ai engineer in fintech

The client is a global investment management company headquartered in London. It manages over $228 billion in assets for institutional investors, pension funds, wealth managers, and other sophisticated clients worldwide, specializing in quantitative investing, alternative investments, systematic trading strategies, and technology-driven asset management.

• Build agentic workflows that reason over research reports, transcripts, filings, and news, presenting portfolio managers with findings, gaps, and confidence levels;
• Engineer automated quality checks on unstructured source content before ingestion;
• Build vendor delivery validation to detect and quantify parsing and format defects, provide feedback to vendors and the data sourcing team, and fix extraction issues handled internally;
• Build evaluation harnesses, benchmarks, and guardrails for agent output, including groundedness, factual accuracy, relevance, and citation/provenance;
• Ship monitoring and dashboards showing data-quality findings, confidence levels, and coverage gaps to engineering and portfolio management audiences;
• Work with platform engineering, data sourcing, and portfolio managers to turn business expectations into measurable, automated quality standards.

• Proven experience building production agentic and LLM systems with multi-agent or orchestrated workflows across heterogeneous sources;
• Hands-on experience engineering document ingestion and extraction pipelines, including parsing, chunking, and automated quality controls;
• Experience building evaluation and guardrail infrastructure for AI systems, including groundedness scoring, citation and provenance, evaluation harnesses, regression suites, and LLM observability;
• Strong production Python engineering experience with unattended services and pipelines, testing, CI, and code standards;
• Ability to work from deliberately vague briefs, shape problems with business stakeholders, and explain technical results to non-technical audiences;
• Nice to have: retrieval quality tuning, structured and time-series data-quality experience, ETL pipelines, SQL, experience working with investment professionals in a fast-paced environment, Snowflake, Linux/UNIX, Git, Jira.

• Remote work is available from Poland, Spain, or the United Kingdom;
• Equal opportunity employment with a commitment to equity, diversity, and inclusion;
• Benefits supporting employee well-being and professional growth.