Client-Facing Applied AI Engineer - Senior

Addepar, Inc.

Greater London

On-site

GBP 110,000 - 170,000

Full time

4 days ago
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Job summary

Addepar, Inc. in London seeks a Sr. Software Engineer in Customer Facing Applied AI to partner with clients and deliver AI-powered workflows.

You will translate client needs into production-ready AI features, prototype rapidly, and work closely with engineering to embed agentic capabilities into the product. You will design agent behaviors, wire tool integrations, and optimize for reliability and performance while maintaining a strong feedback loop with clients and stakeholders.

Qualifications

  • Extensive professional software engineering experience.
  • Proficiency in Python and backend systems.
  • Experience with LLM APIs, function calling and structured outputs.
  • Strong SQL skills for data exploration and AI workflows.
  • Familiarity with cloud infrastructure and deployment pipelines.

Responsibilities

  • Build AI-powered agents and tools end-to-end for client projects.
  • Design and implement LLM integrations including prompt engineering and function calling.
  • Define evaluation criteria and test harnesses for AI systems in production.
  • Work directly with clients to validate AI behavior and iterate toward production quality.
  • Partner with engineering teams to generalize client work into product features.
  • Contribute to shared AI infrastructure and deployment pipelines.
  • Monitor production AI systems for reliability and cost efficiency.

Skills

Software engineering
Python
LLM integration
SQL
Distributed systems
Prototyping

Education

BS/MS in Computer Science or Mathematics

Job description

Addepar, Inc. in London seeks a Sr. Software Engineer in Customer Facing Applied AI to partner with clients and deliver AI-powered workflows.

You will translate client needs into production-ready AI features, prototype rapidly, and work closely with engineering to embed agentic capabilities into the product. You will design agent behaviors, wire tool integrations, and optimize for reliability and performance while maintaining a strong feedback loop with clients and stakeholders.

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