About the Position

Forward Deployed AI Engineer

Salary: $200k – $280k
Location: Atlanta, Georgia, United States; Austin, Texas, United States; Boston, Massachusetts, United States
Experience: 5+ years
Employment Type: FULL_TIME
Remote: Yes

About the Role

We are looking for a senior, hands-on engineer who knows how to make AI systems work beyond the demo. As a Forward Deployed AI Engineer, you’ll embed with client teams and take ownership of LLM-powered systems from architecture through production. You’ll work on problems where behavior isn’t perfectly deterministic and where reliability has to be engineered rather than assumed.

Responsibilities

Build and own production AI systems
- Design, develop, deploy, and operate LLM-powered applications and services.
- Make architectural decisions across models, infrastructure, data, reliability, latency, and cost, and continue owning those decisions after launch.
Build reliable RAG and agentic systems
- Develop and improve retrieval pipelines across ingestion, chunking, retrieval, reranking, grounding, and evaluation.
- Design agents that safely interact with tools, APIs, and enterprise data. Debug failure modes such as looping, incorrect tool usage, poor grounding, and hallucinated actions.
- Recognize when an agent isn’t the right solution.
Measure AI behavior
- Build evaluation systems that combine offline testing, production signals, and human feedback.
- Create ways to detect behavioral regressions caused by model changes, prompts, retrieval quality, or shifting data.
- Instrument systems so that when something goes wrong, the team can understand why.
Operate what you build
- Deploy AI systems into real cloud environments with monitoring, CI/CD, versioning, rollout strategies, and rollback mechanisms.
- Manage model and provider changes without treating production like an experiment.
- Keep an eye on economics too. AI systems need to be reliable, but they also need to make financial sense at scale.
Work directly with clients
- Work with client engineers, technical leaders, product teams, and business stakeholders to turn ambiguous problems into technical decisions and working systems.
- When something breaks, understand the problem, communicate it clearly, and lead the path toward a solution.

Requirements

Experience
- 5+ years building and operating production systems.
- Shipped and owned LLM-powered systems in production, not just prototypes.
- Dealt with hallucinations, retrieval failures, or agent misbehavior beyond prompt tweaks.
- Built or maintained LLM evaluation pipelines and know their limits.
- Understand model drift, data drift, and behavioral regression in live systems.
Skills
- Strong in Python and comfortable building backend services, pipelines, and workers.
- Real experience with cloud infrastructure, CI/CD, monitoring, and incident response.
- Can explain to stakeholders why AI systems fail - without hiding behind hype.
- Value intellectual honesty, low ego, and responsibility when things break.

Nice to Have

Experience with Machine Learning, Kubernetes, MLOps, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI.

We Offer

Impact: Build AI systems that enterprises actually rely on.
Autonomy: Own delivery end-to-end, not tickets.
Variety: Work across industries and problem types.
Growth: Sharpen both engineering judgment and client-facing instincts.
Culture: High competence, low ego, strong opinions loosely held.

About the Company

tribe.ai

We embed elite AI engineers to ship real, production-grade AI for enterprises.

Employees: 51-200
Location: New York City
Funding: $37,000,000 Series A - Jul 2024
Perks: Fully Remote, work from anywhere in the U.S. with a remote-first team built around trust, autonomy, and flexibility.

Why Join Us

Impact: Build AI systems that enterprises actually rely on.
Autonomy: Own delivery end-to-end, not tickets.
Variety: Work across industries and problem types.
Growth: Sharpen both engineering judgment and client-facing instincts.
Culture: High competence, low ego, strong opinions loosely held.

Forward Deployed AI Engineer

Job description