Gramener
Website:
gramener.com
Job details:
We are looking for a delivery leader who has taken AI programs all the way into production, at organisations where the outcome mattered and was measured. You will own how AI solutions are planned, built and delivered across our client programs, working with engineering, architecture, data science and product teams on one side, and with client sponsors and senior business stakeholders on the other.
What separates this from a standard program management role is how much AI delivery experience it needs. You should understand how these solutions are built well enough to see risks before they show up in a status report, ask an engineering team the right questions when a date starts slipping, and push back with credibility when scope or quality is under pressure.
WHAT YOU WILL D
OPrograms and deliver
- yOwn delivery for AI programs end to end, from scoping and planning through to production and the first months of live running
- .Set up the program structure, governance, milestone plan and review schedule across several parallel workstreams
- .Manage risk actively. Raise problems early and make the decisions the team needs to keep moving
- .Keep scope honest, so that what gets built is what was agreed, and what was agreed still solves the business problem
- .Hold the quality bar on everything the team puts out, whether that is a model going live or a steering committee update
- .Own status reporting, risk and issue logs, change control and financial tracking, and report honestly against the value the program was meant to deliver
.
Clients and stakeholde
- rsAct as the senior point of contact for client sponsors and executives on the programs you lea
- d.Run steering committees and executive reviews with the right level of detail for the audience, and put the real decisions on the tabl
- e.Keep stakeholders informed often enough that a status update never comes as a surpris
- e.Build relationships with client and internal leadership that last beyond the current progra
m.
Technical judgem
- entUnderstand the full AI delivery lifecycle: data preparation, model development and evaluation, integration with enterprise systems, deployment, and monitoring once the solution is li
- ve.Work with architects, data scientists and engineering leads to sanity check the delivery approach and catch technical risk ear
- ly.Hold your own in conversations about GenAI platform choices, LLM based applications, model governance and responsible AI, without needing to be the hands-on expe
- rt.Know enough about cloud delivery, AWS in particular, to ask the right questions about how AI workloads will run and what they will co
- st.Make sure programs meet our compliance and responsible AI standards for transparency, auditability and human revi
ew.
- TeamLead delivery teams of project managers, business analysts, solution architects, data engineers and data scienti
- sts.Set clear standards for delivery, documentation, testing and communication, and hold the team to t
- hem.Stay close to the work without taking over from the people doing
- it.Spot skill gaps in the team and close them through hiring, training or partn
- ers.Build playbooks and templates that make the next program easier to run than the last
one.
WHAT WE ARE LOOKIN
G FOREsse
- ntial16 to 20 years in technology delivery, with a substantial part of it leading AI, data or automation programs for large organisat
- ions.A track record of taking AI programs from idea to production, owning the outcome rather than running someone else's
- plan.Experience leading teams that cut across engineering, data science, architecture and business stakeholders on complex prog
- rams.A background in consulting, systems integration or enterprise technology, where managing the client relationship was part of the
- job.Experience managing program budgets, staffing and delivery risk across several initiatives at
- once.Working knowledge of how AI solutions are built and kept running: data engineering, model development, integration, production support, and GenAI patterns such as LLM based applicat
- ions.Working knowledge of cloud platforms, AWS preferred, and how AI workloads are usually set up and oper
- ated.Strong executive communication. Comfortable running steering committees, presenting to senior leadership, and explaining technical work to business audiences and the rev
- erse.Experience handling difficult conversations on scope, quality, timelines and expectations, with clients and intern
ally.
Good t
- o haveAI delivery experience in regulated industries such as financial services, healthcare, media or public s
- ector.Experience in or alongside an AI Center of Excellence or an enterprise AI platform
- team.An MBA or equivalent postgraduate qualification, or certifications such as PMP, MSP or an AWS crede
ntial.
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