Financial Services - Solution Engineering - Technology Consulting - Senior Manager

Location:

New York, Chicago, Charlotte, Hoboken, Philadelphia, Columbus, Atlanta, Boston

At EY, we’re all in to shape your future with confidence.

We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.

EY’s financial services business unit (“FSO”) is at the forefront of the industry’s major transformations. If you are passionate about combining people, engineering, and technology to solve complex challenges, join our FSO team.

Combining hands‑on technical expertise, an AI‑first mindset, and strong business understanding, you will lead multidisciplinary delivery (product, architecture, cloud, data, quality) from discovery and solution design through production and continuous improvement across full‑stack, APIs, microservices, cloud‑native, and generative and agentic AI, championing AI‑assisted engineering and reusable accelerators without compromising quality, security, or accountability. Primary focus is Financial Services, with opportunities in healthcare, automotive, high‑tech, and media.

Oversee multiple pods (15–25+ engineers, including EMs and Tech Leads) across client solutions, product domains, or core financial platforms, operating at the intersection of enterprise architecture, hands‑on engineering leadership, organizational strategy, and executive advisory. Act as technical counterpart to VP/SVP sponsors, audit leadership, and C‑suite stakeholders, accountable for execution, operational readiness, and client outcomes.

Coach EMs, Staff Engineers, and Tech Leads; drive hiring, succession, and inclusion; build pods with Data & AI and Cyber specialists across onshore/global teams, growing career paths and AI fluency.

• Advise executives (VP/SVP of Product, CIO/CTO, Chief Risk Officer, Business Unit Executives) on digital transformation, AI‑enabled solutions, agentic engineering practices, and long‑term technology investment.
• Turn trade‑offs, modernization, and capex needs into executive business cases and board‑level presentations.
• Lead technical discussions in internal audits, regulatory reviews, and key client interactions, including AI governance.

Direct the multi‑year architecture roadmap across Java, Python, and full‑stack platforms; govern the API lifecycle, cloud‑native modernization, multi‑region failover, and zero‑trust security; guide build‑vs‑buy and non‑functional requirements.

Define and operationalize an AI‑first SDLC strategy with AI‑assisted and agentic workflows, governance, IP protection, DORA/cycle‑time/quality/reliability metrics, and AI cost/ROI models, backed by human review, automated validation, and privacy/security controls, measured against baselines, not code volume.

Integrate generative and agentic AI where there is a clear business case, partnering with Data & AI on models, grounding, and evaluation and owning production engineering (access, data, quality, latency, cost, oversight).

Turn client needs into prototypes and production solutions, and build documented reusable components, reference architectures, and accelerators with the Innovation team.

Shape opportunities with account and sector teams via proposals, RFPs, and demos with credible approaches, estimates, staffing models, and risks that become executable delivery plans.

Own delivery across pods (scope, dependencies, quality, risk, budget, timelines), release readiness,…