Senior AI Engineer

Senior AI Engineer with strong financial domain experience.

Location: New York (onsite Role)

Essential Experience & Skills:

• Advanced Python expertise, plus experience with other major backend languages (e.g., Java, C++, Go) and modern AI/ML toolkits
• Demonstrated proficiency in designing, validating, and launching code-generation systems and agentic workflows, strong familiarity with prompt engineering and AI model deployment
• Track record of hands-on technical leadership within agile teams, overseeing both human and AI-generated codebases and ensuring auditability, explainability, and compliance at scale
• Expertise in code review, automated testing, and documentation standards for mixed human/AI development environments

Key Responsibilities:

• Build and demonstrate AI-powered solutions for financial applications preferably in investment banking, Trading or insurance environments.
• Translate complex AI concepts into actionable business value for both technical and non-technical stakeholders, simplifying information for internal teams and executive leadership.
• Lead workshops, seminars, and training sessions for teams across the organization, promoting AI literacy and upskilling staff in banking, investment, or insurance environments.
• Ability and /or experience in authoring technical blogs, white papers, and internal documentation that explain the impact and possibilities of AI in the financial domain.
• Experience on working on advisory capacity to CxO, Head of Engineering, Head of Architecture on technical strategies
• Act as a visible presence at industry conferences, webinars, and external forums to position the organization as a leader in responsible AI use within finance.
• Partner with compliance, risk, and IT teams to ensure all AI solutions meet strict regulatory and ethical standards prevalent in financial services.
• Prototype, test, and deploy AI models that address market forecasting, customer insights, automated underwriting, or anti-money laundering strategies.

Key Technical and Design Responsibilities

• Build, deploy, and manage both agentic AI architectures and generative code systems, ensuring scalable and secure integration of technologies like LLMs, code generators, and automation agents within production workflows.
• Oversee technical design, implementation, and code reviews—especially for code created or assisted by AI tools—maintaining high standards of security, performance, and maintainability in Python and other programming languages.
• Develop robust testing and validation protocols for AI-generated code and agent behavior, including prompt engineering, debugging, and post-deployment monitoring for unusual failure patterns or compliance issues.
• Lead technical teams, mentor junior engineers, and set excellence in software engineering practices; create documentation and establish guidelines for both human and AI-driven contributions
• Collaborate with cross-functional stakeholders (DevOps, security, product, and business leaders) to ensure rapid, safe adoption of agentic and generative AI features

Essential Qualifications

• Bachelor’s or master’s degree in computer science, Data Science, Finance, or related field.
• Experience in one or many of the high-level programming languages like C++, Java, C#
• Good understanding of Typescript, Node.js and other JS framework for UI development
• Strong hands-on experience with Python, SQL, and AI/ML frameworks (e.g., TensorFlow, PyTorch) as applied to financial data and workflows
• At least 4+ years working in AI roles within finance, fintech, or technical consulting, preferably with exposure to regulatory environments.
• Deep knowledge of AI ethics, compliance, Guardrails, data privacy, and compliance trends relevant to the financial sector.
• Excellent communication, stakeholder engagement, and technical storytelling abilities.[7][3]
• Demonstrated ability to manage multiple priorities and projects while maintaining strategic alignment and rigorous attention to detail.

Desired Traits

• Passion for driving innovation and adoption of AI in highly regulated settings.
• Effective at stakeholder education—from boardroom to engineering teams.
• Strong problem-solving mindset, able to translate technical outputs into practical business recommendations.
• Integrity and diligence, with a commitment to both organizational objectives and ethical AI deployment.

Job Type: Full-time

Work Location: In person