Job Title: AI Engineer — Agentic & Production LLM Systems

Location: Remote

Overview:

As an AI Engineer, you will play a critical role in transforming powerful AI models and proprietary data into secure, production-grade, user-facing solutions. This is a unique opportunity to work at the intersection of AI, engineering, and product delivery, with access to high-value datasets, experienced leadership, and the autonomy to design and scale intelligent systems from the ground up.

You will partner closely with the CTO and cross-functional teams to orchestrate agent-based AI frameworks, embed intelligence into product workflows, and deliver measurable customer impact. Your work will directly shape how customers operate, solve problems, and create competitive advantage — while advancing best-practice standards in responsible AI.

Key Responsibilities:

• Design & Deliver Autonomous AI Systems
• Architect secure, agent-based AI tools leveraging solutions such as Claude Code, Model Context Protocol (MCP), A2A frameworks, Gemini CLI, OpenAI Agents SDK, and knowledge-graph concepts to solve complex, high-value problems
• Develop A2A Agent Systems
• Build frameworks enabling LLM-to-LLM collaboration internally and externally, extending the reach of enterprise-scale generative AI capabilities
• Bridge Product & Engineering
• Partner with Product, Engineering, and Customer teams to embed AI intelligence into tools that enhance usability, automation, and decision-making
• Build Secure API Integrations
• Develop scalable APIs connecting AI models with web apps, internal systems, and external platforms — including MCP-enabled agentic workflows
• Champion Responsible AI Practices
• Contribute to alignment strategies, ethical development standards, safety guardrails, and governance practices
• Scale Production AI Infrastructure
• Support MLOps pipelines, inference services, and shared AI services for enterprise deployment

Minimum Qualifications:

• Bachelor’s degree in Computer Science, Data Science, Machine Learning, or related field — or equivalent hands-on experience
• Significant experience building and deploying production-grade AI systems as a Software Engineer or Machine Learning Engineer
• Hands-on experience with:
• Large Language Models & Generative AI
• Agentic frameworks such as MCP, A2A, OpenAI Agents SDK
• Proven experience with AI infrastructure, inference services, and MLOps pipelines
• Strong foundation in AI safety, alignment, and ethical development principles

Preferred Qualifications:

• Master’s or PhD in a relevant technical discipline
• Experience with agent orchestration frameworks such as Claude Subagents, AutoGen, or CrewAI

Expertise in:

• Prompt & context engineering
• Retrieval-Augmented Generation (RAG)
• LLM optimization workflows
• Experience deploying open-source LLMs (e.g., Qwen, DeepSeek, Llama, Mistral, Gemma)
• Familiarity with cloud-based AI platforms including AWS Bedrock, GCP Vertex AI, Azure ML
• Experience integrating AI into legacy web apps, desktop apps, and API ecosystems

Why This Role Matters:

• Solve high-impact, revenue-driving problems
• Apply AI to mission-critical business challenges with measurable customer value
• Leverage proprietary data assets
• Build systems around exclusive, high-signal datasets
• Work with experienced AI leadership
• Collaborate directly with proven AI executives and product builders
• Startup innovation — enterprise stability
• Enjoy autonomy, pace, and impact — backed by strong resources and support