Staff Software Engineer at SIVAD Consulting

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

Requirements

Must-haves

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

Nice-to-haves

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.
CS degree or equivalent work experience

Application prep

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Keywords to mirror

aillm

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