Senior AI Engineer

Senior AI Engineer Automation & Delivery Optimization (Banking Platforms/Professional services)

Location -Remote
Full-time / W2 - with Infinite Computer Solutions

Job Summary

We are seeking an experienced Sr. AI Engineer to lead the design, development and deployment of intelligent automation solutions tailored to online banking platforms. This role combines deep AI/ML expertise with financial domain knowledge to streamline product delivery, enhance customization, and optimize client engagement. The ideal candidate will drive innovation across the delivery lifecycle while ensuring compliance with regulatory standards.

Key Responsibilities

• AI-Driven Automation: Design and implement AI/ML models to automate product configuration, customization, and estimation processes.
• Requirements Analysis: Build intelligent systems to analyze client requirements, generate scope documents, and recommend effort estimations.
• Delivery Forecasting: Leverage historical project data to develop predictive models for delivery timelines and resource planning.
• Lifecycle Optimization: Automate repetitive tasks across customization, configuration, and deployment lifecycle using AI/ML.
• Project Intelligence: Apply AI to enhance project management processes, including risk prediction, milestone tracking, and delivery optimization.
• Knowledge Engineering: Develop tools to document existing customizations and frameworks, contributing to reusable assets and best practices.
• Platform Integration: Support the integration of AI features into digital banking platforms, including mobile and web applications.
• Security Intelligence: Implement AI-based solutions to proactively identify and mitigate security vulnerabilities during development.
• Compliance & Ethics: Ensure all AI implementations adhere to financial regulations, data privacy laws, and ethical AI principles.
• Cross-Functional Collaboration: Collaborate with managers, engineers, and client stakeholders to define and deliver tailored AI solutions.
• Client-Centric Customization: Design and implement tailored AI solutions for banking clients, including intelligent chatbots, personalized recommendation engines, and advanced fraud detection systems. Develop AI-powered chatbots capable of retrieving and interpreting internal product documentation and implementation guides, enhancing client support and operational efficiency.
• Change Management Automation: Automate change request creation and approval workflows using intelligent systems.
• QA Automation: Automate test case generation, creation of automated test scripts, and execution to improve testing efficiency and coverage.
• Production Support Intelligence: Analyze and document past incidents, defects, and resolutions using AI to prevent recurrence and enhance system reliability.
• Innovation and continuous improvements: Stay abreast of the latest AI advancements in financial services. Recommend new tools, frameworks and techniques to enhance solution performance and maintain competitive advantage.
• Mobile App Delivery Automation: Develop AI-driven solutions to streamline and accelerate the mobile banking app delivery lifecycle, including automated build, testing, deployment, and monitoring processes across multiple environments and platforms.

Required Qualifications

• Bachelor s or master s degree in computer science, Artificial Intelligence, Data Science, or a related field.
• 6+ years of experience in AI/ML, with at least 2 years in FinTech or banking technology.
• Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Experience with cloud platforms (AWS, Azure, Google Cloud Platform), APIs, and containerization tools (Docker, Kubernetes).
• Experience with Azure Devops, C#, .Net framework, Jenkins, ReactJS, Github, Github Actions, Confluence, Jira, Sonatype, Fortify, SQL server, JavaScript, HTML, CSS, Harness
• Strong problem-solving, analytical thinking, communication, and collaboration skills are essential.

Preferred Qualifications

• Experience with online and mobile banking platforms.
• Familiarity with digital banking trends, customer journey mapping, and UX personalization.
• Exposure to ML Ops practices and AI model lifecycle management.