Blackrock
Deployment Engineer
Overview
As a Deployment Engineer, you will help bridge the gap between innovative AI capabilities and practical business outcomes. You will work closely with operational stakeholders and technical teams to identify opportunities for AI-driven transformation, support the deployment of solutions into production environments, and drive adoption.
About Blackrock
At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being. Our clients, and the people they serve, are saving for retirement, paying for their children’s educations, buying homes and starting businesses. Their investments also help to strengthen the global economy.
Requirements & Eligibility
- Experience deploying technology solutions into production business environments, ideally involving artificial intelligence, automation, or advanced analytics.
- Strong ability to analyze business processes and translate operational needs into deployable solutions.
- Experience working across technical and non-technical teams to drive outcomes and influence stakeholders.
- Familiarity with artificial intelligence or machine learning concepts, including agentic systems and intelligent workflows.
- Experience partnering with engineering teams on artificial intelligence platforms, Application Programming Interfaces (APIs), or data pipelines.
- Ability to use data, performance metrics, and user feedback to inform prioritization and continuous improvement.
- Demonstrated learning agility and adaptability in rapidly evolving technology environments.
Key Responsibilities
- Lead the end-to-end deployment of AI solutions into live operational environments.
- Conduct business process assessments with domain experts to identify opportunities for artificial intelligence, automation, and workflow optimization while defining success metrics and implementation requirements.
- Partner with engineering, data science, and platform teams throughout solution design, development, testing, and release activities.
- Serve as the primary partner during deployment to ensure solutions are usable, reliable, scalable, and aligned with operational objectives.
- Measure solution adoption, performance, and operational risk, using stakeholder feedback and operational insights to prioritize enhancements and drive continuous improvement.
- Contribute to deployment standards, governance frameworks, documentation, and operational readiness practices that support responsible and scalable adoption of artificial intelligence solutions.
- Support the development of repeatable deployment methodologies, playbooks, and best practices across Technology & Operations.
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