Tech Lead | AI Engineering
Tech Lead, Agentic Engineering | Enterprise AI Platform | Atlanta (Remote)
A well-funded AI company is building the infrastructure that defines how enterprise knowledge work gets done. Their product is an AI agent platform used by large organizations to deploy autonomous workflows at scale. This isn't an AI wrapper business. They're building the framework layer itself.
They're hiring a Technical Lead to own the architecture and implementation of their core agent framework. This is a hands-on role - at least 50% in Python - while setting technical direction and mentoring a team of senior engineers.
The Role
Designing and building the agent orchestration framework, LLM integration patterns, and core platform capabilities. Making real decisions on model selection, prompt strategy, context management, and system architecture. Reviewing critical code, defining technical standards, and keeping the team sharp on AI-native best practices.
What They Need to See
Production agentic systems. Not prototypes. Not chatbots. Systems where LLMs make multi-step decisions, call tools, manage state, and handle real enterprise constraints around cost, latency, hallucination, and compliance.
Concretely: LangGraph or equivalent, tool-use / function-calling, RAG at scale, evals-as-code, prompt CI/CD, and genuine depth on LLM internals (context strategies, structured outputs, model-provider tradeoffs, inference optimization).
10+ years in software engineering, 3+ years applying AI/ML in production, 3+ years in a technical leadership role.
What They're Not Looking For
Copilot-heavy profiles with no production AI underneath. Q&A chatbots with no tools or state. Research experience that never shipped. Vague "AI transformation" roles where someone oversaw a vendor deployment.
Why It's Worth Considering
Greenfield technical scope on a product that's genuinely at the frontier. The successful candidate's architectural decisions will define how the platform scales as models improve. Direct access to leadership. Competitive comp.
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A well-funded AI company is building the infrastructure that defines how enterprise knowledge work gets done. Their product is an AI agent platform used by large organizations to deploy autonomous workflows at scale. This isn't an AI wrapper business. They're building the framework layer itself.
They're hiring a Technical Lead to own the architecture and implementation of their core agent framework. This is a hands-on role - at least 50% in Python - while setting technical direction and mentoring a team of senior engineers.
The Role
Designing and building the agent orchestration framework, LLM integration patterns, and core platform capabilities. Making real decisions on model selection, prompt strategy, context management, and system architecture. Reviewing critical code, defining technical standards, and keeping the team sharp on AI-native best practices.
What They Need to See
Production agentic systems. Not prototypes. Not chatbots. Systems where LLMs make multi-step decisions, call tools, manage state, and handle real enterprise constraints around cost, latency, hallucination, and compliance.
Concretely: LangGraph or equivalent, tool-use / function-calling, RAG at scale, evals-as-code, prompt CI/CD, and genuine depth on LLM internals (context strategies, structured outputs, model-provider tradeoffs, inference optimization).
10+ years in software engineering, 3+ years applying AI/ML in production, 3+ years in a technical leadership role.
What They're Not Looking For
Copilot-heavy profiles with no production AI underneath. Q&A chatbots with no tools or state. Research experience that never shipped. Vague "AI transformation" roles where someone oversaw a vendor deployment.
Why It's Worth Considering
Greenfield technical scope on a product that's genuinely at the frontier. The successful candidate's architectural decisions will define how the platform scales as models improve. Direct access to leadership. Competitive comp.
Apply tot his job
Apply To this Job