Staff Software Engineer - - DBB

SIVAD Consulting; San Francisco (CA); Hybrid; USD 200,000 - 250,000; Full time

Job summary

SIVAD Consulting in San Francisco, CA is seeking a Staff Software Engineer to serve as the technical anchor for a small, high-impact team building AI agents for clinical trials. You will code daily, mentor three juniors, and collaborate with founders and product, customer success to deliver zero-to-one products for a platform used by 400+ research sites.

The role combines hands-on development with leadership, architecture, and process ownership at a seed-stage company, offering a unique chance

Qualifications

• 8+ years of experience in full-stack product engineering.
• Led engineering teams or acted as technical anchor on major projects.
• Hands-on with shipping zero-to-one, customer-facing products (not deep infra).
• Experience shipping LLM-powered features or AI agents in production in past 1–2 years.

Responsibilities

• Own and build AI-powered products end-to-end — from ideation through shipping.
• Mentor three junior engineers and establish code-review and process best practices.
• Collaborate with CTO, PM, and customer success to shape zero-to-one products.
• Architect and deliver full-stack applications across frontend, backend, infra, and data pipelines.

Skills

Full-stack development

Mentoring engineers

LLM-powered features

Cross-functional collaboration

Technical leadership

Education

CS degree

Tools

LangSmith

Braintrust

Weights & Biases

Job description

Staff Software Engineer – Hybrid (San Francisco, CA) – DBB

Salary range: $200k to $250k

We are looking for a Staff Software Engineer with 8+ years of experience to join our organization as the technical anchor of a small, high-impact engineering team building AI agents that accelerate clinical trials. You'll be a hands-on staff-level IC who writes and reviews code daily while mentoring three junior engineers and helping them understand what great engineering looks like. You'll work cross-functionally with product, customer success, and founders to ideate and ship zero-to-one products for a platform already used by 400+ research sites. This is a rare opportunity to shape engineering culture, processes, and architecture from the ground up at a seed-stage company

Responsibilities

• Own and build AI-powered products end-to-end — from ideation through shipping — including agentic workflows and LLM-powered features with production evals
• Serve as the technical lead and mentor for a team of three junior engineers, establishing best practices for code reviews, engineering processes, and team workflows
• Partner closely with the CTO, PM, and customer success to understand customer needs and shape new zero-to-one products
• Architect and deliver full-stack applications across frontend, backend, infrastructure, and data pipelines

Work experience

• 8 - 15 years of experience in full-stack product engineering, building AI/LLM-powered features
• Has been the tech lead or de facto technical anchor on an engineering team: led large projects and coordinated other engineers' work.
• Experienced Full-stack product engineer who can own a feature end-to-end (frontend, backend, infra). Backend-leaning generalists are fine.
• Mentor and bar-raiser for junior engineers: can establish best practices for code quality, code review, and engineering process on a team that hasn't seen what good looks like yet.
• Product engineering background with hands-on experience shipping zero-to-one, customer-facing products (not deep infra).
• Recent (last 1–2 years) hands-on experience shipping LLM-powered features or AI agents in production.
• Partners cross-functionally with PM, customer success, and founders to understand customer needs and ideate zero-to-one products
• Has set up AI evals or LLM observability in production (LangSmith, Braintrust, W&B or similar); experience with multi-step agentic pipelines.

Preferred

• Mix of startup experience (seed to Series B, founding engineer or early hire) and time at a larger company where they saw engineering at scale.
• Genuine interest in bio, life sciences, or healthcare.

Education

CS degree or equivalent work experience