Staff Software Engineer, Financial AI

Requirements:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in coding in one or more of the following languages (C++, Java, Go, or Python).
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine-tuning).
• Experience in the financial services industry, particularly in quantitative finance, algorithmic trading, or risk management.

Nice to haves:

• Master's, or PhD in Physics, Mathematics, Computer Science or a related quantitative field.
• 8 years of experience in data structures and algorithms.
• Experience with machine learning, natural language processing (NLP), or generative AI and large language models (LLMs).
• Experience building complex data processing pipelines with tools like Kafka, Apache Beam (Dataflow) or Spark.
• Experience working with time-series data and financial market data feeds.
• Understanding of Google Cloud Platform services (e.g., BigQuery, Google Kubernetes Engine, Pub/Sub).

What you'll be doing:

• Design, develop, and deploy core components of the financial AI platform, including the orchestration engine, proprietary analytical tools, and data processing pipelines.
• Build high-performance microservices for complex financial workflows, such as historical backtesting, Monte Carlo simulations, and advanced risk calculations.
• Collaborate with researchers from teams like DeepMind to integrate and optimize Google's state-of-the-art forecasting models for financial use cases.
• Develop the intelligent orchestration layer that uses Gemini to interpret natural language queries and chain together the appropriate sequence of financial tools and data sources.
• Engineer scalable and auditable data pipelines for ingesting and transform various data sets (including real-time feeds and proprietary data), ensure the reproducibility and verifiable logic of all AI-generated insights.

Perks and benefits:

• Opportunity to work on cutting-edge technologies that impact billions of users worldwide.
• Ability to switch teams and projects as the business evolves.
• Empowerment to act like an owner, take action, and innovate.
• Versatile engineering role spanning various domains within Google Cloud.
• Contributing to applied AI in the financial services industry.