Senior Applied AI Engineer
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Job Description
Lead design and development of the Agentic AI Platform for compliance software company. Transform traditional Enterprise EHS/ESG SaaS system into an AI-native solution.
Responsibilities:
- The Flex platform helps clients develop a comprehensive compliance program, leveraging technology to instill a culture of safety and maintain a productive workplace.
- The platform combines features that are tailored to the needs of our client’s business, including audits and inspections, incident management, flexible training, and reporting and insights.
- Lead the design, development, and scaling of the Agentic AI Platform, transforming the mature Enterprise EHS/ESG SaaS system (Flex) into a dynamic, AI-native system of intelligence and action.
- Comfortable writing complex state-machine routing code in Python, deploying auto-scaling serverless pipelines on AWS, configuring secure vector search engines, and designing dynamic widget-rendering APIs for the frontend.
- Built and shipped enterprise-grade AI products to production, managing real-world challenges of multi-tenancy, PII redaction, token costs, latency, and model hallucination.
Requirements:
- SaaS Product Experience: 5+ years of software development experience, with at least 2 years spent building and scaling production-grade AI features in a cloud-native SaaS environment.
- Educational Background: Strong academic background in Computer Science, Data Science, Software Engineering, or a highly quantitative field (e.g., Mathematics, Physics, Statistics). Bachelor's degree in Computer Science, Engineering, or a related technical discipline preferred.
- Technical Stack: You must have hands-on, production experience with the following technologies:
- Languages: Python (Expert/Senior level), TypeScript/JavaScript (Strongly Preferred).
- AI Frameworks: LangGraph, LangChain, Vercel AI SDK or equivalent.
- AWS Infrastructure: Amazon Bedrock, ECS Fargate, S3, SQS, EventBridge, KMS, AWS Lambda, Amazon Comprehend, IAM.
- Databases & Search: PostgreSQL / pgVector, Amazon OpenSearch Serverless, SQLAlchemy.
- Data Processing: Pandas, NumPy, PyPDF, Layout-OCR engines.
- API & Protocols: REST, Server-Sent Events (SSE), Webhooks, and Model Context Protocol (MCP).
- Hands-on AWS Background: Strong experience designing secure AWS architectures using Least Privilege IAM execution roles, SigV4 API signing, and KMS envelope encryption.
- RAG at Scale: Experience indexing and searching datasets scaling into millions of document chunks, with a proven understanding of Direct Bulk Indexing APIs.
- System and Security Architecture: Solid understanding of authentication patterns (OAuth 2.0, JWT pass-through) and how to isolate data logically in multi-tenant shared databases.
- Clean Code Advocate: Demonstrated ability to write clean, unit-tested, and well-documented Python code, utilizing self-correction loops and graceful degradation patterns to handle model latency and API rate-limiting limits.
- Collaboration & Agile: Strong communication and collaboration skills, thriving in an agile, team-based environment.
Benefits:
- Medical
- Dental
- Vision
- Flexible Spending Accounts
- PTO
- Paid and Floating Holidays
- 401k with Company match and immediate vesting
- Company-funded Life Insurance
- Employee Assistance Programs
- No-cost Mental Health Benefits
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