We are a leading venture capital/private equity firm specializing in the life sciences sector looking for an Senior Software Engineer to join our dynamic team. You do not need venture capital or life science experience.

We are seeking a highly skilled and experienced Senior Software Engineer for our trailblazing AI and Data Intelligence team, focusing on data infrastructure and machine learning work.

As a core member of the Data Infrastructure team, you will develop data pipelines, create and maintain distributed compute systems, and work with both traditional ML and large language models (LLMs).

You will collaborate closely with investors and scientists to build sophisticated data products and tools and will learn what makes a great life sciences company and how these companies are evaluated in a venture capital context. Your work will be instrumental in crafting an ambitious AI-driven investment decision platform powered by data-driven insights, and potentially demonstrate direct impact on our fund performance.

Key Responsibilities

Data Engineering: Design, implement, and maintain scalable and reliable data

infrastructure.

Data Pipeline Management: Develop, optimize, and maintain ETL/ELT pipelines to

ensure efficient data processing and integration from internal and external sources.

Advanced data systems: Collaborate with domain experts to build and deploy

solutions for entity resolution, prioritization, ranking, and LLM prompt engineering.

Collaboration: Work closely with cross-functional teams, including data scientists,

investors, and software engineers

Software Design: Create software design documentation. Architect and implement

robust, scalable software systems and microservices.

Performance Optimization: Identify and resolve performance bottlenecks in data

pipelines, data warehouse systems, and machine learning models.

Security: Ensure data systems comply with security and privacy regulations and best

practices.

Technical leadership: Actively participate in setting technical direction, roadmaps and

standards for features. Lead and participate in software architecture design reviews.

Continuous Development: Stay current with the latest industry trends and

technologies, continuously improving data infrastructure and ML capabilities.

Qualifications

Education: Bachelor or Master’s degree in Computer Science, or a related field.

Experience: 6+ years as a Software Engineer, with a focus on Data Engineering and/or

Distributed Systems

Technical Skills:

Strong fundamentals in software design, data structures, algorithms, distributed /

parallel computing concepts

Strong proficiency with PyData stack (pandas, numpy, jupyter, Dask, scikit-learn)

Proficiency in SQL (Postgres, Presto/Trino dialects preferable) and database

technologies

Experience with workflow orchestration systems (e.g. Airflow, Prefect)

Experience with cloud-based modern data lake/warehouses (e.g. AWS Athena,

Redshift, Snowflake, Iceberg)

Experience with AWS cloud services (S3, Batch, ECS, Fargate), infrastructure-as-

code tools (CDK, Terraform), containerization (Docker)

Previous hands-on experience with langchain and other LLM frameworks a plus

Soft Skills:

Strong problem-solving, communications, and presentation skills

Fluency in English

Ability to lead and mentor other engineers

Proactive and self-motivated with a strong sense of ownership

Almond Partners (Buy-Side Executive Search)

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