The posting
Software engineering is where AI is changing work fastest. Almost every developer now uses AI coding tools, yet only a minority of engineering organizations see meaningful gains from them. The AWS AI Engineering team exists to close that gap. We help AWS customers systematically build better software with AI, and we aspire to be the team builders worldwide turn to when they want to do exactly that.
This is a big opportunity to have impact. You will join at the point where AI-native development is moving from early adopters to the enterprise, working with some of the largest organizations in EMEA as they change how they build software.
As our Senior Technical Customer Solutions Manager, you will be the coordination hub for every AI engagement routed to the team across EMEA: qualifying inbound requests, assigning owners, keeping engagements moving from first contact to launch, and being the single point of contact that account teams and customers rely on for status. Your work does not end when a workshop is delivered: you own what happens next, making sure the customer turns what they learned into lasting change in how they build software. You will apply your program management expertise and technical fluency so that our AI Engineers can spend their time building and delivering.
Key job responsibilities You will work with customers, account teams, solutions architects, AI engineers, partners and a broad community of AWS practitioners on some of the most challenging AI adoption problems today. You will: - Own intake: qualify new requests, assess each customer's readiness and make sure every engagement has a named owner. - Drive engagements end to end as the single point of contact for customers and account teams on progress, risks and outcomes. - Meet customer executives and engineering leaders to agree business outcomes, and stay with the customer after the workshop until those outcomes are achieved. - Run the team's operating rhythm and own its operational metrics. - Reinvent how the team works with AI. You will not manage engagements through spreadsheets and status boards; you will use AI agents and automation to take manual work out of intake, staffing and follow-up, so every engagement takes less effort than the last. - Stay hands-on: run demos and immersion days, and join workshops alongside practitioners. Travel within EMEA may be required up to 25% of the time.
A day in the life You start the day reviewing new requests with an AI engineer and deciding the right path for each. Later you meet a customer CTO to agree what success looks like after their workshop, and follow up with an account team whose customer's adoption has stalled. You lead the team's weekly planning, and in between you improve one of the agents that handles routine follow-up, so there is less to chase next week.
About the team Our flagship program is AI-DLC, the open-source, AI-native software development lifecycle that we created and continue to evolve with customers. We also lead AI-DLC Discovery, which helps product and business stakeholders decide what to build now that the time and cost of building have fundamentally changed, alongside offerings that give AI agents a deep understanding of large codebases and step customers towards autonomous software delivery. We work from first principles and anchor everything on customer outcomes: measurable, lasting improvements in speed, quality and economics.
AI moves fast, and so do we. Our offerings evolve as the technology does, and you will thrive here if you enjoy adapting quickly and are comfortable with ambiguity.
- Experience leading large-scale, technical or engineering programs with a proven record of thought leadership, business case development, realizing customer benefits, and successful program completion - Experience in enterprise IT, either as a vendor, consultant or have prior experience working with or managing technical programs - Experience in customer-facing work, engaging with customer executives, technologists or partners to solve business problems with advanced technologies - Experience leading technical and non-technical transformation project teams with a proven ability to work across broad functional teams
- AWS or other cloud certification - Knowledge of the software development/engineering lifecycle from conception to delivery or IT lifecycle - Experience implementing cloud services including migrations and modernization projects or equivalent - Familiarity with the AI ecosystem: foundation models and the providers behind them, agent frameworks, coding assistants and the tooling customers use to build AI applications, and how enterprises move AI from experimentation to production - Experience with pipeline management, customer satisfaction tracking and business review reporting - Fluency in English, and an additional European language is an advantage
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