Principal Software Engineer - Agentic PDLC/SDLC

Fetch•Reston, VA

1d•Hybrid

About The Position

AI & Data at Fetch sit at the center of how we understand our business, make decisions, and build intelligent products. The organization operates as an integrated AI & data ecosystem, spanning multiple disciplines, including data engineering, analytics engineering, machine learning, experimentation, and data platforms, all working together to turn data into durable business and customer impact. Teams operate in complex problem spaces where requirements evolve, tradeoffs are constant, and the right answer is rarely obvious. Success depends on strong technical judgment, comfort with ambiguity, and the ability to gather context and make informed decisions while balancing quality, performance, scalability, and responsible use. Practitioners across this org contribute hands-on to production systems, analytical foundations, and intelligent features. You will collaborate closely with product, platform, and engineering partners, help shape standards and best practices, and ensure our AI and data capabilities scale reliably as Fetch grows. About the Role: Fetch is evolving its AI-first mode into a more operational and scaled position, and we are looking for a Principal Software Engineer to design, scale, and evolve the intelligent platforms that power our Product and Software Development Life Cycles (PDLC/SDLC). In this role, you will define and execute the company-wide strategy for transitioning Fetch into an agentic engineering ecosystem, where autonomous AI agents, multi-modal LLM frameworks, and intelligent developer tools directly amplify human capabilities at scale. Sitting at the intersection of Developer Experience (DevX), platform infrastructure, and generative AI systems engineering, you will lead the technical vision to automate heavy SDLC workloads and optimize engineering workflows. This is a hands-on, high-impact technical IC role with massive influence across multiple engineering collectives. Your goal is to fundamentally redefine our engineering velocity and platform performance while setting organizational standards for system reliability, model safety, and strict verification gates. As a Principal Software Engineer, you balance deep software craftsmanship with strategic, company-level influence, engineering systems that endure, scale, and secure Fetch’s infrastructure for its next phase of growth. This is a full-time role that can be held from one of our US offices or remotely in the United States.

Requirements

15+ years of software engineering experience, including a strong track record as a Principal Engineer or equivalent company-level technical authority, leading the architecture of distributed systems and large-scale enterprise developer platforms.
Deep experience designing, scaling, and evolving development platforms powered by agentic AI tools that support product development and the full software development lifecycle across large organizations.
Deep technical mastery in Developer Experience (DevX) or Platform Engineering, with proven experience building or scaling modern CI/CD pipelines, containerized environments, event streaming, and advanced telemetry layers
Proven experience operationalizing GenAI workflows at scale, including hands-on application of multi-modal LLM agent frameworks (e.g., LangChain, Semantic Kernel, Haystack) or Retrieval-Augmented Generation (RAG) systems inside an enterprise engineering ecosystem
Demonstrated company-wide impact leading multi-quarter, multi-team technical initiatives that fundamentally transformed developer velocity, code quality, or resource efficiency
Expert-level fluency in metric trees, with the ability to tie complex platform architectures directly to north-star business KPIs while operating within strict, non-negotiable operational guardrails
Strong data-driven intuition for risk modeling and tradeoff analysis, with a clear framework for balancing acceleration against blast-radius control and understanding where AI creates leverage versus where traditional optimization approaches are more effective
Exceptional communication skills, with a proven ability to drive company-level technical decisions and communicate effectively across engineering, executive leadership, cross-functional stakeholders, and non-technical partners

Nice To Haves

Industry eminence demonstrated through open-source contributions, technical publications, conference speaking, or other work that has shaped engineering practices across the broader technology community
Proven success building first-party platform capabilities and automated frameworks that eliminate reliance on costly third-party development infrastructure and tooling
Strong expertise operating within compliance and privacy constraints, including designing systems aligned with frameworks such as SOC2, GDPR, and CCPA while enforcing strict privacy and redaction boundaries across automated AI pipelines
Expert-level proficiency in modern concurrent backend programming languages such as Go, Java, Kotlin, or Python, backed by a strong polyglot engineering background

Responsibilities

Architect Enterprise DevX Infrastructure: Design and evolve scalable systems supporting AI-assisted development (e.g., GitHub Copilot, Claude Code integrations), autonomous code refactoring, simulation testing environments, automated OKR tracking, and feedback-driven observability
Set Organizational Standards: Redefine and enforce company-wide technical standards for system reliability, performance, observability, and architectural health across all PDLC/SDLC platforms
Architect for Extreme Scale: Lead the system design and evolution of distributed cloud-native developer platforms supporting autonomous code refactoring, simulation testing environments, and feedback-driven observability
Establish Rigid AI-Validation Frameworks: Define company-wide standards for automated contract, regression, and safety checks to ensure AI-generated or refactored code is rigorously validated before reaching production
Simplify Systemic Complexity: Proactively identify organization-level bottlenecks and redesign systems to minimize operational costs while maximizing long-term velocity and reliability
Define Multi-Year Technical Vision: Establish the direction for agentic development beyond a single organization, guiding multiple engineering areas and influencing Fetch's long-term success
Solve the Unsolvable: Resolve deeply complex, ambiguous, cross-organizational technical challenges that have blocked major company initiatives or that few others can solve
Quantify Technical Tradeoffs: Align technical strategy with company business direction, translating platform optimizations and AI capabilities into measurable numbers (e.g., cycle time reduction, defect escape drops, and review rework percentage decreases)
Exercise "Do Not Build" Judgment: Evaluate industry trends and external technologies critically, demonstrating high-signal judgment on when to leverage tools and where to block implementations to protect compliance, IP, or reliability
Mentor at Scale: Mentor and sponsor industry-level staff/principal engineers and managers across organizational boundaries, visibly growing their technical depth, systems thinking, and leadership capability
Sustain Organizational Culture: Build and foster inclusive technical communities internally and externally, maintaining morale, psychological safety, and alignment during periods of organizational change
Navigate High-Stakes Disagreements: Resolve complex, divergent cross-functional views (between Engineering, Product, Data Science, and Legal) with empathy, clarity, and data-driven principles