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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Distinguished Engineer -Developer Insights & AI Telemetry - **Company:** Capital One Financial Corporation - **Location:** McLean, VA, United States - **Experience:** Experienced - **Salary:** $269,100.0 - $307,200.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, Cloud Computing, Cloud Database, Information Systems, Data Architecture, Information Engineering, Data Structures, Distributed Systems, Protocol Buffers, Python (Programming Language), Software Engineering, Data Streaming, TypeScript, Google Cloud, Large Language Models, Snowflake, Apache Spark, Data Strategy, Event Driven Architecture, Information Technology, Apache Kafka, Vertica, Golang - **Published:** August 7, 2026 - **Apply:** https://www.dice.com/job-detail/1258dba3-120d-4b25-8818-18d7f4b10c9b ## About the Role * Bachelor's Degree. * At least 7 years of experience in software engineering, solution architecture, or enterprise architecture. * At least 5 years of experience with big data engineering, distributed computing, or data architecture (e.g., Spark, Kafka, Kinesis, ClickHouse, Snowflake, or cloud data warehouses). * At least 3 years of experience with Big Data and data streaming * At least 4 years of experience building and optimizing production-grade ML/AI lifecycles, pipelines, or frameworks. * At least 2 years of cloud computing experience (AWS, Microsoft Azure, or Google Cloud)., * Master's Degree in Computer Science, Information Systems, Data Engineering, or a related engineering discipline. * 10+ years of professional experience coding in commonly used languages like Python, Go, Java, or TypeScript. * 6+ years of experience designing and managing high-throughput distributed streaming architectures or edge collection telemetry platforms (e.g., OpenTelemetry, Protobuf interception hooks). * 3+ years of experience in a technical leadership role directly influencing VP/SVP/Executive stakeholders on multi-million dollar technology or AI strategy initiatives. * Deep understanding of compliance, data privacy, and cybersecurity constraints within a highly regulated environment (BankTech), including experience co-authoring risk assessments alongside Cyber and Risk teams. * Proven track record of operating within a product-centric organization (Domain Category Owner/Technical Product Owner model), delivering tactical values in continuous validation cycles. * Experience utilizing advanced engineering metrics (DORA, SPACE, AI Telemetry, Feature Lead Time) to demonstrate how developer tool investments translate into measurable corporate velocity and efficiency gains. ## Description * Vision & Strategy: Architect the long-term enterprise roadmap for distributed AI telemetry, streaming data engineering, and automated developer insight frameworks. * Enterprise Scaling & Telemetry: Lead the technical evolution of our internal developer telemetry platform from a high-performance Agent Hook Architecture into a stateless, low-latency utility capable of handling billions of annual high-fidelity events across global regions. * ML/AI & Intelligence Layer: Spearhead the deployment of advanced inference capabilities, including LLM-as-a-Judge models, to autonomously score code complexity, categorize AI use cases (e.g., Core Logic vs. Testing), and calculate the TrueThroughput and return on investment (ROI) of generative AI tools. * Data Engineering & Architecture: Own the end-to-end data strategy, shifting from traditional batch reporting to real-time event-driven architectures utilizing a scalable Medallion (Bronze/Silver/Gold) data structure feeding directly into our enterprise data lake. * Business Metric Correlation: Partner with Bank Tech Analytics to link AI code density data and telemetry directly with core business outcomes-such as lowering Feature Lead Time (FLT) and PR cycle time-without compromising quality and risk bars. * Risk & Privacy Governance: Design and enforce rigorous privacy-by-design principles, implementing automated PII masking, token management, and secret filtering to guarantee a completely safe space for engineering innovation. * Culture & Technical Contribution: Lead through direct technical contribution-prototyping systems, evaluating build vs. buy paths, authoring code patterns, and deeply mentoring principal and senior engineers across the Developer Enablement tower. * ## Related Videos - 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