Job Description
Description
Responsibilities
Drive AI Adoption
- Lead the rollout and day-to-day adoption of AI tools across the engineering team.
- Identify high-impact use cases and embed AI into engineering workflows and processes.
- Partner with engineers to integrate AI into coding, testing, documentation, and operational tasks across environments such as GitHub, .NET, and Java-based systems.
AI Expertise & Enablement
- Serve as the team’s subject matter expert in AI tooling and prompt engineering.
- Provide deep expertise in tools such as Claude Code, Codex, and ChatGPT, and guide teams on when and how to use each effectively.
- Coach and mentor engineers on best practices for leveraging AI in real-world development scenarios.
- Provide hands-on support, including live demonstrations and pair programming when needed.
- Define, track, and report on KPIs that demonstrate the effectiveness of AI adoption (e.g., development velocity, defect rates, cycle time, cost savings).
- Continuously evaluate and optimize AI usage based on measurable outcomes.
- Proactively address skepticism by demonstrating real-world applications and results.
- Build confidence in AI through practical examples and tangible wins.
- Act as an advocate for innovation while grounding decisions in data and outcomes.
- Monitor industry trends, emerging models, and evolving best practices.
- Evaluate new tools and technologies, recommending adoption where beneficial.
- Keep the team informed and engaged on relevant advancements in AI and software engineering.
- Ensure AI usage is efficient and cost-effective.
- Balance performance, quality, and spend when selecting tools and approaches.
- Provide guidance on maximizing ROI from AI investments.
- Product Integration
- Provide technical guidance on incorporating AI capabilities into customer-facing products
- Collaborate with product and engineering teams to design and deliver AI-enabled features
- Increased team efficiency, enabling faster delivery of high-quality projects.
- Clear, data-backed evidence that AI is delivering meaningful value.
- A team that confidently and consistently uses AI tools in their daily work.
- A trusted, approachable leader who is the go-to resource for AI-related guidance.
- Demonstrated ability to quickly validate (or debunk) assumptions about AI effectiveness.
- A forward-looking team that stays current with AI advancements without unnecessary spend.
Qualifications
- Bachelor’s degree or higher in Computer Science, Engineering, or a related field.
- 5+ years of experience in software engineering, AI, and/or machine learning.
- Hands-on experience with modern AI tools, including Claude Code, Codex, ChatGPT, and similar platforms.
- Strong experience working within engineering ecosystems such as GitHub, and development in .NET and/or Java environments.
- Strong understanding of prompt engineering and practical AI application in development workflows.
- Proven ability to influence and drive adoption of new technologies within a team.
- Experience defining and tracking engineering metrics and KPIs.
- Strong communication and mentorship skills; able to explain complex concepts clearly.
- Demonstrated curiosity and continuous learning mindset in a rapidly evolving space.
- Experience in fintech or payments systems.
- Familiarity with multiple AI platforms and model providers.
- Background in developer productivity, DevEx, or tooling optimization.
- Experience running experiments or pilots to evaluate new technologies.
