UNAVAILABLE
$130,000–$175,900 year
On-siteNew York City, New York, United States or Houston, Texas, United States
Job Summary
Partner with business stakeholders to identify manual handoffs, rework, and exception-heavy processes, then design and deliver AI-enabled automation solutions that improve operational efficiency. Translate requirements into technical specifications and build agentic workflows using Python, LLM APIs, and enterprise platforms like Azure and Salesforce. Rapidly prototype, test, and iterate on intelligent agents and secure data pipelines while embedding governance, security, and compliance throughout the lifecycle. Deploy and monitor production solutions, ensuring reliability and continuous improvement across finance, legal, and operations functions. Work cross-functionally with engineering and product teams to move projects from concept to adoption, documenting architecture and best practices.
Required Qualifications
- Bachelor's degree in Computer Science, Engineering, Information Technology, Data Science, Mathematics, or a related field; equivalent practical experience may also be considered
- 3+ years of experience in software engineering, automation engineering, cloud engineering, data engineering, integration development, or related technical roles, including experience delivering AI or Generative AI solutions in a business environment
- Experience building workflow automations, APIs, integrations, copilots, assistants, or AI-enabled business applications using Microsoft, Azure, OpenAI, ChatGPT Enterprise, or comparable enterprise platforms
- Experience supporting production systems, partnering with cross-functional stakeholders, and translating business needs into secure, scalable technical solutions
- Strong product judgment, communication skills, and delivery orientation, with the ability to release useful increments quickly, recognize when a more durable solution is needed, and write specs, docs, and updates that are clear without additional explanation
- Demonstrated ability to deliver reliable code, services, integrations, or automations used in day-to-day business operations
- Required coding proficiency in Python, with the ability to write clean, tested, maintainable code and contribute effectively to shared production codebases
- Hands-on experience applying LLMs and Generative AI to real business problems, including prompt engineering, LLM APIs, retrieval-augmented generation, AI-enabled workflows, prototypes, assistants, or agents
- Experience using AI-assisted development tools and building tool-using workflows or custom agents that leverage MCP or similar agent integration patterns and connect securely to enterprise systems, APIs, data sources, and business applications
- Demonstrated ability to turn business problems into technical specifications, solution designs, implementation plans, and working software that can be explained clearly to non-technical partners
- Working knowledge across several core enterprise engineering areas, including cloud infrastructure, data engineering, SQL, pipelines, integration patterns, automation tooling, IAM, APIs, and enterprise application development
- Familiarity with information security fundamentals, including authentication, authorization, encryption, secrets management, safe data practices, least-privilege access, auditability, and responsible AI guardrails
- Experience with Microsoft and OpenAI tools such as Azure OpenAI Service, OpenAI APIs, ChatGPT Enterprise, Microsoft Copilot Studio, Azure AI Foundry, Semantic Kernel, OpenAI Agent SDK, Power Platform, or comparable platforms
Desired Qualifications
- Familiarity with advanced agent, retrieval, and orchestration patterns, including vector search, iPaaS tools, LangGraph, LangChain, LlamaIndex, or similar frameworks, is a plus
- Familiarity with TypeScript, JavaScript, Go, or Java is a plus
- Experience designing AI-enabled business process automations across functions such as finance, legal, operations, or other enterprise teams
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