GenAI Software Engineer, Professional (Risk Engineering & Automation)
About The Position
As a Software Engineer, Professional (GenAI), your role is pivotal in shaping the future of AI-driven business solutions. You will design and develop scalable applications that integrate sophisticated AI models, directly influencing how businesses operate and succeed. In this role, you will contribute to building next-generation GenAI solutions and automation capabilities, with a focus on embedding risk awareness, controls, and governance into AI-driven systems. Your expertise in Python-based microservices will support the development of robust, quality-controlled frameworks for GenAI solutions, including those supporting governance and approval processes. By collaborating with GenAI scientists, UX designers, and cross-functional teams, you will help deliver enterprise-grade AI solutions that meet high standards of performance, reliability, and responsible AI practices. Joining us offers the opportunity to work on cutting-edge GenAI and automation initiatives, gaining hands-on experience in building enterprise-scale AI solutions. You will learn how AI is applied in real-world, regulated environments, and be part of shaping the future of AI-enabled risk management.
Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, IT, or a related field (advanced degree preferred)
- 2–4 years of software development experience
- 1–2 years of hands-on experience in GenAI solutions, including LLMs (e.g., OpenAI, Anthropic, AWS Bedrock)
- Experience building RAG systems using vector databases
- Familiarity with agentic frameworks (e.g., LangChain, LangGraph, or similar)
- 2–4 years of experience in cloud development (AWS preferred), REST APIs, and microservices
- Strong programming skills in Python (experience with TypeScript/Java is a plus)
- Experience building enterprise or customer-facing AI applications
- Familiarity with CI/CD and DevOps practices
- Demonstrated ability to work in cross-functional agile teams
- Exposure to LLM guardrails, evaluation frameworks, or AI safety techniques
- Familiarity with AI governance, model risk, or responsible AI concepts
- Experience supporting quality-controlled or regulated environments
Responsibilities
- Designing and developing scalable GenAI applications such as copilots, automation tools, and workflow solutions
- Building and enhancing RAG pipelines using vector databases and retrieval strategies
- Applying prompt engineering techniques to improve model performance
- Developing and maintaining Python-based microservices and RESTful APIs
- Supporting the automation of business and risk processes through AI-driven workflows
- Contributing to CI/CD pipelines and DevOps practices
- Assisting in implementing guardrails and validation mechanisms for LLM-based applications
- Embedding risk and control considerations into AI solutions
- Data transformation, cleansing, and preparation for AI model usage, ensuring data quality
- Supporting model evaluation and continuous improvement
- Collaborating with engineers, data owners, product teams, and risk partners
- Participating in code reviews, design discussions, and agile ceremonies
- Staying current with evolving trends in LLMs, agent frameworks, and AI engineering tools
Benefits
- competitive compensation
- market-leading benefit programs
- annual incentive program
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
