Tech Lead, Agentic Engineering

Sema4.ai; Atlanta (GA); On-site; USD 120,000 - 160,000; Full time

Job summary

A technology company specializing in AI platforms is seeking a Technical Lead to architect and enhance their enterprise AI systems. In this role, you will spend considerable time hands-on with Python, setting technical direction and mentoring senior engineers. The ideal candidate has over 10 years of software engineering experience, including technical leadership and AI/ML application. Strong communication skills to convey complex AI concepts are essential. This position requires a deep understanding of the evolving AI landscape.

Qualifications

• 10+ years of experience in software engineering with 3+ years in AI/ML applications.
• Proven ability to influence architecture and guide teams.
• Strong communication skills for explaining complex AI concepts.

Responsibilities

• Lead technical implementation with hands-on Python coding.
• Define technical standards and review critical code.
• Design agent framework and LLM integration patterns.
• Mentor senior engineers and elevate team expertise.

Skills

GenAI Expertise

Technical Vision

Hands-On Coding

Leadership

Communication Skills

Tools

Python

Job description

The Opportunity

At Sema4.ai, we're building an Enterprise AI Agent platform that reinvents how knowledge work happens—how people and AI agents collaborate to get work done better and faster. You'll be the hands‑on leader responsible for building the core of our product: the Agent framework.

We're looking for a Technical Lead who can architect cutting‑edge AI systems while remaining hands‑on with implementation. You'll guide the technical direction of our agent framework while mentoring senior engineers and driving engineering excellence across the team.

Who You Are

• GenAI Expert: You understand how to use LLMs (and other cutting‑edge models) to do useful work. You know the common challenges around using LLMs in enterprise settings, the most useful context management strategies, prompting strategies, and the nitty‑gritty API‑level details such as tool use, prompt caching, multi‑modality, structured outputs, model‑provider‑specific differences, etc. You know the difference between top‑p and temperature and you’ve maybe seen emerging works (like min‑p). You use this significant base of understanding to drive useful outcomes in unique ways that non‑experts in GenAI simply can’t.
• Technical Visionary: You can see around corners in the AI space. You understand not just current capabilities but where the field is heading. You make architectural decisions that will scale as models improve. You’ve grown with the field, tracking key changes, and implementing them when they make sense (avoiding the hype and creating clarity through your vision). You’re the kind of person who may have skipped on GraphRAG after a closer look, anticipated the emergence of truly long context models, and paid close attention to Anthropic’s excellent blog on SOTA retrieval techniques.
• Hands‑On Builder: You write production code daily. You lead by example, contributing to the most challenging technical problems while establishing patterns for others to follow. You act as a force multiplier to the team around you.

What You’ll Do

• Lead Technical Implementation: Spend at least 50% of your time hands‑on with Python code, building core platform capabilities, optimizing LLM performance, and solving complex technical challenges.
• Set Technical Direction: Define technical standards, review critical code, and ensure architectural decisions align with our product vision. Guide the team on best practices for building AI‑native applications.
• Drive AI Architecture: Design and implement our agent framework, orchestration systems, and LLM integration patterns. Make critical decisions about model selection, prompt strategies, and system architecture.
• Mentor & Elevate: While not necessarily managing people directly, you'll mentor senior engineers, conduct technical reviews, and help the team level up their AI and systems expertise.

What You Bring

• 10+ years of experience in software engineering including 3+ years applying AI/ML in practice, and 3+ years in a technical leadership position.
• Technical Leadership: Proven ability to drive technical decisions, influence architecture, and guide teams without formal authority. You lead through expertise and example.
• Communication Skills: Ability to explain complex AI concepts to various audiences and document architectural decisions clearly.