Application Deployment Engineer, Associate

BlackRock•New York, NY

4d•$132,500 - $162,500•Hybrid

About The Position

BlackRock is seeking an Associate, Deployment Engineer to support the delivery and deployment of tech enabled solutions created by the Platform Enablement Engineering team within the Technology & Operations organization. The role is focused on helping move solutions from discovery through requirements, delivery, launch, and post-launch improvement, so that AI capabilities are embedded into real operational workflows. This role is well suited to someone who is analytically strong, highly organized, and comfortable working across business and technology teams. The successful candidate will develop deep knowledge of the operational workflows they support, contribute to clear and executable requirements, and keep delivery moving by tracking dependencies, coordinating stakeholders, and escalating risks early. They will work under the direction of a Deployment Engineering Lead while owning defined workstreams end to end.

Requirements

Bachelor's degree required.
Typically 3–5 years of relevant experience in business analysis, project management, technology delivery, consulting, or operations.
Experience translating business or operational needs into structured requirements and executable deliverables.
Demonstrated ability to analyze workflows, identify gaps and dependencies, and contribute to practical future-state solutions.
Working knowledge of the software delivery lifecycle, including requirements, testing, release readiness, and post-launch support.
Strong analytical and problem-solving skills, including the ability to organize ambiguous information and form clear recommendations.
Strong written and verbal communication skills, with the ability to work effectively with both technical and non-technical stakeholders.
Excellent organizational skills, attention to detail, and the ability to manage multiple priorities with consistent follow-through.
Proficiency with delivery and collaboration tools such as Azure DevOps, Jira, Confluence, Airtable, SharePoint, or comparable platforms.

Nice To Haves

Familiarity with AI or machine learning concepts, including agentic systems, intelligent workflows, or document processing.
Experience supporting deployment or rollout of technology solutions into live business environments.
Exposure to automation technologies, workflow tooling, or operational reporting (e.g., Power BI).
Knowledge of investment operations, client onboarding, post-trade, or asset management workflows.

Responsibilities

Facilitate end-to-end business deep dives and workshops, including scheduling sessions with subject matter experts, capturing notes, and documenting current- and future-state process maps.
Capture and organize key themes from discovery, including pain points, manual effort, and risk areas, and validate documentation with business stakeholders.
Contribute to Business Requirements Documents (BRDs), future-state workflows, and data dictionary requirements under the direction of a Deployment Lead.
Gather data on scope, volume, and time spent to support benefit and ROI estimates.
Own defined workstreams from requirements through testing, launch, and post-launch stabilization.
Coordinate day-to-day with engineers, business SMEs, and transformation partners to keep deliverables, dependencies, and timelines on track.
Support working sessions and functional steering committees, including agendas, notes, and follow-ups.
Support user acceptance testing, AI acceptance criteria (AIAC), and production readiness activities.
Track risks, issues, and open decisions, escalating promptly and transparently.
Support rollout planning, business readiness assessments, and training and communication materials for new AI tools and workflows.
Help establish support channels and post-launch feedback loops with business users.
Monitor adoption and usage, gather user feedback, and translate it into prioritized enhancement recommendations.
Maintain accurate, organized project and process documentation so knowledge is reusable across engagements.
Contribute to team reporting, newsletters, delivery metrics, and status updates for business and technology leaders.
Apply AI-enabled tools to streamline analysis, documentation, reporting, and knowledge management within the team's own ways of working.
Contribute to deployment standards, playbooks, and reusable patterns that improve how the team delivers.