Senior Manager – Solution Engineering, Technology Consulting

. Lead multidisciplinary delivery across product, architecture, cloud, data, and quality from discovery and solution design through production and continuous improvement .

Posted 10/10/2026full-timeUnited StatesSenior💰 $151,500 - $346,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in leading engineering teams and delivering complex enterprise solutions, with a strong focus on AI integration, cloud-native architectures, and operational excellence in regulated environments. Capable of advising executives on technology investments and driving modernization initiatives while ensuring quality and security.

Highest-signal resume keywords

Java DevelopmentPython DevelopmentAPI ManagementAI IntegrationFinancial Services Delivery

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Microservices ArchitectureCloud-Native DevelopmentCI/CD PracticesObservability TechniquesSecure Development

Soft Skills

Collaborative LeadershipExcellent CommunicationStrong Engineering Judgment

Tools & Technologies

AI-Assisted Engineering ToolsGenerative AIAgentic AI

Certifications & Qualifications

Bachelor’s Degree in Computer Science

Industry Keywords

Digital TransformationOperational ResilienceAuditabilityRegulatory ComplianceClient Solutions

Tech Stack

Tools & technologies

CloudJavaMicroservicesPython

About the role

Key responsibilities & impact

Lead multidisciplinary delivery across product, architecture, cloud, data, and quality from discovery and solution design through production and continuous improvement
Oversee multiple pods of 15–25+ engineers, including Engineering Managers and Tech Leads, across client solutions, product domains, or core financial platforms
Act as technical counterpart to VP/SVP sponsors, audit leadership, and C-suite stakeholders, accountable for execution, operational readiness, and client outcomes
Coach Engineering Managers, Staff Engineers, and Tech Leads; drive hiring, succession, inclusion, career paths, and AI fluency
Advise executives on digital transformation, AI-enabled solutions, agentic engineering practices, and long-term technology investment
Turn modernization trade-offs and capital expenditure 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 multi-year architecture roadmaps across Java, Python, and full-stack platforms
Govern API lifecycles, cloud-native modernization, multi-region failover, zero-trust security, build-vs-buy decisions, and non-functional requirements
Define and operationalize an AI-first software development lifecycle strategy with AI-assisted and agentic workflows, governance, IP protection, metrics, and AI cost/ROI models
Integrate generative and agentic AI where there is a clear business case, partnering with Data & AI and owning production engineering
Turn client needs into prototypes and production solutions; build documented reusable components, reference architectures, and accelerators
Shape client opportunities through proposals, RFPs, demos, estimates, staffing models, and risk planning
Own delivery across pods, including scope, dependencies, quality, risk, budget, timelines, release readiness, observability, production support, and handover
Agree success measures with clients and track value, adoption, reliability, and continuous improvement after launch
Guide transformations from legacy monoliths to contract-driven microservices and stream-aligned squads
Embed AI-enabled ways of working through training, adoption support, accountability, and impact measurement

Requirements

What you’ll need

Bachelor’s degree in Computer Science or another related field
Experience leading multiple engineering teams and developing EMs, Tech Leads, or senior technical specialists
Experience delivering complex enterprise solutions from discovery and architecture through production and improvement
Strong technical depth in Java and/or Python, APIs, microservices, cloud-native, and full-stack delivery
Experience with CI/CD, testing, secure development, and observability
Practical experience introducing AI-assisted engineering tools, including adoption, evaluation, and governance
Working knowledge of generative/agentic AI integration, including evaluation, security, latency, and cost
Experience advising senior stakeholders, managing delivery risk, and linking technology decisions to business outcomes
Delivery experience in Financial Services or similarly regulated environments, including security, auditability, and operational resilience
Ability to prioritize and lead multiple pods in a fast-paced, collaborative environment, with travel as required
Excellent written and oral communication for executives and engineers
Strong engineering judgment to turn ambiguous needs into designs and plans, challenge architecture, and resolve delivery issues
Practical, responsible AI judgment balancing value and speed with quality, security, and privacy
Collaborative leadership supporting learning, inclusion, and accountability across onshore and global teams

Benefits

Comp & perks

Medical and dental coverage
Pension and 401(k) plans
Flexible vacation policy
EY Paid Holidays
Winter/Summer breaks
Personal/Family Care leave
Other leaves of absence
Professional growth opportunities
Inclusive culture
Reasonable accommodation for qualified individuals with disabilities