Senior Software Engineer Agentic Workflow & Craftsmanship

Job Description:

This position is responsible for orchestrating advanced, agentic workflows and engineering the surrounding quality infrastructure for enterprise-grade software. The role balances high-velocity startup execution with rigorous software craftsmanship, utilizing continuous refactoring, stacked architectures, and advanced testing methodologies to control non-deterministic AI outputs and systematically minimize the long-term cost of change.

Essential Duties & Responsibilities

Agentic System Development: Write production-grade code alongside advanced agents, engineer systems that orchestrate agentic workflows, and construct the surrounding quality machinery to ensure reliability under heavy enterprise loads.

Architectural Oversight: Design and implement robust, stacked architectures that employ algorithmic guardrails to successfully bound and constrain stochastic LLM outputs.

Software Craftsmanship: Champion continuous refactoring, micro-modular design, and extreme code readability as standard daily practices to keep the long-term cost of change low.

Quality Infrastructure: Adapt 2020-era quality methodologies (e.g., TDD, real Devops, BDD, etc. ) to modern AI paradigms by implementing characterization testing, mutation testing, property-based testing, observability frameworks, and related.

C ollaborative Execution: Engage in heavy, direct technical collaboration with a peer group of senior engineers; actively participate in high-level trade-off debates while maintaining a strict "disagree and commit" shipping philosophy.

Qualifications & Skills

Enterprise Software Expertise (Historical Track Record)

Substantial, proven experience architecting and maintaining production-grade enterprise software systems.

Deep understanding of complex integration surface areas, the long-term life cycle of architectural decisions, and designing for decade-long maintainability.

Modern Agentic Capability

Hands-on, deep engagement with current-generation development agents (e.g., Claude Code, Codex, or equivalent tools) within the current calendar year.

Demonstrated experience moving past basic prompt engineering into building tools, pipelines, and stacked architectures to tighten developer feedback loops.

An empirical, evidence-based understanding of the current limitations, failure modes, and strengths of LLM-driven development.

Core Technical Proficiencies

Fluency in at least one mainstream programming language, with a demonstrated ability to learn and switch languages fluidly based on project needs.

Working depth with Git, CI/CD pipelines, containerization, and modern testing frameworks.

Key Behavioral Competencies

Startup Velocity: Thrives in a highly iterative environment ("build today, release tonight, refactor tomorrow").

Empirical Tinkerin