Sr Software Engineer

RadarFirst

Location
United States
Job Type
full-time
Salary
$120,000 – $145,000
Posted
October 29, 2025

Job Description

We are seeking a Senior Software Engineer (Engineer IV) with experience building AI-powered SaaS features and agentic solutions. This role is ideal for engineers who thrive at the intersection of application development and applied AI — delivering production-ready, customer-facing solutions that leverage large language models, generative AI, and cloud-native services.

As a Senior Engineer, you’ll design, develop, and ship AI-driven product features that make compliance and risk management smarter and more efficient. You’ll own major projects, mentor teammates, and work closely with architects to ensure our AI integrations are scalable, ethical, and secure.

This position can be based out of our HQ in Portland, OR, or remote from anywhere in the U.S.

Essential Responsibilities & Duties:

  • AI Development

    • Design and implement AI-driven features and agentic solutions using AWS Bedrock or equivalent AI platforms.

    • Integrate LLMs, retrieval-augmented generation (RAG), and workflow orchestration into SaaS products.

    • Ensure AI solutions meet standards of reliability, compliance, and ethical use.

  • Engineering Leadership

    • Own end-to-end delivery of major features or subsystems, from technical design through deployment and monitoring.

    • Mentor and support junior and mid-level engineers, raising the team’s AI development skills.

    • Contribute to architectural reviews, aligning with staff engineers on long-term AI strategies.

  • Full-Stack Product Development

    • Build and maintain SaaS applications using Angular, TypeScript, Node/NestJS, Go, and AWS services.

    • Collaborate with product, design, and data science teams to translate business needs into AI-enabled solutions.

    • Ensure high standards for code quality, scalability, and security.

Qualifications:

  • 7+ years of professional software engineering experience, including SaaS product delivery.

  • Proven experience developing production-ready AI features and/or agentic systems (AWS Bedrock strongly preferred).

  • Strong proficiency in at least one major programming language (TypeScript, Go, Python, etc.) and cloud-based environments (AWS preferred).

  • Demonstrated ability to design and deliver scalable APIs, microservices, and distributed systems.

  • Experience mentoring and leading engineers through technical challenges.

Research shows that people who identify as being from underrepresented groups are more likely to doubt the strength of their qualifications, so we encourage you to submit an application if you're interested in this role despite any reservations you may have about your background or skill set.

What is Nice to Have:

  • Familiarity with compliance, privacy, or regulated industry SaaS environments.

  • Experience with RAG pipelines, orchestration frameworks, or multi-agent AI systems.

  • Strong understanding of security and governance requirements for AI applications.

Who We Are

At RadarFirst, our mission is to make regulatory risk and data privacy simple, actionable, and sustainable.

We’re transforming how organizations handle incidents and compliance with automated, purpose-built SaaS solutions. Recognized as pioneers in privacy, we’ve earned patents, industry awards, and the confidence of some of the world’s most highly regulated industries, from healthcare and insurance to finance and beyond.

Our Values

Respect & Candor

Inclusion & Innovation

Integrity & Empathy

Why Join RadarFirst?

At RadarFirst, our team is filled with smart, thoughtful, and forward-thinking contributors who are experts at what they do.  Our culture of innovation and trust is paramount to our success. We work hard, but we also encourage and support a healthy work/life balance. We offer a generous package of benefits and perks that make RadarFirst a great place to work, including:

  • Comprehensive benefits that include medical and dental, 401k, Life and Disability insurance, generous flexible time off policy, paid holiday time, and 12 weeks paid parental leave. Plus flexible spending accounts for medical, dependent care, and commuter expenses
  • Community outreach programs to encourage giving back to our community both as a group and individually
  • Commitment to anti-racism work and accountability to our short-term and long-term equity & inclusion action plan

RadarFirst is a community-first organization, operating on a hybrid model. We actively support all employees working in the way they need. For those who wish to work from the office, these are some features of our downtown Portland office:

  • On-site amenities such as indoor bike racks, showers, lockers, and gym facilities
  • Casual work environment in an ideal central location, close to great food, shopping, and transportation options

This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. If E-Verify cannot confirm that you are authorized to work, this employer is required to give you written instructions and an opportunity to contact Department of Homeland Security (DHS) or Social Security Administration (SSA) so you can begin to resolve the issue before the employer can take any action against you, including terminating your employment. Employers can only use E-Verify once you have accepted a job offer and completed the Form I-9.

The salary range for this role is $120,000 – $145,000 annually.

🎯 Who is this job for?

This role is ideal for a Senior Engineer with 7+ years of experience in SaaS, strong in TypeScript, Node.js/NestJS, Go, or Python, and skilled in building AI-driven features using LLMs, RAG, and AWS Bedrock. Candidates should be comfortable leading projects, mentoring engineers, and working across the stack in a cloud-native (AWS) environment. Ideal for those passionate about secure, scalable AI applications in compliance-focused industries.

πŸ’¬ Potential Interview Questions

  1. How do you implement AI features using AWS Bedrock or similar platforms?
    I define workflows using orchestration tools, integrate LLMs via Bedrock APIs, and apply RAG techniques to ground responses in structured data, ensuring secure and compliant deployment.

  2. What are key design considerations when integrating agentic systems into SaaS products?
    Ensure agent autonomy is bounded, workflows are traceable, user intent is validated, and fallback logic handles hallucinations or model failures to maintain trust and compliance.

  3. How would you architect a scalable AI-powered feature in a microservice-based SaaS platform?
    I’d decouple the AI logic into a service, expose it via a secure API, use async messaging (e.g., SQS), cache static responses, and monitor usage/performance via AWS CloudWatch and X-Ray.

  4. Explain your experience with RAG pipelines and their use cases.
    I’ve used RAG to enhance LLM accuracy by retrieving relevant documents from a vector database (e.g., Pinecone), combining them with prompts for contextually accurate completions in compliance scenarios.

  5. How do you manage AI governance, ethical use, and model observability in production systems?
    By implementing logging for model inputs/outputs, rate limiting, human-in-the-loop review, prompt testing, and ensuring audit trails meet security and regulatory standards.

  6. What strategies do you use for mentoring mid-level engineers on complex AI integrations?
    I conduct architecture walkthroughs, encourage pair programming on key AI features, assign ownership of POCs, and review their implementation with structured, actionable feedback.

  7. How do you ensure front-end and back-end systems work seamlessly in full-stack AI features?
    Align contracts through shared API documentation (e.g., Swagger), ensure data schemas are validated both ends, and test features end-to-end using mocks and staging environments.

  8. Describe a time you implemented a multi-agent AI workflow.
    I built a multi-agent system where each agent had specialized roles (e.g., data extraction, risk classification), orchestrated via LangChain, passing context iteratively with checkpoint validations.

  9. What makes TypeScript and NestJS well-suited for AI-integrated backends?
    TypeScript ensures type safety in dynamic LLM interactions, and NestJS’s modular architecture supports clean separation of services, guards for security, and integration with AWS-native tooling.

  10. How would you design an AI-powered compliance assistant for real-time data breach reporting?
    Use Bedrock for LLM tasks, integrate with case data via RAG, provide real-time suggestions in UI via Angular, and log all actions for compliance, with human override for legal review.

πŸ“‹ Job Summary

RadarFirst is hiring a remote Senior Software Engineer (U.S.-based) to lead development of AI-powered SaaS features that enhance compliance and risk management. You'll work with LLMs, AWS Bedrock, TypeScript, Node.js, Angular, and Go to build secure, scalable AI integrations and agentic systems. The role offers $120K–$145K, full benefits, and the chance to shape privacy tech at a mission-driven company serving highly regulated industries. Join a collaborative team driving innovation where ethical AI and purpose-built solutions are at the core.

Required Skills

TypeScript Node.js NestJS Go

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