Senior Managing Consultant / Managing Consultant AI Architect (Financial Services)

Location: New York, NY; preferred locations include Chicago, Washington, D.C., Dallas, and Boston. Ability to travel to client sites as needed. Candidates must be able to verify their legal right to work in the United States without employer sponsorship now or in the future.

Salary: $158,000–$180,000 for Managing Consultant; $190,000–$210,000 for Senior Managing Consultant. Final title and compensation depend on qualifications and experience.

Company

hirify.global is an established consulting firm launching a Financial Institution Operations & Technology practice that combines financial services expertise with AI-enabled delivery.

What you will do

• Lead AI architecture and engineering workstreams, translating client operating problems into solution designs, delivery plans, and boundaries between automation and human judgment.
• Implement production AI services in Python, integrating models, retrieval, business rules, tools, APIs, client data, and operational systems.
• Design and build RAG and agentic workflows with source-grounded responses, constrained tool use, human review, exception routing, and escalation paths.
• Define evaluation datasets and acceptance criteria, and test retrieval quality, task accuracy, unsafe behavior, latency, cost, and human oversight.
• Implement LLMOps practices including prompt and model versioning, regression testing, deployment, observability, feedback capture, rollback, and performance review.
• Collaborate with client, security, risk, data, full-stack, change, and domain teams; mentor engineers, lead technical reviews, document solutions, and contribute to reusable assets, estimates, and future pursuits.

Requirements

• At least 5 years of applicable experience for the Managing Consultant level or 7 years for the Senior Managing Consultant level.
• Senior, hands-on delivery of AI applications from architecture through production implementation; equivalent practical experience is accepted regardless of formal education or certification.
• Strong Python engineering skills, including tested services, model integrations, tool interfaces, and maintainable APIs.
• Experience implementing RAG and agentic workflows, including retrieval, orchestration, state management, tool permissions, and human oversight trade-offs without dependence on one vendor stack.
• Ability to design evaluations using representative tasks and expert-reviewed ground truth and improve accuracy, reliability, safety, latency, and cost based on results.
• Experience applying AI security and governance controls, including prompt-injection defenses, access-aware retrieval, sensitive-data protection, and prevention of unauthorized tool execution.
• Experience deploying and operating AI services using cloud infrastructure, containers or equivalent deployment patterns, CI/CD, versioning, monitoring, and rollback.
• Ability to lead complex technical workstreams, mentor engineers, communicate architectural trade-offs, and provide credible delivery estimates to client business, technology, and risk teams.
• Ability to travel to client sites as needed and verify legal right to work in the United States without employer sponsorship.

Nice to have

• Applied AI experience with document-heavy or rules-based financial services processes in lending, servicing, collections, payments disputes, or investment operations.
• Experience facilitating vendor evaluations or AI Co-lab experiments comparing hosted and open-weight models, orchestration frameworks, and deployment options.
• Experience building expert-in-the-loop systems that capture reviewer feedback and convert domain expertise into reusable decision rules, evaluation assets, or workflow components.
• Experience with multimodal document understanding, structured extraction, or advanced retrieval techniques for complex operational tasks.

Culture & Benefits

• Opportunity to build a new Financial Institution Operations & Technology practice within an established consulting firm.
• Collaboration with the AI Co-lab, vendor partners, client teams, domain experts, engineers, and change and risk practitioners.
• Work focused on reusable digital assets, practical implementation roadmaps, measurable operating improvements, and thought leadership.
• Interdisciplinary environment combining specialist consultants, industry experts, academics, data scientists, and emerging technologies.