Novara provides safety and operational risk management software that empowers organizations to identify and resolve issues before they become incidents. Through the Flex and Risk Management Center platforms, Novara helps organizations address operational risk proactively by unifying data, increasing workforce engagement, and proactively managing risk. Novara’s combination of training, software, and tools puts people and safety first while protecting critical operations.

Position Description:

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. We are seeking a highly motivated, hands-on, production-proven Senior Applied AI Engineer to drive the technical realization of our Agentic AI Platform. In this role, you will lead the design, development, and scaling of this platform, transforming our mature, traditional Enterprise EHS/ESG SaaS system (Flex) into a dynamic, AI-native system of intelligence and action. You are a developer-first engineer who is 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. You have built and shipped enterprise-grade AI products to production, managing the real-world challenges of multi-tenancy, PII redaction, token costs, latency, and model hallucination.

### Knowledge, Experience, 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 passthrough) 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.

Nice-to-Haves: The following experience will be highly valued:

• Machine Learning & Predictive Modeling: Practical experience training and serving classical ML models (e.g., Isolation Forest, One-Class SVM, or unsupervised clustering) for behavioral baselining, anomaly detection, or predictive risk scoring.

• Experience developing React-based micro-frontends or canvas-style Generative UI layouts.

• Contributions to the open-source Model Context Protocol (MCP) ecosystem.

• Background in EHS (Environmental Health & Safety) or ESG (Environmental, Social, and Governance)

software systems.

• AWS Certified Machine Learning – Specialty or AWS Certified Solutions Architect – Professional.

### Success Criteria:

• Core AI & Orchestration - Key expectations for AI platform engineering:

• Agentic State Machines: Design and implement complex, multi-agent state machines and stateful

graphs using LangGraph and LangChain to support autonomous decision-making and self-correcting

loops.

• Dynamic Agent & Workflow Registries: Architect database-driven registries (using PostgreSQL) to

dynamically discover, load, and configure agent definitions, system prompts, and task workflows at

runtime without redeploying code.

• Optimized LLM Routing: Build intent-based routing engines that evaluate user queries and direct them to either deterministic execution layers (e.g., Python code interpreters running over in-memory DataFrames) or semantic retrieval layers (RAG).

• Observability & Cost Tracking: Configure centralized telemetry pipelines and AI Gateways for token tracking, caching, rate limiting, and real-time streaming of internal graph execution traces (via ServerSent Events).

• Advanced RAG & Data Engineering - Key expectations for data pipelines and search systems:

- Production-Grade RAG on AWS: Build and maintain a dual-engine vector search architecture: Amazon OpenSearch Serverless for unstructured policy, regulation, and SOP document retrieval, and PostgreSQL + pgvector for structured transactional logs, incident histories, and audit records.

- Serverless Ingestion Pipelines: Build scalable, event-driven ingestion pipelines using AWS S3, SQS, EventBridge, and AWS Fargate to parse raw documents (PDF, Word, CSV) into Markdown.

- Context Preservation & Visual RAG: Implement advanced chunking strategies, including slidingwindow paragraph overlaps, header breadcrumb perpetuation, and Vision Transformer (ViT) visualenrichment models to summarize embedded charts, diagrams, and stamps.

- Automated PII Redaction: Integrate Amazon Comprehend or custom LLM classifiers inside the Fargate worker container to scrub names, emails, and SSNs before data is indexed.

• EHS Integration & MCP - Key expectations for security, integration, and guardrails:

- Model Context Protocol (MCP) Servers: Build standardized, decoupled MCP servers that wrap legacy REST APIs (Java/C# backends), exposing databases, schemas, and actions as dynamically discoverable tools for the AI agents.

- Prompt-Independent Security (RBAC): Implement user-delegated token pass-through (JWT forwarding) so that data-access permissions are enforced mechanically by the legacy API. Design hard metadata filters (where tenant_id = jwt.tenant_id) in OpenSearch and pgvector to ensure multi-tenant isolation.

- HITL Write Guardrails: Configure Human-in-the-Loop (HITL) state breakpoints in LangGraph to halt write-mutations, broadcasting the pending action to administrators for UI-based approval.

• Generative UI Layouts - Key expectations for UI integration:

- Dynamic Component Rendering: Design structured JSON widget schemas (representing tables, Recharts graphs, checklists, and forms) generated dynamically by the backend agents to enable zerostate rendering of layouts in the Next.js UI.

### Compensation:

Annual Base Salary Range of CA$144k-165k

Annual Bonus Opportunity of 10%

As a growing company, Novara values its employees by supporting them with a full benefits package including 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, and No-cost Mental Health Benefits.

About Novara

Novara, a Providence Equity portfolio company, provides safety and operational risk management software that empowers organizations to identify and resolve issues before they become incidents. Through the Flex and Risk Management Center platforms, Novara helps organizations address operational risk proactively by unifying data, increasing workforce engagement, and proactively managing risk. Novara’s combination of training, software, and tools puts people and safety first while protecting critical operations.

Novara launched January 1 2026, as an independent company, a spin-off of the Flex and RMC software businesses formerly part of KPA.

Don’t meet every job requirement? At Novara, we are dedicated to building a diverse, inclusive, and authentic workplace. Studies have shown that women and people of color are less likely to apply unless they meet every requirement. If you’re excited about the role but your past experience doesn’t align perfectly with every qualification, we still encourage you to apply! You might just be the right candidate for this or other roles.

Please note that we may use AI tools to assist in the initial screening of resumes to help identify qualified candidates more efficiently. All decisions are reviewed by a human recruiter, and no hiring determination is made solely by automated means.

Novara is committed to providing equal opportunity in all of our employment practices, including selection, hiring, promotion, transfer, and compensation, to all qualified applicants and employees without regard to race, religion, religious dress/grooming, color, ethnicity, sex (including sex stereotyping), sexual orientation, gender identity or gender expression, national origin, ancestry, citizenship status, creed, uniform service member status, military or veteran status, marital status, pregnancy, breast-feeding and/or pregnancy-related conditions, age, protected medical condition, leave status, physical or mental disability, genetic characteristics, or any other legally-protected status in accordance with the requirements of all federal, state and local laws.

Senior Applied AI Engineer

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