AI Integration Engineer

We at P99soft are looking for an AI Integration Engineer who builds, deploys, runs, and optimizes agentic AI tools and pipelines. This role requires solid applied AI knowledge and some product understanding but does not require building custom training pipelines or deep foundational research work; that responsibility sits with the AI architect.

Responsibilities:

• Build, deploy, and run agentic AI tools and pipelines in production; retrieval-augmented generation systems, agentic bots, semantic search, and related tooling.
• Optimize existing AI tools for reliability, performance, and cost, working within an architecture defined by the AI Architect.
• Debug applied AI/systems issues as they arise in production, including model-serving failures and library/dependency or version compatibility problems.
• Collaborate with the AI architect on implementation of system design decisions and with product/GTM stakeholders on what's technically feasible to support adoption goals.
• Contribute to expanding tooling into adjacent areas as scope grows.

Requirements:

• Applied, hands-on AI experience is non-negotiable: genuine experience building or integrating generative/agentic AI systems (LLMs, RAG, vision models), not just using AI assistants as an end user.
• Practical engineering skill in deploying and running AI systems in production, comfortable with the full build-deploy-optimize lifecycle for agentic tools.
• Some depth in AI systems internals, able to debug lower-level issues such as model serving cache failures or library/version compatibility problems, not just call existing APIs.
• Working understanding of generative/applied AI as distinct from traditional data science (regression, classification).
• Background can come from startup, founder, or self-taught paths; a traditional AI/data science pedigree is not required if applied AI fundamentals are genuinely strong.

Nice to Have:

• Some product understanding/awareness of how tools get adopted by end users, even though this is primarily an engineering role.
• Experience operating in a regulated, quality-driven, or highly technical enterprise environment.

Skills

AI, LLMs, Production, RAG, Vision