Sr Software Engineer

Cox Enterprises • Atlanta, GA

6d • $101,500 - $169,100 • Hybrid

About The Position

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.

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• 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.

Benefits

• flexible vacation with pay
• seven paid holidays
• up to 160 hours of paid wellness annually
• bereavement leave
• time off to vote
• jury duty leave
• volunteer time off
• military leave
• parental leave
• health care insurance (medical, dental, vision)
• retirement planning (401(k))
• paid days off (sick leave, parental leave, flexible vacation/wellness days, and/or PTO)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior