Senior AI & Data Solutions Engineer

Flint Hills Resources

Atlanta, Plano, Wichita (GA, TX, KS)

Hybrid

USD 120,000 - 180,000

Full time

6 days ago

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Job summary

Koch Technology Data Solutions (KTDS) seeks a Senior Software Engineer to design, build, and support secure, scalable data, software, and AI-enabled solutions. This role blends hands-on engineering with solution architecture, leading complex initiatives and applying AI-DLC practices to deliver reusable solutions that create measurable business value.

The ideal candidate is a technically strong engineer who enjoys solving complex problems, shaping solution strategy, and leveraging AI capabilities

Qualifications

Demonstrated experience designing, building, deploying, and supporting production software, data, and AI-enabled solutions.
Experience leading technical design, architecture, or implementation efforts across large-scale, multi-team initiatives.
Experience mentoring engineers through design reviews, code reviews, technical guidance, or pair programming.
Demonstrated experience using Python and SQL to develop production applications, including source control, automated testing, CI/CD, observability, and orchestration practices.
Experience building and supporting cloud-native solutions on AWS, including serverless, event-driven, and containerized applications.
Experience communicating technical concepts and solution trade-offs to technical and business stakeholders.

Responsibilities

Lead the design and delivery of AI, data, and software solutions across multiple systems, including data pipelines, APIs, applications, agents, automations, and AI-enabled workflows.
Apply AI-DLC practices to accelerate development while ensuring solution quality, security, scalability, and operational readiness.
Partner with architects, capability leaders, SMEs, and users to translate business needs into supportable technical solutions.
Design and operationalize generative AI, agentic AI, semantic layer, and retrieval-augmented generation (RAG) capabilities using modern integration standards such as MCP.
Drive sound technical decisions by balancing architecture, delivery timelines, risk, operational support, and long-term maintainability.
Mentor engineers through technical leadership, design reviews, code reviews, and hands-on coaching while contributing directly to solution delivery.
Continuously evaluate emerging AI models, frameworks, and engineering practices to improve solution outcomes.