales activities and solution configurations, and support pipeline reporting.
Participate in win/loss reviews and apply learnings to improve proposals and demonstrations.
Demonstrate Fincrime OS across representative end-to-end financial crime scenarios tailored to each client's products, channels, and detection estate.
Design and present deployment architectures, including integrations, ingestion patterns, cloud-native AI components, identity and access, and downstream case and reporting systems.
Explain agent behavior, quality, evidence citations, decision rationale, policy controls, and model-risk practices to clients and stakeholders.
Scope pilots and proofs of value, establish case populations and success criteria, support parallel runs, and present results to operations, compliance, and model-risk stakeholders.
Shape solutions for outcome-based managed services, SaaS-style, and AI-as-a-Service deal models, and provide sizing input to the commercial team.
Lead technical responses to RFPs, security questionnaires, and due-diligence reviews covering architecture, security, data residency, resilience, outsourcing, and model governance.