Drive R& D; designing, prototyping, and validating new approaches to hard, open-ended problems.
Own the design and architecture of core systems, from algorithms and data structures to how they're exposed, deployed, and scaled.
Work independently with minimal hand-holding, comfortably taking a loosely defined problem, figuring out the right approach, and driving it to completion without needing constant direction.
Use AI coding agents to accelerate development across backend, frontend, and infra, while applying rigorous review, testing, and validation to everything shipped.
Design and evolve system architecture, including RDBMS schema, APIs, and cloud infrastructure.
Set up and maintain CI/CD pipelines, and take ownership of deployment, monitoring, and reliability.
End-to-end responsibility from problem definition through design, development, testing, and release.
Work in a cross-domain team with ML engineers, immunologists, biochemists, and bioinformaticians, translating scientific problems into engineering systems.

Strong software design and architecture judgment, able to make and justify design decisions, not just implement them.
Practical, hands-on experience using AI coding agents (e. g., Claude Code, Cursor, and Copilot) for real engineering work, with the judgment to critically review, test, and validate agent-generated code rather than accept it as-is.
Strong data structures and algorithms fundamentals.
Experience working across the stack, comfortable picking up backend, frontend, or infra work as needed, rather than staying in one lane.
Hands-on experience with cloud platforms (AWS/GCP/Azure) and cloud infrastructure.
Experience setting up or maintaining CI/CD pipelines.
Hands-on experience with at least one RDBMS.
Ability to work and communicate effectively in a cross-domain team.
Comfort exploring ambiguous, unfamiliar problem statements and adapting fast in an early-stage start-up.

Prior professional experience in Go, Python, C++, Bash, and Postgres.
Experience building tooling around AI agents, custom prompts, eval harnesses, agent orchestration, or MCP-based integrations.
Familiarity with containerization/orchestration (Docker, Kubernetes) or infrastructure-as-code (Terraform).
Any experience in data mining or scientific/biological data pipelines.

Drive R& D; designing, prototyping, and validating new approaches to hard, open-ended problems.
Own the design and architecture of core systems, from algorithms and data structures to how they're exposed, deployed, and scaled.
Work independently with minimal hand-holding, comfortably taking a loosely defined problem, figuring out the right approach, and driving it to completion without needing constant direction.
Use AI coding agents to accelerate development across backend, frontend, and infra, while applying rigorous review, testing, and validation to everything shipped.
Design and evolve system architecture, including RDBMS schema, APIs, and cloud infrastructure.
Set up and maintain CI/CD pipelines, and take ownership of deployment, monitoring, and reliability.
End-to-end responsibility from problem definition through design, development, testing, and release.
Work in a cross-domain team with ML engineers, immunologists, biochemists, and bioinformaticians, translating scientific problems into engineering systems.

Strong software design and architecture judgment, able to make and justify design decisions, not just implement them.
Practical, hands-on experience using AI coding agents (e. g., Claude Code, Cursor, and Copilot) for real engineering work, with the judgment to critically review, test, and validate agent-generated code rather than accept it as-is.
Strong data structures and algorithms fundamentals.
Experience working across the stack, comfortable picking up backend, frontend, or infra work as needed, rather than staying in one lane.
Hands-on experience with cloud platforms (AWS/GCP/Azure) and cloud infrastructure.
Experience setting up or maintaining CI/CD pipelines.
Hands-on experience with at least one RDBMS.
Ability to work and communicate effectively in a cross-domain team.
Comfort exploring ambiguous, unfamiliar problem statements and adapting fast in an early-stage start-up.

Prior professional experience in Go, Python, C++, Bash, and Postgres.
Experience building tooling around AI agents, custom prompts, eval harnesses, agent orchestration, or MCP-based integrations.
Familiarity with containerization/orchestration (Docker, Kubernetes) or infrastructure-as-code (Terraform).
Any experience in data mining or scientific/biological data pipelines.

Senior Software Engineer

Skills