Job Description
AI Engineer – Financial Services Remote / Hybrid
About RiskSpan
RiskSpan is a leading source of analytics, modeling, data, and risk management solutions for the Consumer and Institutional Finance industries. We serve banks, issuers of mortgage\- and asset\-backed securities, asset managers, servicers, and regulators with cutting\-edge technology and deep domain expertise across credit, market, and operational risk.
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Position Overview We are seeking a hands\-on AI Engineer to design, build, and deploy production\-grade AI applications using AWS Bedrock, RAG architectures, and agent\-based workflows. This role focuses on building real\-world AI systems\- chatbots, data analysis agents, and workflow automation solutions, integrating enterprise data and delivering scalable, reliable applications in AWS. The ideal candidate brings strong Python skills, cloud\-native engineering experience, and a track record of shipping production AI systems end\-to\-end.
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Key Responsibilities
* Design, build, and deploy AI\-powered applications including chatbots, knowledge assistants, and workflow automation agents.
* Implement end\-to\-end solutions covering data ingestion, transformation, prompt orchestration, model interaction, and cloud deployment.
* Integrate AI systems with internal APIs, enterprise platforms, and data pipelines.
* Design agent workflows with tool/function calling, branching logic, retries, and fallback handling.
* Implement human\-in\-the\-loop and approval\-based workflows for regulated financial use cases.
* Build multi\-agent systems for validation, refinement, and complex task decomposition.
* Design and implement RAG pipelines covering chunking, embeddings, retrieval, and grounding.
* Work with structured and unstructured data using SQL, S3, and data pipeline tools.
* Leverage AWS services (S3, Glue, Redshift, Lambda, ECS, Step Functions, SQS/SNS) for storage, transformation, and orchestration.
* Monitor and improve AI systems for accuracy, latency, cost, and reliability.
* Implement structured output validation, schema enforcement, and guardrails.
* Evaluate model performance and iteratively improve grounding and output consistency.
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Required Qualifications
* Strong experience building AI applications using LLMs (e.g., AWS Bedrock or equivalent platforms).
* Hands\-on experience with RAG architectures and retrieval pipelines.
* Experience with vector databases, embeddings, and semantic search.
* Demonstrated track record deploying production AI systems end\-to\-end — not just prototypes.
* Solid Python programming skills (required).
* Experience with core AWS services: Lambda, ECS, S3, Step Functions, SQS/SNS.
* Strong SQL skills for querying and integrating structured data.
* Experience integrating AI systems with APIs, databases, and cloud services.
* Understanding of prompt engineering, tool/function calling, and structured outputs.
* Strong problem\-solving skills for building reliable systems around probabilistic AI behavior.
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Preferred Qualifications
* Experience with AWS Bedrock AgentCore or similar agent orchestration frameworks.
* Experience building multi\-agent systems or advanced agent workflows.
* Experience with AWS Glue, Redshift, EMR, or broader data engineering pipelines.
* Experience with LLM evaluation frameworks and automated testing.
* Knowledge of schema validation, guardrails, and output control techniques.
* Experience with CI/CD, containerization, and infrastructure as code.
* Background in financial services, regulated environments, or GSE/enterprise data platforms.
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Why RiskSpan? Join a team that combines deep industry expertise with cutting\-edge analytics and AI to solve our clients’ most complex challenges. At RiskSpan, we foster innovation, collaboration, and continuous growth.
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Equal Opportunity Employer RiskSpan is proud to be an Equal Opportunity/Affirmative Action employer committed to hiring a diverse workforce and sustaining an inclusive culture. Qualified candidates must be legally authorized to work in the United States on an unrestricted basis.