We are seeking a skilled Software Engineer who will design, build, and maintain software systems that deliver business value. In this role, you will focus on code quality, architecture decisions, and reliable delivery while leveraging AI tools to enhance productivity. You will verify and review AI-generated code to ensure it meets our quality standards.

In this forward-deployed role, you will be embedded directly with business units including Commercial, Manufacturing, and R&D. You will operate like a "startup CTO," bridging the gap between building products and solving real business problems through rapid solution delivery and deep domain expertise. As part of the discovery-to-scale pipeline, you will identify recurring patterns and hand off validated solutions to Platform Engineers for generalization into enterprise capabilities.

This role encompasses multi-team initiatives with area-wide impact. You will set own direction within broader strategic goals, influence teams in your area and be recognized as a domain expert. You will handle very high complexity driving through ambiguity to deliver results.

ROLE RESPONSIBILITIES

• Business: Drive business outcomes through technical solutions across your area, influence product roadmaps, and partner effectively with business stakeholders
• Delivery: Lead technical delivery of complex projects across multiple teams, unblock others through hands-on contributions, and ensure engineering quality
• Machine Learning: Architect end-to-end ML systems across teams, handle challenging modeling scenarios, mentor engineers on ML practices, and establish ML standards for your area
• Artificial Intelligence: Design AI-augmented engineering workflows for your area, evaluate new AI tools, train engineers on effective AI usage, and balance speed with verification
• People: Coach multiple engineers on career growth, lead hiring for technical roles across your area, and shape team technical culture
• Scale: Design scalable components, make sound architectural decisions, ensure code quality, and review others' designs
• Reliability: Design for reliability, implement comprehensive monitoring and alerting, lead incident response, and drive post-incident improvements
• Process: Drive process efficiency within your team, coordinate cross-functional technical work, and lead retrospectives
• Documentation: Design documentation strategies for your projects, ensure knowledge persists beyond individuals, and write specifications that enable effective collaboration

PRACTITIONER-LEVEL SKILLS

• AI-Augmented Development: You optimize AI tool usage across teams in your area, train engineers on AI-augmented workflows, evaluate new AI development tools, and establish practices that balance AI speed with verification rigor.
• Business Immersion: You immerse in operations until you think like an insider. You rapidly acquire domain expertise through direct observation, translate between business and engineering seamlessly, and mentor engineers in your area on immersion.
• Data Integration: You navigate complex enterprise data landscapes across teams, build relationships to gain data access, handle undocumented schemas through investigation, and build robust, maintainable integration solutions. You mentor engineers in your area on data integration challenges.
• Full-Stack Development: You build complete applications rapidly across any technology stack for teams in your area. You select the right tools for each problem, balance technical debt with delivery speed, and mentor engineers on full-stack development.
• Model Development: You design end-to-end ML systems for complex problems across teams, handle challenging modeling scenarios (imbalanced data, concept drift), mentor engineers in your area, and establish ML practices.
• Model Fine-Tuning: You architect fine-tuning pipelines for complex use cases across teams, implement advanced techniques (LoRA, PEFT, multi-task learning), mentor engineers on fine-tuning practices, and establish model customization standards.
• Multi-Audience Communication: You influence through communication at all levels—from frontline to executive. You handle difficult conversations skillfully, train engineers in your area on effective communication, and represent teams across the function.
• Problem Discovery: You seek out undefined problems rather than avoiding them. You embed with users to discover latent needs, coach engineers in your area on problem discovery techniques, and turn ambiguity into clear problem statements.
• Rapid Prototyping & Validation: You lead rapid delivery initiatives across teams in your area, coach on prototype-first approaches, establish trust through consistent fast delivery, and define clear criteria for prototype-to-production transitions.

WORKING-LEVEL SKILLS

• AI Evaluation & Observability: You design evaluation frameworks with custom evaluators tailored to your use case. You build golden datasets, establish annotation workflows with clear rubrics, and run experiments to compare prompt and model changes systematically.
• AI Literacy: You evaluate AI solutions critically for specific use cases. You understand bias, fairness, and hallucination risks. You make informed decisions about when AI helps vs when traditional approaches are better.
• Architecture & Design: You design components and services independently for moderate complexity. You make appropriate trade-off decisions, document design rationale, and consider AI integration points in your designs.
• Cloud Platforms: You design cloud-native solutions, manage infrastructure as code, implement security best practices, and make informed service selections. You troubleshoot cloud-specific issues.
• Code Quality & Review: You produce consistently high-quality, well-tested code. You review AI-generated code critically and never ship code you don't fully understand. You identify edge cases and ensure adequate test coverage.
• Developer Experience: You design golden paths—opinionated, well-documented workflows developers can follow with minimal cognitive load. You conduct user research, create self-service capabilities, and build for Day 50, not just Day 1.
• DevOps & CI/CD: You build complete CI/CD pipelines end-to-end, manage infrastructure as code, implement monitoring, and design deployment strategies for your services.
• Knowledge Management: You design knowledge structures for discoverability, ensure knowledge accessibility across teams, facilitate knowledge sharing sessions, and reduce single-person dependencies.

QUALIFICATIONS

• Bachelor's degree in Computer Science, Engineering, or related field with 7+ years of relevant experience.
• Deep technical expertise with a proven track record in developer advocacy, community building at scale, and organization-wide engineering culture leadership.