What are the responsibilities and job description for the Applied Research Engineer (LLMs / AI Systems / Agentic Frameworks) position at Lawrence Harvey?
About the Opportunity
I’m currently partnering with a high-growth, venture-backed AI company operating at the intersection of:
- Responsible AI
- AI Safety & Governance
- High-stakes, decision-critical systems
This team is building production-grade AI systems used in complex, real-world environments where accuracy, reliability, and explainability are critical.
Rather than focusing on surface-level AI use cases, they are tackling deep technical challenges around evaluation, control, and scalable reasoning in LLM-powered systems.
What They’re Building
- Advanced multi-agent AI systems capable of complex, multi-step reasoning
- Scalable LLM infrastructure and orchestration frameworks
- Systems for evaluation, validation, and monitoring of AI outputs
- High-performance retrieval and knowledge systems for large-scale data
- Production-ready AI tools used in high-stakes decision-making environments
The Role
As an Applied Research Engineer, you’ll sit at the intersection of research and production, working on:
- Developing and experimenting with cutting-edge LLM and NLP techniques
- Building agentic systems and intelligent workflows
- Translating research into robust, production-grade systems
- Designing and improving evaluation and validation frameworks
- Collaborating with engineering teams to embed AI capabilities into real-world applications
This is a highly hands-on role where you’ll own problems end-to-end, from experimentation through to deployment.
What They’re Looking For
- Strong experience building machine learning systems in production
- Deep understanding of NLP, LLMs, or AI systems
- Proficiency in Python
- Experience working with foundation models / LLM APIs
- Ability to bridge research and engineering
- Strong problem-solving and systems thinking
Nice to Have
- Experience building LLM-powered applications or agentic systems
- Exposure to evaluation, monitoring, or validation of AI systems
- Background in search, retrieval, or large-scale data systems
Why This Role is Interesting
- Work on some of the most complex challenges in AI today
- Build systems where accuracy, reliability, and trust actually matter
- Join a high-growth, well-funded team solving real-world problems
- Operate at the forefront of Responsible AI & AI Safety in production
Salary : $225,000 - $275,000