Gen AI Developer Specialist
Fa Etqo Saasfaprod1 Open · verified Oct 22, 2026 United States Full-time Mid-level AI Engineering
At a glance
Mid-level AI Engineering role at Fa Etqo Saasfaprod1. United States · full-time · no salary stated · we estimate $132,450–$205,151 across the United States.
Estimated pay
Fa Etqo Saasfaprod1 has not published a salary for this role. The figure below is our estimate, not theirs.
$132,450 – $205,151
What the middle half of mid-level AI engineering roles in the United States paid, among postings that did state a salary.
Worked out from 376 postings that stated pay, median $165,000. Last updated Oct 22, 2026.
RoleAI Engineering
SeniorityMid-level
LocationUnited States
EmploymentFull-time
PostedSep 3, 2026 · 7w ago
Role brief
aimlroles summary, based on the employer's posting.
What you'll do
- Build enterprise apps with React, TypeScript, JavaScript, Python and microservices, translating business needs into deployable code
- Create AI features with language models and agent frameworks, including copilots, virtual assistants and workflow automation
- Develop backend APIs and microservices that connect AI services with enterprise systems
- Design RAG systems that draw on vector databases and internal knowledge repositories
- Improve AI results with prompt and context techniques, and manage agent memory, monitoring and governance
What you bring
- You can develop with React, TypeScript, JavaScript and Python, and build around microservices
- You can create solutions with language models, generative AI services or agent frameworks
- You can build RAG systems that use vector databases and internal knowledge repositories
Who this fits
This role suits a mid-level AI engineer who can deliver application code and AI-enabled systems. You’ll work with product owners, architects, business analysts and development teams, and take part in Agile practices, code reviews, CI/CD and DevSecOps.
From the employer
Role: AI Engineer
Description:
- Design, develop, and maintain AI-powered enterprise applications using React, TypeScript, JavaScript, Python, and Microservices Architecture.
- Leverage GitHub Copilot, Claude Code, Amazon Q Developer, and other AI coding assistants to convert business requirements and user stories into production-ready code and pull requests.
- Architect and develop AI-enabled solutions using LLMs, GenAI services, and Agentic AI frameworks.
- Build scalable backend APIs and microservices integrating AI services with enterprise systems.
- Design and implement Retrieval Augmented Generation (RAG) solutions using vector databases and enterprise knowledge repositories.
- Develop conversational AI applications, copilots, virtual assistants, and intelligent workflow automation solutions.
- Implement Prompt Engineering and Context Engineering techniques to improve AI output quality, consistency, and performance.
- Build autonomous and semi-autonomous AI agents capable of orchestrating multi-step business processes.
- Design memory management strategies, including:
- Short-term Memory
- Long-term Memory
- Context Windows
- Token Optimization
- Integrate AI services using:
- Amazon Bedrock
- Claude
- OpenAI
- Other Foundation Model Platforms
- Develop event-driven architectures leveraging Kafka and cloud-native messaging services.
- Collaborate with Product Owners, Architects, Business Analysts, and Development teams to identify AI automation opportunities.
- Implement AI governance, observability, monitoring, and performance optimization practices.
- Participate in Agile development, code reviews, CI/CD automation, and DevSecOps processes.