Technical Program Manager

MaaS by CodeSM; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

CodeSM is hiring a Technical Program Manager to own both ends of the enterprise AI delivery pipeline. You will scope client work, convert it into specifications and prototypes, and drive delivery from prototype to release, working with the Head of Product and CTO.

You will lead discovery, write user stories and acceptance criteria, estimate work with engineering, and manage scope changes. Cross-team coordination across AI engineering, frontend, QA, and client support is essential.

Qualifications

• Business analysis capability to elicit requirements and write specs for engineering.
• Ability to prototype and wireframe concepts with clients using AI tools.
• Proven delivery of technical software projects in a product/engineering setting.
• Comfortable reading API docs, understanding integrations and data flows.
• Strong client-facing communication and stakeholder management.
• Experience coordinating cross-team delivery and managing scope.

Responsibilities

• Discovery with clients to map current processes and surface needs.
• Write user stories, acceptance criteria and scope documents for engineering.
• Estimate work with engineering to size scope before client commitment.
• Manage scope changes, price impact and client decisions.
• Create wireframes and prototypes to test scope with clients.
• Run delivery cadence with sprint planning and milestone tracking.
• Coordinate across AI engineering, frontend, QA and client support.
• Lead UAT sessions and ensure sign-off with clients.

Skills

Business analysis capability

Prototyping

Delivery track record

Technical fluency

Enthusiasm for AI

Project hygiene

Client confidence

Self direction

Tools

CRM platforms

Marketing automation platforms

AI tools

APIs & data flows

Job description

CodeSM builds and delivers AI software for financial services. The Product Group covers two divisions. Applied AI ships enterprise AI implementations for banks, wealth managers and fintech platforms. The software portfolio covers Marketing AI Suite, Research AI Suite and GoCRM.

We are hiring a Technical Program Manager to own both ends of that pipeline, which currently sit with the Head of Product and the CTO. You will scope new client work with clients, turn it into a specification and a prototype engineering can build from, then run the delivery through to release.

About the role

CodeSM builds and delivers AI software for financial services. The Product Group covers two divisions. Applied AI ships enterprise AI implementations for banks, wealth managers and fintech platforms. The software portfolio covers Marketing AI Suite, Research AI Suite and GoCRM.

We are hiring a Technical Program Manager to own both ends of that pipeline, which currently sit with the Head of Product and the CTO. You will scope new client work with clients, turn it into a specification and a prototype engineering can build from, then run the delivery through to release.

What you will own

Scoping and business analysis

• Discovery with clients. Run the sessions, map the current process, and surface what the client actually needs rather than what they first asked for.
• Business analysis. Process mapping, data flows, user journeys, and the commercial case for what gets built.
• Written specification. User stories, acceptance criteria and scope documents that engineering can build from without a second round of questions.
• Estimation support. Working with engineering to size the work honestly before it is committed to a client.
• Change control. When scope moves, you catch it, price the impact, and put the decision in front of the client rather than absorbing it.
  

Prototyping

• Wireframes and clickable mockups used to pressure test scope with clients before a line of production code is written.
• Fast, throwaway AI assisted prototypes to prove a concept, de risk an approach, or make an abstract requirement concrete in a client conversation.
• Working alongside engineering to turn a validated prototype into a build plan, not to hand over a picture and walk away.
  

Delivery execution

• Sprint structure and delivery cadence across all active product work, in both divisions.
• Granular project plans. Every implementation broken down into trackable milestones, owners and dates.
• Backlog hygiene. Nothing stale, nothing ambiguous, everything prioritised and estimated.
• Acceptance validation. Testing delivered work against the acceptance criteria and the original client use case before it reaches the client. QA covers whether it works. You cover whether it does the job the client asked for.
• UAT with client stakeholders. Running the sessions, capturing feedback, and getting fixes triaged and closed out before sign off.
• Hours, budget and timeline tracking across the portfolio, with overruns flagged early rather than explained late.
• Cross team dependency management across AI engineering, front end, QA and client support, so work does not collide.
• A lightweight standup and async check in rhythm, plus the agenda and follow ups for the weekly product sync.
  

Client and reporting

• Milestone updates, timeline changes and recurring delivery reporting into client stakeholders.
• A weekly portfolio view for leadership. The state of every build in five minutes of reading.
  

Two modes of work

This is one role with two modes rather than a split between two jobs, and the balance shifts with the portfolio.

Applied AI implementations

Scoping and program management for enterprise AI builds with financial services clients. This is where the discovery, specification and prototyping work concentrates, alongside heavier coordination, tighter client scrutiny and real budgets to protect.

Software portfolio

Release cadence, roadmap hygiene and feature specification across Marketing AI Suite, Research AI Suite, GoCRM and internal platforms. More rhythm than rescue, the discipline has to be just as consistent.

What we are looking for

• Business analysis capability. Demonstrable experience eliciting requirements from non technical stakeholders and turning them into specifications engineering can build from.
• Prototyping. Comfortable producing wireframes and clickable mockups, and using AI tools to stand up a working prototype quickly.
• Delivery track record. Proven delivery of technical software projects in a product or engineering environment, ideally several running concurrently.
• Technical fluency. Comfortable reading API documentation, understanding integrations and data flows, and holding your own in a conversation with engineers without needing everything translated first.
• Enthusiasm for AI. You use AI tools daily, you follow where the field is going, and you are excited to deliver AI products rather than cautious about them.
• Project hygiene. Plans, owners, dates, risks, actions. You are the person who notices the thing that has quietly stopped moving.
• Client confidence. You can run a scoping workshop and a difficult delivery status call with an enterprise client, hold the line on scope and timeline, and keep the relationship warm while you do it.
• Self direction. We are a lean team. You will not inherit a process. You will build one and then run it.
  

A plus, not a requirement

• Experience in fintech or financial services, particularly wealth management, banking or capital markets.
• Familiarity with enterprise delivery constraints. Security review, data handling and procurement in a regulated environment.
• Working knowledge of CRM and marketing automation platforms.
• Formal delivery training such as Agile, Scrum or PRINCE2. Welcome, but never a substitute for evidence of shipping.
  

What good looks like at 90 days

• One new piece of client work scoped, specified and prototyped end to end.
• Every active implementation sitting on a single tracked plan with owners and dates.
• The delivery cadence running without needing to be prompted.
• Weekly portfolio reporting that leadership reads rather than chases, and at least one recurring client report moved off the Head of Product's desk.
  

How we work

• Async by default and written first. One standing weekly sync, with short recorded walkthroughs in place of meetings that do not need to be calls.
• Regular client calls. Discovery sessions, delivery status updates and milestone reviews with enterprise stakeholders are a routine part of the week, often across timezones.
• Time and tasks tracked against client billable work, so budgets and capacity stay visible.
• Small team, direct communication, no layers to route through.