AI Agent Engineer - FinTech Software

Alldus International Consulting Ltd; New York (NY); On-site; USD 130,000 - 140,000; Full time

Benefits offered by this job

Salary: $130k - $140k

Equity

Medical, dental, vision insurance

401(k) match

Job summary

Alldus International Consulting Ltd is recruiting a graduate or early-career Software Engineer in New York to design, build, and deploy production-grade AI agent systems for financial workflows. You will own context engineering, prompting, tooling, evaluations, guardrails, and the broader product experience.

Responsibilities include building robust data pipelines, enabling AI systems to reason across transactions and ledgers, and delivering secure, auditable AI-driven actions within enterprise

Qualifications

• Pursuing or recently graduated with a CS/ML/AI degree.
• At least one meaningful internship in software or AI engineering.
• Experience building AI agents or generative AI systems in research, work or projects.

Responsibilities

• Design, build and deploy AI agents for finance and audit workflows with guardrails.
• Develop context-engineering strategies for AI reasoning across transactions and policies.
• Build data pipelines from ERPs, banking systems and CRMs.
• Explain decisions, handle uncertainty and improve via human feedback.
• Create reliable, stateful workflows across enterprise systems.
• Ensure AI-driven actions are secure and auditable to financial records.
• Contribute across LLMs, backend, infra and product development.
• Utilize modern AI tools to accelerate delivery with quality and reliability.

Skills

AI agent dev

Python

LLM tooling

Prompt engineering

Context engineering

Backend dev

Ownership

Team collaboration

Open-source projects

Education

Bachelor's or Master's in CS/ML/AI

Tools

Claude Code

Cursor

Job description

Alldus International Consulting Ltd is recruiting a graduate or early-career Software Engineer in New York to design, build, and deploy production-grade AI agent systems for financial workflows. You will own context engineering, prompting, tooling, evaluations, guardrails, and the broader product experience.

Responsibilities include building robust data pipelines, enabling AI systems to reason across transactions and ledgers, and delivering secure, auditable AI-driven actions within enterprise