Senior Product Engineer, AI & Platforms

MJH Life Sciences®

1d•$100,000 - $125,000•Remote

About The Position

At MJH Life Sciences our success is measured by your success! If you set your standards high and want to contribute to a winning team, we’ll provide you with every opportunity to help grow our company and your career. Our associates come from all backgrounds, sharing one key quality: determination to succeed. We value being Service Focused, having a Passion for Winning, Innovation, Respect, Integrity, and Teamwork. Nothing means more to us than hiring people with these attributes. If you believe you’re right for the job, this is the place to prove it! We are seeking a Senior Product Engineer to join our Enterprise Platforms team. You'll work across a wide range of projects — web applications, APIs, integrations, cloud infrastructure, and AI-powered workflows — collaborating with stakeholders to understand real problems and build solutions that make a meaningful difference. This role goes beyond writing code. You'll be involved from problem definition through delivery, with genuine ownership over what you build and how you build it. We're an AI-first team, and you'll use tools like Claude Code and Cursor as a natural part of your daily workflow. If you care about outcomes, not just output, this is the role for you.

Requirements

You own deliverables end-to-end — from understanding the problem through architecture, implementation, deployment, validation, and iteration. No one needs to check on you
3+ years of experience building and shipping web applications or platform services
Proficiency in TypeScript and Python, with experience in React/Next.js for frontend and FastAPI or similar for backend services
Working knowledge of AWS services (Lambda, API Gateway, DynamoDB, Secrets Manager, or equivalent) and experience with Docker and containerized workflows
Experience with PostgreSQL and an ORM (Prisma, SQLAlchemy, or similar)
Comfort working with LLM APIs (Anthropic, OpenAI, or similar) — including prompt engineering, evaluating model outputs, and integrating AI capabilities into applications
Familiarity with OAuth 2.0 flows and secure API authentication patterns
Strong written communication — you can write a clear recommendation doc, not just code

Nice To Haves

Experience with enterprise platform APIs (Salesforce, Workfront, Workday, or similar) preferred
Familiarity with serverless architectures and Infrastructure as Code (AWS CDK, Serverless Framework, Terraform) preferred
Experience using AI-assisted development tools (Claude Code, Cursor, Windsurf, or similar) as a core part of your daily workflow preferred
Background in healthcare, life sciences, or media industries a plus

Responsibilities

Build and ship web applications using Next.js, React, and TypeScript — dashboards, internal tools, and stakeholder-facing products backed by PostgreSQL and deployed to Vercel or AWS
Design and deploy APIs and integration services on AWS (Lambda, API Gateway, DynamoDB, Secrets Manager) that connect enterprise systems including Salesforce, Workfront, Workday, and other platforms
Integrate LLM capabilities into products — prompt engineering, multi-model orchestration, streaming responses, embeddings, and cost-optimized AI pipelines using Anthropic Claude, OpenAI, and Google APIs
Develop developer tools and automation that improve team productivity and enable AI-assisted workflows, including CLI tools, MCP servers, automation scripts, and internal tooling
Implement OAuth 2.0 flows, secure credential management, and compliance-aware data handling across all integration points
Own cloud infrastructure using Infrastructure as Code (AWS CDK, Serverless Framework) — you deploy what you build
Gather requirements directly from stakeholders, push back when the ask doesn't match the real problem, and write up recommendations when you identify a better approach
Follow up after launch — confirm features are being used, measure whether they achieved their goal, and iterate based on real feedback
Contribute to team growth by helping peers troubleshoot, sharing technical knowledge, and participating in AI Accelerator discussions