AI/Ml Engineer (Python, React)

Posted Recently

Full-time

Overview

Seeking an experienced AI/ML Engineer to lead rapid delivery initiatives across teams, architect production-grade generative AI applications, and mentor engineers in full-stack development and AI-augmented workflows. This role requires deep technical leadership, hands-on coding across the stack, and the ability to communicate effectively with stakeholders.

What You'll Do8

1Immerse in operations to acquire domain expertise and translate between business and engineering teams.
2Lead rapid delivery initiatives across teams, coaching on prototype-first approaches and establishing trust through consistent fast delivery.
3Architect RAG systems for complex use cases, implementing hybrid search, reranking, and query expansion techniques.
4Lead evaluation strategy across teams, establishing annotation guidelines, training human-calibrated LLM judges, and building evaluation pipelines that connect tracing to datasets to experiments.
5Optimize AI tool usage across teams, train engineers on AI-augmented and agentic engineering workflows, and evaluate new AI development tools.
6Design complex multi-component systems end-to-end, evaluate architectural options for large initiatives, and guide technical decisions.
7Define documentation standards, create documentation systems and templates, and train engineers on spec-driven development.
8Define reliability standards, drive post-incident improvements, and mentor engineers on SRE practices.

Requirements8

17+ years of relevant professional software engineering experience with full-stack delivery across backend and frontend.
2Deep production experience with Python AND JavaScript/TypeScript, working comfortably across the full stack.
3Hands-on experience architecting production generative AI applications including LLM integrations, vector databases, RAG systems, and evaluation pipelines.
4Strong experience with modern frontend frameworks (Next.js / React) and backend API development.
5Extensive experience with cloud platforms (AWS preferred; Azure/GCP valued), including infrastructure-as-code (CloudFormation / Terraform).
6Working knowledge of multiple database paradigms — relational (PostgreSQL), document, and key-value (Redis) — with ability to select the right storage per problem.
7Strong experience with CI/CD pipelines, containerization, and production deployment strategies.
8Demonstrable fluency with AI coding tools (Claude Code, Cursor, GitHub Copilot, or similar) and proven ability to design agentic engineering workflows and train teams on them.

Who Should Apply

This role is ideal for a staff-level full-stack engineer who thrives on leading multi-team technical initiatives, has deep production GenAI experience (RAG, LLMs, vector databases), and is passionate about mentoring and building high-performing teams. You should be comfortable working across the stack, from frontend (React/Next.js) to backend (Python/TypeScript) to cloud infrastructure (AWS/Terraform).

Salary Insight

Compensation is open to discussion.

Required Skills

ci/cd + containers, ai coding tools (claude code/cursor/copilot) & agentic workflowscloud (aws) + iac (terraform)consultingdatabases (postgresql/redis)frontend / fullstack developmentfull-stack (python + js/ts, react/next.js)multi-team tech leadership, strong stakeholder communication.production genai/rag (llm, vector dbs, eval pipelines),

Application Tip

In your application, highlight specific examples where you architected and deployed a RAG-based system in production, including details on the evaluation pipeline and how you balanced AI speed with verification rigor.