AI Engineer

Talantir; New York (NY); On-site; USD 180,000 - 240,000; Full time

Job summary

Talantir is seeking an AI Full-Stack / Systems Engineer to design scalable backend services and platform components powering enterprise AI apps and agent-based workflows. You will focus on LLM integrations, AI orchestration, and production-grade AI infrastructure used by multiple teams.

You will collaborate with platform, architecture, and application teams to build secure, governed systems at scale, with emphasis on reliability, cost visibility, and safety controls.

Qualifications

• Backend and platform engineering experience required.
• Experience with distributed systems and microservices.
• Hands-on with LLMs, RAG architectures, or AI agent frameworks.
• Experience integrating AI APIs (OpenAI, Anthropic, Bedrock, etc.).
• Experience with AWS or other cloud platforms.
• Familiarity with vector databases and embeddings for retrieval.
• Proficient with RESTful APIs and containerization (Docker).

Responsibilities

• Build backend services supporting AI agents and multi-step AI workflows
• Develop LLM integration layers and model service APIs
• Implement RAG pipelines including document ingestion, embeddings, and vector retrieval
• Build orchestration frameworks connecting models, tools, and enterprise APIs
• Implement AI safety controls, guardrails, and policy enforcement
• Develop observability, monitoring, and cost tracking for AI systems
• Integrate AI systems with enterprise platforms and internal services

Skills

Backend engineering

Distributed systems

LLMs / RAG / AI agents

AI integrations

AWS / cloud platforms

Vector databases / embeddings

REST APIs / Docker

Tools

Docker

Job description

Role Overview

We are looking for an AI Full-Stack / Systems Engineer to build scalable backend services and platform components that power enterprise AI applications and agent-based workflows. The role focuses on LLM integrations, AI orchestration frameworks, RAG-based knowledge systems, and production-grade AI infrastructure used by multiple engineering teams. This engineer will work closely with platform, architecture, and application teams to build secure, reliable, and governed AI systems at enterprise scale.

Key Responsibilities

• Build backend services supporting AI agents and multi-step AI workflows


• Develop LLM integration layers and model service APIs


• Implement RAG pipelines including document ingestion, embeddings, and vector retrieval


• Build orchestration frameworks connecting models, tools, and enterprise APIs


• Implement AI safety controls, guardrails, and policy enforcement


• Develop observability, monitoring, and cost tracking for AI systems


• Integrate AI systems with enterprise platforms and internal services

Required Skills

• Strong backend engineering experience (Python preferred)


• Experience building distributed systems / microservices


• Hands-on experience with LLMs, RAG architectures, or AI agent frameworks


• Experience integrating AI APIs such as OpenAI, Anthropic, Bedrock, etc.


• Experience with cloud platforms (AWS preferred)


• Familiarity with vector databases, embeddings, and knowledge retrieval systems


• Experience with REST APIs, containerization (Docker), and modern backend frameworks

Preferred Skills

• Experience with LangChain, LlamaIndex, or agent orchestration frameworks


• Experience building AI platform components or internal developer platforms


• Exposure to AI governance, guardrails, and evaluation frameworks


• Experience operating systems in enterprise or regulated environments

Ideal Candidate

• 5-10 years backend / platform engineering experience


• Hands-on experience building production AI systems


• Strong problem solving and distributed systems background


• Comfortable working in AWS cloud-native environments