Cox Enterprises Jobs

Principal Software Engineer

Cox Enterprises

Principal Software Engineer

Posted 5 Hours Ago

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Atlanta, GA, USA

Hybrid

163K-272K Annually

Expert/Leader

Artificial Intelligence • Automotive • Greentech • Information Technology • Machine Learning • Software • Cybersecurity

Building a better future for this generation and the next.

The Role

Owns architecture and technical direction for enterprise AI platforms, AWS Quick integrations, and an internal AI Artifact Hub. Leads development of connectors, agents, knowledge retrieval, MCP servers, data pipelines, quality systems, observability, and resilient distributed workflows. Guides Python engineering, architecture reviews, incident response, and cross-functional alignment with security, cloud, enterprise architecture, and AWS teams. Establishes standards for AI evaluation, governance, reliability, and verification-first development.

Summary Generated by Built In

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 seeking a Principal Software Engineer to own technical direction for the platform, the applications, and integrations around it. This role shapes architecture across two products: AWS Quick, an emerging AI platform for agents and enterprise connectors; and an established internal AI Artifact Hub used across Cox Automotive that lets engineering and product teams publish and share interactive artifacts through a web experience and an MCP server interface.
This is a hands-on technical leadership role. You will make the key architecture and engineering decisions, lead engineers through implementation, and stay close enough to the code to review designs, debug difficult issues, and contribute where it matters. The team builds connectors, agents, knowledge bases and data pipelines, and quality systems that integrate Quick with Cox Automotive's core enterprise tools and operational systems.
This is early-stage work with executive sponsorship, direct access to AWS technical teams, and the autonomy to define the architecture.
What You'll Do
Architecture & Technical Direction

Own the end-to-end architecture for the AWS Quick customization layer, including connectors, agent orchestration, knowledge ingestion, service boundaries, and infrastructure as code.
Define the Model Context Protocol (MCP) strategy for enterprise integrations: tool contracts, governance, authentication, authorization, and safety boundaries.
Own the technical direction of the AI Artifact Hub. Assess its current state, define a hardening plan, and improve reliability as adoption grows.
Make and document major architecture decisions, including the trade-offs behind them. Build for near-term delivery without closing off the platform's next stage.
Work with Enterprise Architecture, Security, Cloud Automation, and AWS technical teams to align platform direction and resolve cross-team issues.

AI Platform Engineering & Quality

Own the quality and evaluation approach for AI capabilities, including automated regression tests, measurable acceptance criteria, and human-in-the-loop (HITL) feedback.
Lead technical decisions around enterprise knowledge and retrieval, including ingestion, content curation, metadata, knowledge graphs, retrieval quality, context management, and platform-supported RAG configuration.
Define standards and reusable patterns for agents and skills.
Set the design for MCP servers, tool interfaces, and structured APIs intended for agent use.
Establish spec-driven, verification-first practices for AI-assisted software development. Evaluate new capabilities and adopt them when they improve delivery without weakening quality or security.

Resilient Distributed Systems

Set production reliability standards for AI-enabled integrations, including monitoring, observability, graceful degradation, and incident response.
Define failure and recovery patterns: timeouts, bounded retries with backoff, circuit breakers, and clear fallback behavior.
Define idempotency and durable workflow patterns for operations that cross service or third-party boundaries.
Lead response to significant platform incidents and drive the follow-up engineering work.

Technical Leadership & Influence

Lead architecture and design reviews. Pair with engineers on the hardest problems and raise the team's engineering judgment.
Guide the team's Python implementation through design, code review, debugging, and targeted production contributions.
Serve as a senior technical contact for AWS on platform architecture, product capabilities, and roadmap needs.
Explain technical direction and trade-offs clearly to engineering, product, security, and senior leadership.
Represent the platform team in cross-organization technical forums and build alignment across team boundaries.

Who You Are

Bachelor's degree in Computer Science and 10 years' experience in a related field. The right candidate could also have a different combination, such as a master's degree and 8 years' experience; a Ph.D. and 5 years' experience in a related field; or 22 years' experience in a related field.
10+ years of experience across the software development life cycle, architecture, and platform delivery.
Strong experience designing and delivering cloud-native platforms on AWS, including compute, storage, networking, IAM, observability, and infrastructure automation.
Experience designing, building, or operating AI/ML-powered systems, with exposure to emerging patterns such as RAG, knowledge retrieval, or agent-based architectures.
Strong software engineering fundamentals and working proficiency in Python. Able to design, review, debug, and contribute to Python-based connectors, pipelines, and tooling.
Experience defining evaluation and quality approaches for software, including regression testing, measurable acceptance criteria, HITL review, or other methods suited to non-deterministic systems.
A track record of enterprise integration work across SaaS, data platforms, and operational systems, including API design, authentication (OAuth 2.0, OIDC, SSO), data quality, and reliability concerns.
Demonstrated ownership of a platform or system architecture used by multiple engineering teams.
Experience setting technical direction and influencing decisions across team boundaries without relying on formal authority.
Experience establishing engineering practices and team norms in a newly formed team.
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 and lead incident response for production platform systems.

Preferred Qualifications

Experience with Amazon Bedrock, AWS managed AI/ML services, or a comparable enterprise AI platform.
Experience working directly with a cloud or platform vendor on product capabilities and roadmap priorities.
Familiarity with the MCP specification and SDKs, or experience building comparable agent/tool integration layers and governance patterns.
Background in knowledge graphs, graph databases, or enterprise knowledge and retrieval systems.
Experience with Infrastructure as Code (preferably Terraform) and CI/CD for cloud or AI-enabled systems. Familiarity with GitHub Actions and self-hosted runners is a plus.
Experience with HITL workflows, agent orchestration, evaluation harnesses, or LLM-backed middleware.
Experience with Snowflake, including semantic views or similar semantic-layer technology.
Background in data loss prevention, PII redaction, or zero-trust data pipelines.
Experience building internal developer platforms, developer tooling, or platform-as-a-product capabilities.
Experience taking ownership of an inherited codebase and bringing it to a supportable, well-documented state.
Experience with event-driven architectures and workflow engines such as AWS Step Functions or Temporal.
Experience establishing spec-driven development, evaluation, governance, or verification practices for AI-assisted engineering.
Prior work in automotive, media, or another large enterprise with a complex system landscape is an advantage but not required.
Experience designing and operating APIs for other teams, including versioning and backward compatibility.

USD 163,400.00 - 272,300.00
Compensation:
Compensation includes a base salary in the range of $163,400.00 - $272,300.00. The base salary may vary within the anticipated base pay range based on factors such as the ultimate location of the position and the selected candidate's knowledge, skills, and abilities. Position may be eligible for additional compensation that may include an incentive program.
Benefits:
The Company offers eligible employees the flexibility to take as much vacation with pay as they deem consistent with their duties, the company's needs, and its obligations; seven paid holidays throughout the calendar year; and up to 160 hours of paid wellness annually for their own wellness or that of family members. Employees are also eligible for additional paid time off in the form of bereavement leave, time off to vote, jury duty leave, volunteer time off, military leave, and parental leave.
EOE, including disability/vets

Skills Required

Bachelor's degree in Computer Science and 10 years of related experience, or an equivalent combination such as a master's degree with 8 years, a Ph.D. with 5 years, or 22 years of related experience
10+ years of experience across the software development life cycle, architecture, and platform delivery
Experience designing and delivering cloud-native platforms on AWS, including compute, storage, networking, IAM, observability, and infrastructure automation
Experience designing, building, or operating AI/ML-powered systems, including RAG, knowledge retrieval, or agent-based architectures
Strong software engineering fundamentals and working proficiency in Python
Experience defining software evaluation and quality approaches, such as regression testing, measurable acceptance criteria, or human-in-the-loop review
Enterprise integration experience across SaaS, data platforms, and operational systems, including API design, authentication, data quality, and reliability
Experience owning a platform or system architecture used by multiple engineering teams
Experience setting technical direction and influencing decisions across team boundaries without formal authority
Experience establishing engineering practices and team norms in a newly formed team
Authorization 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 and lead production platform incident response
Experience with Amazon Bedrock, AWS managed AI/ML services, or a comparable enterprise AI platform
Experience working directly with a cloud or platform vendor on product capabilities and roadmap priorities
Familiarity with the MCP specification and SDKs, or comparable agent and tool integration layers
Background in knowledge graphs, graph databases, or enterprise knowledge and retrieval systems
Experience with Infrastructure as Code, preferably Terraform, and CI/CD for cloud or AI-enabled systems
Familiarity with GitHub Actions and self-hosted runners
Experience with human-in-the-loop workflows, agent orchestration, evaluation harnesses, or LLM-backed middleware
Experience with Snowflake, including semantic views or similar semantic-layer technology
Background in data loss prevention, PII redaction, or zero-trust data pipelines
Experience building internal developer platforms, developer tooling, or platform-as-a-product capabilities
Experience taking ownership of an inherited codebase and making it supportable and well documented
Experience with event-driven architectures and workflow engines such as AWS Step Functions or Temporal
Experience establishing spec-driven development, evaluation, governance, or verification practices for AI-assisted engineering
Prior experience in automotive, media, or another large enterprise with a complex system landscape
Experience designing and operating APIs for other teams, including versioning and backward compatibility

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The Company

HQ: Atlanta, Georgia

30,000 Employees

Year Founded: 1898

What We Do

Cox Enterprises is a family-owned enterprise spanning 125+ years of innovation. Through our diverse network of businesses, our people are shaping the future with bold thinking, cutting-edge technology and an unwavering commitment to doing what’s right. Across a range of industries — including automotive, agriculture, cleantech, journalism and more — we’re building a better future for this generation and the next. Make your mark at Cox!

Why Work With Us

Founded in 1898, Cox Enterprises is a community of kind, grounded individuals who work together to drive positive change across vital industries. At Cox, employees experience meaningful work, great benefits, work-life balance and a supportive team environment, plus ample opportunities for career growth across our family of businesses.