Senior Software Engineer
$101.5k - $169.1kCox Automotive
Cox Automotive is deploying enterprise AI capabilities on AWS Quick across the enterprise, helping teams work more effectively in their day-to-day operations.
We are looking for a Senior Software Engineer who applies the principles of secure software engineering to the design, development, maintenance, testing, and evaluation of software and cloud infrastructure that supports this initiative. As a senior member of the engineering organization, you will be expected to contribute beyond feature implementation by influencing development practices, mentoring teammates, raising engineering standards, and helping guide technical decision-making across products and services. You'll regularly balance short-term delivery objectives with long-term maintainability, scalability, and operational excellence. This is early-stage work with executive sponsorship, direct access to AWS technical teams, and the autonomy to shape how the platform is built. What You'll Do Platform Integration & Connector Governance- Own the enterprise connector catalog - define integration standards, security review gates, and onboarding playbooks for teams publishing MCP servers to Quick.
- Build platform-level integration infrastructure: auth plumbing (Entra/OAuth 2.0), connector health monitoring, and lifecycle tooling.
- Serve as the senior technical contact for domain teams (Snowflake, Salesforce, ServiceNow, Seismic) building MCP servers - unblock them, enforce guardrails, review designs, and ensure production readiness.
- Build connectors for systems where no dedicated team exists - AS400 wholesale auction databases, multi-step Databricks pipelines, internal REST/gRPC services, or whatever the business needs next.
- Own and evolve the AI Artifact Hub - harden the product, improve reliability, and ship features that make it a core part of how the org builds with AI.
- Build and improve knowledge ingestion pipelines - chunking strategies, metadata extraction, and retrieval quality tuning.
- Develop agents, skills, and automation workflows that solve real business problems through the Quick platform.
- Design and implement fine-grained access controls and DLP enforcement - when an agent queries Snowflake or Office 365 on behalf of a user, it must strictly respect row-level permissions and never surface unauthorized data in prompt contexts.
- Adopt spec-driven, verification-first development practices - define expected behavior before implementation, especially when building with AI-assisted tooling.
- Build the operational backbone for AI at scale - cost tracking by team/department, proactive circuit breakers for runaway token loops, and fallback handling when underlying services degrade.
- Design evaluation frameworks and automated "ground truth" test suites - measure whether changes to agent instructions improve or degrade accuracy across dozens of business workflows before they hit production.
- Build feedback loop APIs (Lambda, Step Functions) that capture human-in-the-loop corrections and feed quality signals back into the platform.
- Implement observability across the stack: usage metrics, latency, error rates, cost dashboards, and security-aware alerting.
- Participate in design and code reviews. Mentor junior engineers through pairing and knowledge sharing.
- Collaborate with the Principal Engineer on architecture decisions and technical direction.
- Work directly with AWS technical teams to troubleshoot issues, provide feedback, and adopt new capabilities.
- Bachelor's degree (list any requirements of discipline here) and 4 years' experience in a related field. The right candidate could also have a different combination, such as a master's degree and 2 years' experience; a Ph.D. and up to 1 year of experience; or 16years' experience in a related field.
- 5+ years of professional software development experience, including designing, building, and operating production systems.
- Strong proficiency in Python, including building APIs, data pipelines, and integrations.
- Hands-on experience with AWS services (Lambda, S3, IAM, API Gateway, CloudWatch, Step Functions, or similar).
- Experience building integrations with third-party APIs and SaaS platforms, including authentication flows (OAuth 2.0, OIDC).
- Experience with Infrastructure as Code (Terraform preferred) and CI/CD pipelines (GitHub Actions preferred).
- Solid understanding of distributed systems concepts: fault tolerance, idempotency, eventual consistency, and graceful degradation.
- Experience designing and enforcing authorization policies in multi-tenant or multi-user systems (row-level security, ABAC, or similar).
- Comfort working in a small, fast-moving team where you own what you build end-to-end.
- Strong communication skills. Able to explain technical decisions clearly and collaborate across teams.
- Applicants must be authorized to work in the United States for any employer without current or future sponsorship.
- Ability to work in the office three days per week.
- Willingness to participate in an on-call rotation for production platform systems.
- Experience with AI/ML-powered systems, with exposure to emerging patterns such as RAG, knowledge retrieval, or agent-based architectures.
- Experience with Amazon Bedrock, AWS managed AI/ML services, or a comparable enterprise AI platform.
- Familiarity with the Model Context Protocol (MCP) or experience building agent/tool integration layers.
- Experience with Snowflake, semantic views, or similar data platform technologies.
- Background in knowledge graphs, embeddings, vector stores, or enterprise search/retrieval systems.
- Experience building evaluation or testing frameworks for non-deterministic systems (ML model eval, A/B testing infrastructure, or similar).
- Familiarity with cost optimization in cloud-native architectures - FinOps thinking, usage metering, or chargeback systems.
- Experience with data loss prevention, PII detection/redaction, or security controls in data pipelines.
- Experience with event-driven architectures or workflow engines (Step Functions, Temporal).
- Experience building or operating internal developer platforms or developer tooling.
- Experience taking ownership of an inherited codebase and improving it to a well-documented, supportable state.
- Prior work in automotive, media, or another large enterprise with a complex system landscape is an advantage but not required.
Vacancy posted 1 day ago
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