What You'll Own
Set the vision, strategy and roadmap for data, analytics, AI and product engineering, and connect it to the outcomes clients care about
Lead the organization through a layer of team leads across data engineering, analytics, machine learning, generative AI and application development, with clear ownership and accountability
Run production data, reporting and application services to agreed service levels, with strong operational discipline around monitoring, incident management and data quality
Direct the design and delivery of new solutions, from data platforms and dashboards to machine learning models, generative AI agents and full-stack applications, taking them from idea to production and adoption
Own the technical architecture and engineering standards across the organization, including data modeling, API design, security, CI/CD, and architecture decision records
Set the standard for how AI is built and operated, covering evaluation, documentation, production monitoring, retraining and responsible-AI review
Make build, extend or buy decisions and keep the portfolio focused on solutions that deliver measurable value
Balance capacity between steady-state operations and new build so that existing service commitments are protected while new work lands
Build the organization: structure, hiring, leadership bench, succession, and a culture where engineers own what they ship and raise problems early
Serve as the senior counterpart to client stakeholders, running a regular governance rhythm of status updates, steering reviews and business reviews
Own the value story: define how benefits are measured, track realized results against commitments, and report them with conservative, traceable assumptions
Turn new client requests into prioritized, governed work, and position the roadmap as a way to grow the client relationship
Manage budget, cloud cost and vendor relationships for the organization
What You'll Bring
Extensive experience in technology, including significant time leading engineering, data or AI organizations through team leads
An engineering, analytics or data science background, with enough current depth to review a design, a query or a model evaluation
A track record of leading data and analytics teams alongside product or application engineering teams
Experience managing senior client or business stakeholders and negotiating scope, priorities and investment
Experience building and scaling teams, including hiring senior specialists and developing first-time leaders
Experience owning a value case or cost-and-benefit model at leadership level and defending how it was built
Cloud platforms at architecture level, with Google Cloud preferred and AWS or Azure also welcome
Data engineering and BI, including pipeline design, data modeling, data quality, lineage and modern dashboarding tools
Applied machine learning and generative AI in production, including LLM, RAG and agent applications, with the evaluation and monitoring discipline to run them safely
Modern product engineering, including backend services, component-based web frontends, relational databases, containers and CI/CD
Familiarity with IT service management platforms and ITIL practices
Clear written and verbal communication, including the ability to explain a technical tradeoff to an executive in a few sentences
A bachelor's degree in Computer Science, Engineering, Mathematics, Statistics or a related field, or equivalent practical experience; a master's degree or MBA is a plus
Nice to Have
Experience leading a client-dedicated or captive technology team inside a large enterprise
Experience in field services, IT asset management or workplace operations
Experience running onshore and offshore teams across time zones
Program management certification such as PgMP, PMP or SAFe
What Success Looks Like
Early on: you are running governance with client stakeholders, you know every team and lead, production services are stable, and the roadmap and hiring plan are agreed.
Over time: new solutions are live and adopted, the organization has grown to plan, and clients see measurable results they recognize as their own.
Throughout: no surprises for clients, decisions written down when they are made, and leads growing into the next level.
What Astreya Offers
Work with leading enterprises as part of the Astreya delivery network
Career paths built around internal promotion and mobility
Professional development, online learning and education assistance
Competitive compensation with insurance, health and wellness benefits
