• Design and ship vault strategies: take a strategy from thesis and design doc through implementation, simulation, deployment, and live operation — RWAs, leveraged lending, yield aggregation, cross-protocol allocation, perpetuals, prediction markets, and new product types we haven't built yet. • Optimize strategies: signals research, execution optimization, gas-aware rebalancing across tokens and chains, liquidity and duration management. • Run protocol and asset due diligence: evaluate new protocols, collateral assets, and chains for inclusion in strategies — solvency mechanics, oracle design, redemption paths, liquidity depth, and more. • Own risk parameters: supply caps, LLTV settings, concentration limits, VaR-based exposure models, and automated de-risking logic that pulls positions when conditions deteriorate. • Integrate new protocols and chains: build and validate adapters for lending markets, DEX aggregators, and bridges; verify strategy behavior against forked-chain simulation before capital touches it. • Monitor what you build: extend our risk-monitoring and alerting systems, define the conditions that page someone, and participate in the on-call rotation for the strategies you own. • Support launches and clients: partner with growth, capital markets, and client teams on new vault and strategy launches.

• Understanding the business requirements • Writing code and implementing the proposed solutions • Debugging, root cause analysis… • Creating data pipelines, versioning and change management • Manage the complexity inherent in versioned data pipelines • Develop ETL/ELT processes to help extract and manipulate data from multiple sources. • Design, build and maintain batch or real-time data pipelines in production. • Automate data workflows such as data ingestion, aggregation, and ETL processing. • Ensure data accuracy, integrity, privacy, security, and compliance through quality control procedures. • Train and mentor junior engineers.

• Design, develop, and optimize complex Calculation Views using SAP HANA 2.0 (HDI Containers, Web IDE, or Business Application Studio) • Create advanced Table Functions and Stored Procedures using SQLScript to support analytical and transactional workloads • Implement and maintain HDI Containers, Synonyms, and .hdbgrants configurations to ensure proper data access governance • Build, maintain, and troubleshoot robust data pipelines using SAP Data Services (BODS) to move data from S/4HANA to Google BigQuery • Design and implement delta-load frameworks that minimize data extraction overhead while ensuring data freshness • Manage BODS job servers and configure complex transformations to meet business and technical requirements • Leverage S/4HANA standard CDS Views and ODP (Operational Data Provisioning) frameworks for efficient, scalable data extraction • Navigate the S/4HANA data dictionary (e.g., ACDOCA, MATDOC) to identify optimal data sources and extraction patterns • Ensure extraction logic aligns with business processes (e.g., Sales Orders, Material Documents, Financial Postings) • Configure and optimize connectivity between SAP and Google Cloud Platform, utilizing Google Cloud Storage (GCS) for staging and the BigQuery Adapter for bulk loading • Design and implement file-based integration patterns using Parquet and CSV formats to maximize load performance • Optimize BigQuery table partitioning, clustering, and schema design to support high-performance analytics at scale • Continuously analyze and optimize data pipeline performance to achieve real-time or near-real-time data availability • Troubleshoot integration issues across SAP HANA, BODS, GCS, and BigQuery, ensuring minimal disruption to downstream consumers • Recommend architectural improvements that balance data freshness, system performance, and cost efficiency

Role Description This is a high-accountability environment where bold ideas drive real innovation for customers, partners, and the industry. The successful candidate will take ownership, deliver meaningful impact, and help shape the future of AI-ready connectivity. Lumen is seeking an experienced and hands-on Senior Lead Software Developer, AI Developer Enablement to help shape the next chapter of AI-assisted software engineering across the organization. This role will define, build, and scale reusable AI capabilities that: - Accelerate developer productivity - Reduce friction in everyday engineering work - Transform practical AI workflows into high-impact accelerators for teams across the enterprise The ideal candidate will bring deep expertise in: - Modern software development - AI-assisted engineering workflows - Developer tooling - Automation - APIs - Cloud platforms - Enterprise engineering practices This role will help make AI enablement practical, measurable, and transformational for developers across Lumen. Responsibilities - AI-Assisted Development Enablement: - Design and implement AI-enabled developer workflows for code generation, reviews, debugging, testing, documentation, research, incident triage, and platform navigation. - Establish scalable, secure, and repeatable patterns for AI adoption across engineering teams. - Develop reusable prompts, agents, integrations, and workflow accelerators that improve developer productivity. - Developer Productivity & Experience: - Identify development friction and translate it into high-impact AI solutions. - Partner with engineering teams to reduce toil, accelerate delivery, improve onboarding, and enhance the developer experience. - Define adoption metrics, feedback loops, and success measures. - Reusable AI Capabilities & Patterns: - Build and scale shared AI capabilities, reference architectures, prompt libraries, templates, and playbooks. - Partner with platform, architecture, and security teams to ensure AI solutions are maintainable and aligned with responsible AI practices. - Technical Knowledge & AI-Driven Support: - Improve access to engineering knowledge through AI-powered search, summarization, technical Q&A, documentation generation, and context-aware support. - Transform tribal knowledge, coding standards, platform guidance, and operational playbooks into scalable AI-assisted experiences. - AI Adoption & Community Enablement: - Drive AI adoption through demos, training, office hours, onboarding resources, reusable examples, and engineering community engagement. - Coach developers and technical leaders on practical AI usage and responsible engineering practices. - Technical Delivery & Project Execution: - Lead AI enablement initiatives from discovery through production. - Identify and mitigate risks related to security, data access, hallucinations, quality, compliance, integrations, user experience, and operational support. - Measurement & Continuous Improvement: - Measure AI impact through adoption, usage, cycle time reduction, automation, developer satisfaction, and quality improvements. - Use data and feedback to refine AI enablement strategies. - Leadership & Technical Influence: - Provide technical leadership and mentorship for AI developer enablement. - Guide teams on architecture, prompt engineering, agent workflows, and responsible AI. Qualifications - Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field. Advanced degree or equivalent practical experience preferred. - 10+ years of experience in software development, platform engineering, developer productivity, AI enablement, automation, or related technical disciplines. - Strong hands-on experience designing, building, and supporting modern software solutions. - Experience with AI-assisted development workflows, coding assistants, generative AI capabilities, and applied AI solutions for engineering teams. - Deep understanding of the software development lifecycle, code quality, testing, documentation, secure coding, CI/CD, operational reliability, and production support practices. - Proven ability to translate ambiguous developer needs into practical, secure, scalable, and reusable technical solutions. - Experience partnering with cross-functional teams including engineering, platform, security, product, architecture, operations, and business stakeholders. - Strong communication skills with the ability to explain technical concepts and influence adoption. - Strong understanding of responsible AI, data protection, security considerations, governance, and risk management for enterprise AI adoption. - Demonstrated ability to mentor engineers, lead technical initiatives, and drive measurable improvements in developer productivity and engineering outcomes. Preferred Skills - Experience with LLM-based developer tools, AI coding assistants, agent frameworks, retrieval-augmented generation, vector search, tool calling, or workflow orchestration. Location This is a work from home position within the US.