Senior Software / Data Engineer
At a glance
Senior Data Engineering role at Sleuth Insights. Hybrid (San Francisco, California, US) · full-time · no salary stated · we estimate $142,500–$193,650 across the United States.
Sleuth Insights has not published a salary for this role. The figure below is our estimate, not theirs.
dataroles summary, based on the employer's posting.
What you'll do
- Build and run AI-enabled data products, including ETL workflows, entity extraction and analytics for client projects
- Test emerging tools through proof-of-concept work that helps deliver data solutions faster
- Turn recurring project needs into platform features by analyzing requirements and proposing technical approaches
- Work with engineering teammates to ship platform improvements, LLM-based applications and data pipelines
- Add monitoring, observability and engineering practices for security, compliance and software quality
What you bring
- Ten years of professional software or data engineering, including at least two years at a small company or startup
- Proficiency in Python, Docker, an orchestration framework and PostgreSQL
- Experience building and operating with cloud services, infrastructure-as-code and secure software practices
- A computer science, engineering, math, biology or related scientific degree at the bachelor’s or master’s level
- Familiarity with biopharma, biotech or life sciences data, such as diseases, drugs or clinical trials
Who this fits
This role suits a senior engineer comfortable balancing near-term client deliverables with longer-term platform work. You’ll collaborate across engineering and take ownership from project data assets through reusable product capabilities. The role offers a flexible hybrid or remote setup.
From the employer
About Sleuth
Sleuth is building a modern, agentic, and intelligent decision-making platform for the biopharma and life sciences industry. We’re using AI to automate workflows and deliver crucial insights and bespoke reports that answer our users’ critical questions about their investments.
You should join us, because:
- Traction: we’ve generated outsized demand for a startup of our size, and have already signed deals with some of the world’s leading biopharma companies.
- Talent density: we’re growing thoughtfully and only work with incredibly smart, driven people.
- Velocity: to meet the demand we’ve generated, we ship fast. You’ll learn a lot and constantly take on new challenges.
- Frontier technology & product: we’re developing cutting-edge AI systems. You’ll truly be building the future of how biopharma and life sciences companies generate insights to power their business.
About the role
We are seeking an experienced data engineer who has built enterprise-grade, cloud-native data infrastructure and products. In this role, you’ll support our forward-deployed engineering efforts to build and ship data assets as part of pharma projects involving competitive intelligence and complex analytical tasks. You will be the primary bridge between these projects and the core engineering efforts to transform those assets into standard Sleuth platform AI-powered features. You will need to have knowledge and working experience with complex datasets in the pharma and biotech industry, a broad knowledge of data engineering tools and technologies, and the ability to swing between short/mid-term deliverables with customers and the mid/long-term sleuth technology roadmap.
What you'll do
- Design, develop, and operate AI-powered data solutions (ETL pipelines, entity extractions, and analytics) to deliver client projects.
- Investigate new tools and technologies and develop proof of concepts to accelerate the delivery of data solutions.
- Identify patterns that could be turned into platform capabilities and product features, document and analyze requirements, and deliver technical proposals.
- Collaborate closely with the rest of the engineering team to ship platform capabilities and product features.
- Develop applications and pipelines leveraging LLMs and modern agentic frameworks and tooling.
- Leverage large-scale datasets for advanced analytics.
- Contribute to engineering best practices across security, compliance, and software quality.
- Build monitoring and observability into the infrastructure and all data components.
What we are looking for
- Experience: 10 years of professional software and/or data engineering experience in the industry with 2+ years in small companies or startup environments.
- Languages and tools: proficiency in Python, Docker, orchestration framework (e.g., Airflow),
- Data stores: relational databases (specifically PostgreSQL). Experience with graph and vector databases is a big plus.
- Generative AI: Knowledge of LLMs and GenAI frameworks (LangChain, LangSmith, LangGraph, AutoGen, MCP, etc.). Hands-on experience is a big plus.
- Infrastructure & Ops: experience in leveraging cloud environments and data services for development and operation, strong in infrastructure-as-code.
- Security & Compliance: experience in secure software development and familiar with SOC2 or regulated software development environments.
- Education: BS or MS in computer science, engineering, math, biology, or a related scientific field. Additional hands-on certificates are great to have.
- Working style: collaborative and organized with a strong sense of end-to-end ownership.
- Domain Knowledge: familiarity with biopharma, biotech, or life sciences environments and experience with the industry datasets (e.g., diseases, drugs, clinical trials, etc.)
What we offer
- Competitive compensation and meaningful equity, full healthcare benefits with generous employer contribution, and flexible hybrid/remote work setup.
- Hands-on experience at the frontier of AI, building agentic systems that don’t just support but transform how insights are generated and applied.
- An opportunity to directly partner with leading biopharma companies and see your work shape how this industry makes billion-dollar decisions using our software.
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