# Full Stack AI Engineer (Senior Level)

**Company:** [Pareto AI](https://hotfix.jobs/companies/pareto-ai)
**Location:** Remote
**Role:** Fullstack Engineering
**Experience:** 10+ years
**Skills:** Python, TypeScript, AWS, GCP, Terraform, Temporal Cloud, LLMs, RAG, Vector Stores, Semantic Search, Agentic Workflows, Multi-Agent Orchestration, Distributed Systems, Containerization, Data Pipelines
**Posted:** 2026-04-08

> Leads design and architecture of production AI systems including agentic workflows, RAG, and LLM applications for scalable company automation. Requires 10+ years full-stack engineering with deep AI/ML production experience.

## Job Description

## Responsibilities
- **Design Leadership**: Own and lead complex system design discussions, architectural decisions, negotiate and shape builds.
- **Feasibility & Scoping**: Assess technical feasibility of AI product ideas, produce scoping documents to prevent scope creep.
- **Technology & Frameworks**: Define tech stacks, build reusable frameworks, establish engineering guidelines.
- **Experimentation**: Build prototypes, align with stakeholders, evaluate early signals to kill or accelerate.
- **Cross-functional Collaboration**: Partner with research, operations, data teams; juggle workstreams and tradeoffs.
- **Excellence**: Build scalable systems, lead AI application evaluation practices.

## Qualifications
- Staff-level with 10+ years software engineering experience owning complex systems end-to-end.
- Strong full-stack engineer with extensive AI/ML experience; systems, architecture, tradeoffs focus.
- Design ambiguous problems into reliable, scalable AI harnesses; lead design discussions.
- Production AI systems: agentic workflows, multi-agent orchestration, HITL pipelines, LLM apps, RAG, vector stores, semantic search, multi-model stacks.
- Context engineering for AI limitations.
- Distributed systems in AI/data platforms.
- Agentic coding proficiency to boost output.
- Quick learner across technical domains.

## Nice to Have
- Experience at AI data companies (Scale AI, Surge, Snorkel, Labelbox) building synthetic data pipelines, eval environments, task generation.
- Human data labeling interfaces, annotation workflows, data collection pipelines.
- Preference data, reward models (RLHF, RLVR).
- Proficiency: Python, TypeScript, AWS, GCP, Terraform, Temporal Cloud, containerization, LLM gateways, RAG frameworks, data pipeline tooling.

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**Apply:** https://hotfix.jobs/jobs/4609821d-c802-4261-8c27-799df69f1338
**Canonical:** https://hotfix.jobs/jobs/4609821d-c802-4261-8c27-799df69f1338