Job Overview:You'll be joining our Mitratech Workforce Compliance Engineering team, building AI-first SaaS products. This role sits at the intersection of two disciplines. First, you'll build the AI features our customers use every day: LLM-powered workflows, retrieval over compliance content, and agents that take action inside our products. Second, you'll help lead how we build software, using agentic, pipeline-driven development in which AI coding agents plan, write, test, and review code under strong engineering oversight.
We hold both to the same bar: high quality (low escaped defects), well tested (Cypress automation framework with focus on unit test coverage), secure (scanned and verified), scalable (AWS, but hardware isn't the answer), and measurably accurate when AI is involved. This is a great opportunity to join a growing company, be part of an excellent team, architect solutions to complex problems, and deliver valuable features where clean code, and trustworthy AI, matter.
Essential Duties & Responsibilities:Agentic, Pipeline-Driven Development- System Design & Task Decomposition: Break down high-level product goals into well-defined, modular engineering tasks with clear specifications and acceptance criteria that can be executed by both engineers and AI coding agents.
- Agentic Development Pipelines: Develop and optimize CI/CD pipelines that incorporate AI agents for code generation, automated testing, and intelligent code review, with guardrails, quality gates, and clear human approval points.
- Specification & Context Engineering: Design and test structured instructions, prompts, specifications, and repository context (e.g., agent instruction files, reusable skills, MCP tools) that drive accurate, context-aligned output from AI agents, and measure and improve agent output over time.
- Code Review & Validation: Conduct in-depth reviews of both human and AI-generated code, ensuring quality, security, scalability, and alignment with domain requirements.
- Architectural Oversight: Ensure design plans created by both human engineers and AI tools adhere to architectural best practices with a focus on modularity, bounded contexts, etc.
- Documentation and Domain Clarity: Contribute to the development of domain models, technical documentation, and internal knowledge bases that support AI agent performance and team activity.
Engineering Excellence & Teamwork- Write secure code. Avoid introducing an OWASP vulnerability, including those in the OWASP Top 10 for LLM Applications. Know how APIs are secured, sessions are handled, and data is validated properly.
- Serve in an on-call rotation (DevOps philosophy where you will participate in ops) and respond promptly to any production issues, including AI feature degradations, to remediate rapidly.
- Be a teammate, help other teammates resolve complex problems or think through design/architecture challenges. Be available and responsive.
- Mentor others and foster an excellent engineering culture based in trust, accountability, character, and honesty, including coaching teammates on using AI agents effectively and responsibly.
- Seek feedback and deliver constructive criticism (e.g., code reviews) in a tactful and empathetic manner; build others up and mentor without ego.
Your Qualifications:Required- Possess a bachelor's degree, or equivalent experience. Emphasis in engineering, data science, computer science or information systems is preferred.
- Have a minimum of 5 years of software engineering experience developing SaaS applications, with strong hands-on experience in our stack: Python, React, AWS (Lambda, DynamoDB).
- Hands-on experience with LLM application patterns: prompt design, embeddings and vector search/RAG, tool/function calling, structured outputs, and agent orchestration.
- Demonstrated experience delivering software with AI coding agents such as Claude Code, Devin, or Codex as a core part of your workflow, including integrating agents into CI/CD pipelines with automated quality gates.
- Experience designing evaluation and testing strategies for non-deterministic systems, and the judgment to decide when AI is, and is not, the right solution.
- Strong fundamentals in system design, API security, automated testing, and multi-tenant SaaS architecture.
- Clear, precise written communication: specs and documentation that both people and AI agents can act on.
Preferred- Experience with managed model platforms and provider APIs (e.g., Amazon Bedrock, Anthropic, OpenAI) and agent frameworks or SDKs.
- Have shipped at least one AI/LLM-powered feature to production in a SaaS product and supported it after launch (monitoring, evaluation, and iteration based on real usage).
- Experience building MCP servers or other tool integrations for AI agents.
- Background in regulated domains (HR, legal, risk, or compliance) and with data privacy and security standards (e.g., SOC 2, GDPR, CCPA).
- Familiarity with AI risk and governance practices (e.g., NIST AI RMF, OWASP Top 10 for LLM Applications).
- Experience with spec-driven development.
Our Technology Stack:- Python, React
- AWS (Lambda, DynamoDB, SQS, S3, CloudFront, API Gateway)
- Containerized environments with CICD pipelines, RESTful APIs, etc.
- LLM, RAG, and MCP components powering in-product AI features
- AI coding agents integrated into the development lifecycle with automated quality gates
Benefits we offer:- Health, Dental & Vision Insurance *
- 401 (k) + Employer Match *
- Open PTO + 11 Paid Holidays + 4 Annual Paid Global Wellness Days Off
- STD, LTD & Group Life Insurance
- Paid Parental Leave
- Pet Insurance
- FSA & HSA Options
- Employee Assistance Program
Perks we offer:- Remote Work
- Career Advancement & Professional Development Opportunities
- Employee Recognition
- LinkedIn Learning Platform
