About this role.
This hands-on Engineering Manager role leads GoodLeap's AI Transformation engineering team, building and operating agentic AI solutions for internal business units. The position owns architecture, delivery quality, reliability, operational maturity, and engineering standards for AI agents, plugins, evaluation harnesses, integrations, and usage analytics. It requires deep practical experience with LLM products, MCP-style orchestration, cloud-native systems, TypeScript and/or Python, CI/CD, and observability. The manager will hire and coach engineers while partnering closely with Product, Security, Compliance, and business stakeholders in a regulated financial-services environment. Success depends on safely scaling AI adoption while delivering measurable improvements in adoption, quality, and engineering velocity.
Role DNA
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Job Complexity
5/5Pace & Pressure
5/5Autonomy Level
5/5Communication Load
5/5Salary analysis
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Core skills
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Sample interview questions
I would establish reusable platform components for identity and access controls, model gateways, tool and MCP integrations, prompt and policy management, evaluation harnesses, telemetry, and audit logs. Business-specific agents would be built on these governed primitives, with clear ownership, rollout controls, and service-level expectations.
I would define task-specific offline evaluations covering correctness, groundedness, tool-use accuracy, security, policy adherence, and failure modes. I would then use staged releases, human review for higher-risk workflows, production monitoring, and feedback loops to detect regressions and continuously improve quality.
I would involve Security, Compliance, Legal, and business owners early to establish data classifications, approved models and tools, retention rules, access controls, audit requirements, and escalation paths. Teams should treat governance as an engineering constraint built into architecture and CI/CD rather than a late-stage approval step.
I would use a balanced scorecard: adoption and active usage, time saved or workflow throughput, task quality and reliability, incident and support trends, delivery lead time, and stakeholder satisfaction. Metrics would be tied to each engagement model while avoiding vanity measures such as raw prompt volume alone.
I would set clear technical direction and quality standards, pair with engineers on consequential architecture decisions, and create regular design reviews and learning opportunities. I would delegate ownership of services and outcomes, provide direct feedback, and use career plans that grow both technical depth and leadership capability.
About GoodLeap:
GoodLeap is a technology company delivering best-in-class financing and software products for sustainable solutions, from solar panels and batteries to energy-efficient HVAC, heat pumps, roofing, windows, and more. Over 1 million homeowners have benefited from our simple, fast, and frictionless technology that makes the adoption of these products more affordable, accessible, and easier to understand. Thousands of professionals deploying home efficiency and solar solutions rely on GoodLeap’s proprietary, AI-powered applications and developer tools to drive more transparent customer communication, deeper business intelligence, and streamlined payment and operations. Our platform has led to more than $30 billion in financing for sustainable solutions since 2018.
GoodLeap is also proud to support our award-winning nonprofit, GivePower, which is building and deploying life-saving water and clean electricity systems, changing the lives of more than 1.6 million people across Africa, Asia, and South America.
Position Summary
GoodLeap’s AI Transformation team partners with business units across the company to enable safe and effective AI adoption through tools, guidance, infrastructure, training, and custom solutions — from Claude plugins and skills to AI agents, evaluation frameworks, and usage analytics. The Engineering Manager will lead the AI Transformation engineering team, owning the delivery, quality, and operational health of the AI solutions the team builds and maintains.
This is a hands-on technical leadership role for someone who can guide the architecture of agentic AI systems while building, coaching, and scaling the team accountable for them.
Essential Job Duties and Responsibilities
- People Leadership – Lead, coach, and grow the AI Transformation engineering team. Own hiring, performance management, and career development. Build a high-performance, accountable engineering culture.
- Technical Leadership – Own the architecture, delivery, and reliability of the team’s AI solutions (agents, plugins/skills, evaluation harnesses, integrations, usage analytics).
- Guide technical decisions on agentic workflows, LLM integration, and MCP-based orchestration. Set and enforce engineering standards for security, compliance, and auditability appropriate to a regulated financial services environment. Champion modern engineering practices, including AI-assisted and agentic development workflows.
- Cross-Functional Execution – Partner with Product, business units, and the Enterprise AI Governance process to align engineering delivery with business outcomes across consult, co-develop, and own-and-maintain engagement models. Own delivery across initiatives spanning multiple teams; define and track KPIs for adoption, quality, and velocity.
- Process & Operational Maturity – Drive CI/CD, observability, and support rigor across the team’s solutions. Manage technical debt and scalability as the portfolio of AI solutions grows.
Required Skills
- 7+ years of software engineering experience, including 2+ years in technical leadership or management roles
- Hands-on experience building and shipping LLM-based or agentic AI products (prompting, evals, agent frameworks, MCP or similar orchestration)
- Strong grasp of cloud-native architecture (AWS or equivalent), API design, and modern CI/CD practices
- Proficiency in TypeScript and/or Python
- Track record of hiring, coaching, and growing engineers through changing scope
- Excellent stakeholder management and communication skills; comfortable operating across Product, business units, Security, and Compliance
- Experience in a regulated environment (fintech, lending, payments) a plus
- Experience integrating AI or agentic tooling into the software development lifecycle to improve engineering throughput a plus
Compensation
Additional Information
CA, WA, NJ, MA, DC, NYC range: $185,200 – $210,600
Rest of US Range: $169,100- $191,800
SF Range: $207,900- $235,700
In addition to the above salary, this role may be eligible for a bonus and equity.
Additional Information Regarding Job Duties and Job Descriptions:
Job duties include additional responsibilities as assigned by one’s supervisor or other managers related to the position/department. This job description is meant to describe the general nature and level of work being performed; it is not intended to be construed as an exhaustive list of all responsibilities, duties and other skills required for the position. The Company reserves the right at any time with or without notice to alter or change job responsibilities, reassign or transfer job position or assign additional job responsibilities, subject to applicable law. The Company shall provide reasonable accommodations of known disabilities to enable a qualified applicant or employee to apply for employment, perform the essential functions of the job, or enjoy the benefits and privileges of employment as required by the law.
If you are an extraordinary professional who thrives in a collaborative work culture and values a rewarding career, then we want to work with you! Apply today!
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