Senior AI Application Engineer

About the role

The Senior AI Application Engineer is a senior technical builder and architect responsible for designing, building, and deploying production-grade AI-powered tools, automations, and intelligent systems across Channel Partners.

Responsibilities

• Own the full lifecycle of AI application development — from technical scoping and architecture through build, testing, deployment, and ongoing maintenance.
• Design and implement production-grade AI-powered tools including LLM-integrated workflows, intelligent automations, internal assistants, chatbots, and RAG-based retrieval systems.
• Define and enforce AI architecture standards — selecting frameworks, establishing integration patterns, and documenting decisions the broader engineering team can build on.
• Lead technical discovery with internal stakeholders — translating ambiguous business problems into clear, scoped engineering specifications.
• Support LLM training, fine-tuning, and private/on-prem deployment in secure, closed environments where required.
• Evaluate and recommend AI tooling, frameworks, and infrastructure; stay current with the rapidly evolving LLM and agentic AI landscape.
• Build and maintain evaluation frameworks to measure AI tool performance, accuracy, latency, and cost at scale.
• Mentor junior engineers and serve as a technical resource for the broader team on AI architecture, prompt engineering, and best practices.
• Produce thorough technical documentation: architecture decisions, integration patterns, deployment guides, and operational runbooks.

Requirements

Experience and Education:

• Bachelor’s degree in Computer Science, Engineering, or related technical field — or equivalent demonstrated expertise through shipped work.
• Portfolio of production AI applications required; GitHub, deployed tools, or detailed project case studies strongly preferred.

Technical Experience:

• 4–8+ years of software engineering experience, with 2–3+ years focused on production AI/LLM application development.
• Deep hands-on experience with LLM frameworks — LangChain, LangGraph, LlamaIndex, OpenAI/Anthropic SDKs, Hugging Face; able to reason about trade-offs across them.
• Demonstrated experience building and deploying RAG systems — including vector database selection, chunking strategies, hybrid search, and evaluation pipelines.
• Experience with agentic AI architectures — multi-agent systems, tool use, memory, and orchestration patterns.
• Strong Python engineering — clean, testable, production-quality code; JS/Node.js a plus.
• Experience deploying LLMs or AI tools in private/closed environments (on-prem, private cloud, VPC); security-conscious design.
• Experience with automation platforms (n8n, Make, Zapier) and API integration patterns.
• Experience with CI/CD pipelines and cloud environments (AWS, GCP, or Azure).

Qualifications

• Architectural judgment — knows when to use RAG vs. fine-tuning, LangChain vs. custom orchestration, agent vs. workflow; makes defensible technical decisions.
• Senior builder instinct — moves from ambiguous problem to working architecture quickly, without needing the spec handed to them.
• Production mindset — builds for reliability, observability, and maintainability, not just for the demo.
• Techical communicator — explains trade-offs clearly to non-technical stakeholders and writes documentation that actually gets used.
• Multiplier — elevates the engineers around them through code review, mentorship, and shared standards.

Skills and Attributes

• Experience with AI & LLM Frameworks: LangChain, LangGraph, LlamaIndex, OpenAI / Anthropic SDKs, Hugging Face, Ollama, RAG patterns, vector databases, LLM fine-tuning and eval frameworks.
• Experience with Automation & Integration: n8n, Make (Integromat), Zapier, REST APIs, Webhooks, CI/CD pipelines, marketing automation platforms.
• Languages & Infrastructure: Python (required), JavaScript/Node.js, Docker, Git, AWS / GCP / Azure (working knowledge), prompt engineering, agent architecture.

Benefits

• Health and wellness benefits plans
• Flexible vacation and holiday policies
• Paid parental leave
• 401(k) with employer matching
• Technology allowance
• Referral bonus
• Tax savings with flexible spending accounts for parking, transit, dependent care, and healthcare costs
• Opportunity to work with a growing company that actively rewards and promotes its employees

Pay

Minimum Pay USD $120,000.00/Yr. Maximum Pay USD $140,000.00/Yr.

Schedule

Hybrid, remote-flexible work model with opportunities for onsite collaboration as needed. Minimal travel is expected.