Fractional Chief AI Officer for Capital Markets

01

Finance is native, not a vertical I learned for the pitch.

The category is full of AI generalists who treat "financial services" as one more industry slide. They have never priced a bond, run a P&L, or shipped to a regulator. I have. I spent seven years building real-time pricing, P&L, and risk systems on a $85B mortgage desk, then ran data and AI products at Disney Streaming scale.

That order matters. I build agentic systems that work inside the constraints a trading desk, a risk team, and an allocator actually operate under, because I have sat in those seats.

"Most agents fail because the data underneath them was never ready, and because whoever built them never understood the business they were built for."

02

Built for a specific buyer.

A fractional CAIO is only useful when the fit is exact. This is who the engagement is designed for, and who it is not.

A strong fit if you are

A trading desk, risk function, or asset manager moving AI from scattered pilots to systems people rely on.
A capital-markets fintech that needs credible AI leadership your buyers and regulators will trust.
A firm that wants to own its AI capability, not rent it from a vendor indefinitely.
A leadership team that needs board-ready AI governance without a $400K full-time hire.

Probably not a fit if

You want a generic chatbot bolted onto a website with no governance behind it.
Your priority is the cheapest possible build over a system that survives an audit.
You need a hands-off slide deck rather than an operator embedded in the work.
Your domain is outside finance, where my desk experience stops being the differentiator.

03

Why AI stalls inside financial firms.

/01

Pilots that never leave the lab

A demo impresses the offsite, then dies on contact with real positions, real latency, and real accountability. There was no operating model to carry it into production.

/02

A data layer that was never ready

Agents are only as good as the foundations beneath them. Lineage, quality, and governance get skipped, and the system fails quietly where it costs the most.

/03

Vendors who don't speak desk

The people selling AI rarely know what an axe, an RFQ, or a model-risk regime is. Their tools fight your constraints instead of working within them.

04

What I own as your fractional CAIO.

Embedded executive leadership, not a project that ships and disappears. I sit with your team, carry the strategic thread across quarters, and leave you with capability you keep.

01

AI strategy and roadmap

Translate board-level pressure into a sequenced, ROI-anchored roadmap tied to your business: which use cases, in what order, against which P&L or risk outcome.

02

Governance and model risk

Stand up governance the firm can defend: acceptable-use policy, model-risk controls, audit trails, and review cadence aligned to your regulatory surface.

03

Build oversight, systems you own

Architect and oversee the agentic systems themselves, on your infrastructure, inside your perimeter, so the capability stays with your team instead of a vendor.

04

Vendor and build evaluation

Independent, conflict-free assessment of buy-versus-build and vendor selection from someone with no referral fees and a markets background to judge fit.

05

Board and leadership reporting

Clear, credible updates that an investment committee or board will actually trust: progress, governance health, and where the next dollar should go.

06

Team enablement

Build internal AI literacy and capability so the firm grows past needing me, which is the point of a fractional engagement done well.

05

The track record this is built on.

Proof that does not survive a find-and-replace. Each line is a seat I actually sat in.

Capital Markets

7 years on Citi's MBS trading desk
Real-time pricing, P&L, and risk systems
$85B book across 13 trading desks
OCC regulatory delivery
Hedge-fund risk work at StepStone
Master of Finance · CFA Level I

Data & AI at Scale

Data and AI products at Disney Streaming
PB-scale viewership and subscriber data
60M+ subscribers · 160 countries
Forecasting and content analytics in production
Production multi-agent orchestration on AWS Bedrock
The full data foundation agents stand on

Regulated by Design

Fluent in the EU AI Act
DORA operational-resilience regime
Financial model-risk frameworks
Architecture stays outside the data perimeter
Controls, guardrails, observability, human-in-loop
Built for audit, not just for demo

06

And I build it myself.

Strategy backed by hands on the system. The agentic and data layers I design, oversee, and can build directly. The build practice lives at applied-agents.ai.

Agentic Systems

Multi-agent orchestration, tool use, MCP
RAG, knowledge bases, retrieval strategy
Evals, guardrails, observability
Human-in-the-loop control

Data Foundations

Strategy, governance, quality, lineage
Lakes, warehouses, lakehouse
Pipelines and orchestration
Dimensional modeling, analytics, BI

Stack

AWS Bedrock · AgentCore
LangSmith · Step Functions · Lambda
Claude Code
Your cloud, your perimeter

07

How we work together.

Three ways in, scoped to where you are. Every engagement starts with a working call to confirm fit before anything is signed.

Entry point

Strategy Sprint

A time-boxed engagement to produce a sequenced AI roadmap, a governance baseline, and a clear buy-versus-build call. The fastest way to turn pressure into a plan.

FormatProject

Duration4–6 weeks

OutputRoadmap + charter

Flagship

Embedded Fractional CAIO

Ongoing executive ownership of your AI agenda: roadmap, governance, build oversight, vendor decisions, and board reporting. Embedded in your leadership team across quarters.

FormatRetainer

CadencePart-time exec

Min term3 months

Targeted

Advisory & Build

Defined-scope work: a specific agentic system to architect and ship, a model-risk review, a vendor evaluation, or standing advisory presence for an internal team.

FormatProject / advisory

ScopeDefined

Hands-onYes

08

Questions worth answering up front.

How is a fractional CAIO different from a consultant?

A consultant delivers a project and leaves. A fractional CAIO is embedded in your leadership team over time, owns the AI roadmap, attends the meetings, makes ongoing vendor and build decisions, and is accountable for outcomes across quarters. The goal is to build capability you keep, not a dependency.

Does our data ever leave our environment?

No. The architecture is designed to stay inside your data perimeter. Systems run on your infrastructure and your cloud, which is non-negotiable for trading, risk, and allocator data and is built in from the first design decision rather than bolted on.

Why finance specifically?

Because the differentiator is real domain experience, not a vertical learned for a pitch. Seven years on a mortgage desk and hedge-fund risk work mean I know what a desk, a risk team, and an allocator actually do, and I build agents that work within those constraints. Outside finance, that edge stops applying, which is why this page commits to it.

How much time does an engagement involve?

It depends on scope and maturity. A flagship embedded engagement is part-time executive presence on a retainer with a three-month minimum. Sprints and defined-scope advisory are sized to the work. We confirm the right shape on the first call before anything is committed.

What does pricing look like?

Pricing is scoped to the engagement and discussed on the working call, once the fit and shape are clear. Every engagement is bespoke to your firm's regulatory surface and maturity, so a fixed menu would misrepresent the work.

Who you'd be working with

Camille Lambert

For seven years I built the pricing, P&L, and risk systems traders actually used on Citi's mortgage desk, then led data and AI products at Disney Streaming scale. This practice is where those two halves meet: executive AI leadership for capital markets and asset management firms, plus the agentic systems — built through my firm, Applied Agents — to back the strategy up.

I take on a small number of firms at a time, embedded closely enough to be accountable for what actually ships.

Master of Finance · CFA Level I · LA-based, available nationally

The rare AI leader who already knows what your desk does.