Head Of Software Development Jobs in Missouri (NOW HIRING)

As a Head of AI Engineering, you will be responsible for defining the AI vision, building scalable AI capabilities, and enabling teams to adopt AI effectively across the organization. You will combine technical leadership, strategic thinking, and operational execution to create secure, reliable, and impactful AI solutions.

• Define and execute an AI strategy and roadmap focused on building AI capabilities as a core technology platform.
• Assess existing AI tools, vendors, internal solutions, costs, ownership models, risks, and unofficial AI usage across the organization.
• Establish an AI operating model, including ownership structures, initiative prioritization, experimentation processes, and production deployment standards.
• Design and implement AI platform architecture, including AI gateways, authentication, access controls, model routing, logging, cost management, usage tracking, and audit capabilities.
• Define and manage an approved AI technology ecosystem covering models, vendors, APIs, SaaS solutions, self-hosted components, and platform standards.
• Drive AI adoption across engineering productivity, code reviews, testing, automation, refactoring, support, analytics, product, and marketing workflows.
• Establish AI governance and security practices covering sensitive data, private repositories, credentials, production systems, compliance, and risk management.
• Implement AI observability and evaluation frameworks to monitor quality, reliability, latency, usage, costs, and return on investment.
• Create AI adoption programs, including training, internal champions, playbooks, and best practices for responsible AI usage.
• Build and lead an AI Engineering function with a scalable model combining centralized platform capabilities and domain-driven AI initiatives.
• Collaborate with technical and business leaders to align AI initiatives with organizational priorities.
• Provide technical guidance, review architecture decisions, and ensure AI solutions move successfully from experimentation to production.

You are an experienced AI engineering leader with a proven ability to build platforms, establish technical strategies, and drive large-scale adoption of emerging technologies. You combine deep AI expertise with strong leadership skills and the ability to influence across multiple teams.

• Experience in a Head of AI, Engineering Manager, Head of Platform, Director of AI Engineering, or similar leadership role.
• Proven experience building technology platforms, engineering capabilities, or AI-focused functions from strategy through execution.
• Strong understanding of production AI systems, including architecture, reliability, latency, cost management, observability, evaluation, security, and lifecycle management.
• Deep knowledge of LLMs, RAG architectures, AI agents, tool/function calling, model routing, prompt lifecycle management, and evaluation frameworks.
• Strong understanding of software development processes and how AI can improve engineering productivity, testing, code review, documentation, and onboarding.
• Strong security mindset with experience addressing data leakage, privacy risks, prompt injection, unsafe tool access, secrets management, and vendor risks.
• Understanding of AI FinOps concepts, including total cost of ownership, budgeting, forecasting, vendor management, and ROI analysis.
• Ability to collaborate effectively with CTOs, engineering leaders, security teams, product teams, analytics teams, and business stakeholders.
• Ability to balance strategic leadership with hands-on technical involvement when needed.
• Proven ability to transform AI strategies into measurable outcomes through roadmaps, execution plans, adoption metrics, and continuous improvement.
• Bonus: Experience building or implementing AI gateways or proxy layers such as LiteLLM or similar solutions.
• Bonus: Experience driving adoption of AI developer tools such as GitHub Copilot, Cursor, JetBrains AI, or equivalent platforms.
• Bonus: Background in Platform Engineering, Internal Developer Platforms, DevEx, or Engineering Productivity.
• Bonus: Experience with AI solutions for QA automation, support, analytics, marketing, or operational workflows.
• Bonus: Experience with self-hosted models, model serving, AI observability, or evaluation pipelines.
• Bonus: Familiarity with engineering and infrastructure tools such as GitHub, GitLab, Jira, Slack, CI/CD platforms, cloud environments, or hybrid infrastructure.

• Fully remote work environment with flexibility to work from a location that suits you.
• Official employment support in available regions with assistance for administrative processes.
• 20 paid vacation days, public holidays, and sick leave support.
• Medical insurance through leading healthcare providers.
• Mental health support and access to professional wellbeing services.
• Monthly benefits budget that can be used for hobbies, sports, and personal interests.
• Professional development opportunities, including courses, workshops, mentoring programs, and language learning.
• Access to corporate events, team activities, and community initiatives.
• Opportunity to build advanced AI capabilities from the ground up in a technology-focused environment.
• Culture based on autonomy, openness, innovation, and continuous growth.