Engineering Manager Jobs

About The Position

Requirements

• 10 or more years of experience in software engineering or technical consulting, including 5 or more years managing engineering teams.
• Demonstrated success hiring, developing, and retaining senior engineers.
• Ownership of client-facing engineering delivery in consulting, professional services, or a comparable environment, including staffing, resource allocation, utilization, and capacity forecasting.
• Experience leading teams that shipped LLM-powered applications into production, with the ability to explain architecture, implementation decisions, operating costs, and technical tradeoffs.
• Hands-on experience with modern AI engineering practices, including RAG, agentic workflows, function calling or MCP, evaluation frameworks, and observability.
• Daily use of AI coding tools such as Claude Code, Cursor, or GitHub Copilot, and experience establishing team workflows around them.
• Ability to assess and address AI risks in regulated environments, including hallucinations, data leakage, prompt injection, and audit-trail integrity.
• Demonstrated technical decision-making, people development, delivery prioritization, and stakeholder communication, including managing expectations and resolving escalations with senior client executives and internal leaders.

Nice To Haves

• Experience in tax, audit, accounting, or financial services.
• Experience managing engineering leads or managers.
• Experience scaling engineering teams while maintaining hiring quality and delivery standards.
• Background in forward-deployed engineering, solutions engineering, or embedded client delivery.

Responsibilities

• Build, lead, and develop a senior engineering team of engagement leads, AI engineers, and integration engineers, including hiring, coaching, performance management, and career development.
• Own staffing, capacity planning, and delivery forecasting across client engagements; match skills and availability to demand, maintain capacity for pre-sales prototypes, and address resource gaps before they affect delivery.
• Provide technical leadership for production AI solutions by reviewing architecture, scope, estimates, and operating costs across RAG, AI agents, tool integrations, and prompt and context engineering.
• Set standards for AI quality, evaluation, and risk controls, including reference datasets, expert review, regression testing, accuracy thresholds, and safeguards for regulated tax and audit work.
• Own delivery health and client outcomes across engagements, manage scope, risk, quality, and client satisfaction, and serve as an escalation point for clients and internal teams.
• Improve engineering effectiveness by embedding AI coding tools, automated testing, evaluation pipelines, and reusable solutions into team workflows.
• Partner with business, product, consulting, and platform leaders to align demand with capacity, resolve competing priorities, support transitions into ongoing support, and report on utilization, throughput, and forecast accuracy.

Benefits

• Flexible vacation and flexible work arrangements, including work from anywhere for up to 8 weeks per year.
• Two company-wide Mental Health Days off and access to the Headspace app.
• Health, dental, vision, disability, and life insurance programs.
• Retirement savings plan with company match.
• Tuition reimbursement.
• Employee incentive programs and possible annual bonus.
• Resources and programs for mental, physical, and financial wellbeing, including fitness reimbursement and an Employee Assistance Program.
• Paid holidays, sick and safe paid time off, and parental leave.
• Sabbatical leave.
• Two paid volunteer days annually and opportunities for pro-bono consulting and ESG initiatives.
• Flexible Spending and Health Savings Accounts.
• Commuter benefits.
• Adoption and surrogacy assistance.
• Employee Stock Purchase Plan.
• Optional hospital, accident and sickness insurance; optional life and AD&D insurance; group legal and identity theft protection; and access to a 529 Plan.