Senior GenAI Engineer — Production Systems

502 CGCG-LDO CG Companies Global-LDO; Greater London; Hybrid; GBP 110,000 - 190,000; Full time

Benefits offered by this job

Bonuses

Benefits

Health benefits

Flexible work options

Generous time away

Gift matching

Job summary

Capital Group is seeking a Senior Software Engineer to turn ambiguous problems into working AI solutions that improve investment processes and business outcomes. You will lead discovery, design the approach, write the code, and own it in production.

This hands-on engineering role requires comfort in collaborating with business teams, building retrieval pipelines, and hardening agents for scalable, responsible AI use across the firm.

Qualifications

• 10+ years of professional software engineering experience with Python or similar language.
• Hands-on production experience building and shipping LLM-powered apps, including prompt engineering and evaluation.
• Experience designing end-to-end RAG pipelines and integrating LLM into real systems.

Responsibilities

• Understand workflows with business partners, scope high-value opportunities, and translate needs into clear technical specs.
• Design, build, and operate production generative AI apps such as copilots and agentic workflows.
• Architect end-to-end retrieval-augmented generation pipelines with parsing, ingestion, embeddings, and prompt management.
• Build agents and agentic workflows with auditable boundaries and guardrails for safe operation.
• Define acceptance criteria, build evaluation harnesses, and measure accuracy, latency, and hallucination.

Skills

Python

LLM apps

RAG pipelines

Distributed systems

APIs

Cloud-native

Evaluation & testing

Strong communication

Education

Bachelor's degree in Computer Science or related field

Tools

LangChain

LlamaIndex

Vector databases

MLOps tooling

Job description

Capital Group is seeking a Senior Software Engineer to turn ambiguous problems into working AI solutions that improve investment processes and business outcomes. You will lead discovery, design the approach, write the code, and own it in production.

This hands-on engineering role requires comfort in collaborating with business teams, building retrieval pipelines, and hardening agents for scalable, responsible AI use across the firm.