AI Engineer

• Build automation workflows using n8n.io and Python as the primary platform.
• Integrate APIs, databases, and AI services to create functional, scalable automation pipelines.
• Work with tools like Claude Code, Codex GitHub Copilot to build agents, streamline development, and generate value from LLMs.
• Write and test prompts that enable AI to complete meaningful tasks—text classification, summarization, chatbot functionality, and more.
• Build task-specific AI agents or multi-step assistants powered by APIs and large language models.
• Take abstract product ideas and build working MVPs quickly, with clarity and minimal oversight.
• Partner with engineering leads and other Augusto team members to deliver meaningful, production-ready solutions.
• Explain technical designs and limitations clearly to both technical and non-technical stakeholders.

AI Workflow Engineer, Developer

• Partner with AI Solution Engineers, Architects, and senior technical teammates
• Design, build, and deploy AI-powered solutions for legal customers
• Translate legal workflows and business needs into technical solutions
• Contribute to technical discovery, solution delivery, and prototyping
• Assist with demonstrations, proofs of concept, and early-stage prototypes
• Develop working knowledge of legal terminology and processes
• Design and implement AI-powered solutions for legal workflows
• Collaborate with senior engineers and architects to ensure solutions are scalable
• Evaluate LLM outputs for legal accuracy and relevance

Software Engineer – AI, CoCounsel Forward Deployed Engineering

• Creating the future of smart mobility requires the highly intelligent use of data, metrics, and analytics. That’s where you can make an impact as part of our Global Data Insight & Analytics (GDIA) team.
• Responsible for designing, developing, testing and maintaining software applications and products to meet customer needs both on-prem and cloud native.
• Involved in the entire software development lifecycle including designing software architecture, writing code, testing for quality and deploying the software to meet customer requirements.
• Full-stack software engineering roles, who can develop all components of software including user interface and server side also fall within this job function.

AI/ML Engineer

• Ship and debug code on a live, real-time voice pipeline
• Design control systems around LLMs: guardrails, budgets, watchdogs
• Build and operate LLM evaluation and batch-analysis pipelines
• Own traditional ML workflows from data to scheduled production inference
• Trace production issues from a metric anomaly to root cause

Senior Software Engineer – Applied AI

• Own stakeholder relationships across Medbridge’s executive team, working with them to find the problems and AI enabled solutions that can expedite, or remove, the current blockers in the business.
• Design, build, and ship AI-powered features across our internal teams, from the user interface to the backend services and AI workflows behind it.
• Build full-stack applications using AI-native engineering workflows and tools such as Claude, Cursor, Codex, and OpenAI and Anthropic APIs.
• Develop APIs, backend services, and automation pipelines that support intelligent product capabilities and production-ready deployments.
• Apply software engineering, DevOps, and MLOps best practices to the testing, deployment, monitoring, evaluation, and optimization of AI solutions.
• Partner closely with our Product and Engineering teams to turn ambiguous goals into scalable internal products.
• Use AI tooling throughout your workflow (coding, code review, testing, and planning) and help push the team’s adoption forward.
• Research emerging AI technologies, LLM implementation patterns, and modern product engineering frameworks, and bring what works back to the team.
• Instrument what you ship and use usage data and evidence to decide what to build, fix, or kill next.

Product Engineer – AI

• Design, develop, and deploy machine learning models and AI-powered applications
• Collaborate with cross-functional teams to identify and implement AI/ML solutions for client needs
• Build and maintain data pipelines, model training workflows, and inference systems
• Evaluate and integrate large language models (LLMs), generative AI tools, and emerging AI frameworks
• Monitor model performance, conduct testing, and iterate on improvements
• Document technical architectures, methodologies, and best practices
• Stay current with AI/ML research and translate advancements into practical applications

• Define and evolve enterprise AI architecture, standards, reference models and implementation guidelines to support consistent solution delivery across business functions
• Align AI initiatives to enterprise strategies, roadmaps, and business priorities
• Identify and prioritize AI opportunities that drive student success and operational efficiency
• Design scalable AI platforms and solutions across data, application, and technology domains
• Provide guidance on how AI, ML, and automation will improve current and future-state architectures
• Lead design and implementation of AI-powered solutions (e.g., LLMs, agents, automation, and analytics)
• Integrate AI capabilities with enterprise applications and data platforms
• Guide evaluation and selection of AI/ML models, frameworks, and vendors
• Establish reusable patterns, APIs, and integration approaches
• Establish governance practices covering model oversight, responsible AI usage, security controls, compliance expectations, and lifecycle management
• Establish AI governance, including responsible AI, security, privacy, and compliance (FERPA, HIPAA, GDPR)
• Establish lifecycle management practices (MLOps/LLMOps, model monitoring, drift detection, retraining)
• Implement performance, bias, and risk monitoring frameworks
• Ensure secure AI architecture (e.g., data protection, isolation, adversarial defense)
• Partner with business, product, data, and engineering teams to provide AI solutions
• Provide architectural guidance to architects and delivery teams
• Facilitate workshops, POCs, demos and AI adoption projects identifying viable opportunities where AI can be a positive differentiator
• Mentor teams on AI best practices, patterns, and frameworks

Enterprise AI Architect

• Transform the Integrated Services Product Team Operating Model: Identify, redesign, and scale AI-enabled workflows across discovery, customer research, Product Requirement Document (PRD) roadmaps, prioritization, launch readiness, executive reviews, analytics, PMO, go-to-market, and post-launch learning.
• Build AI Agents, Automation and Infrastructure: Create, configure, test, and maintain AI agents, tools, workflows, and integrations using APIs, retrieval, orchestration, agent instructions, approved AI platforms, enterprise systems, and related technical patterns.
• Prototype, Pilot and Scale: Rapidly prototype with real users, validate workflow fit, identify failure modes, and move successful solutions from idea to prototype to pilot to scaled adoption, working through technical, operational, security, privacy, and change-management barriers.
• Create Reusable Capabilities and Playbooks: Build repeatable agents, templates, standards, workflows, and best practices for common product, PMO and GTM work, including customer insight synthesis and journey mapping, requirement generation, PRD review, competitive analysis, roadmap tradeoffs, launch planning and execution, risk reviews, business case development, and executive communication.
• Measure Impact: Define and track outcomes tied directly to business and customer value creation, including adoption, time saved, cycle-time reduction, decision speed, employee experience, quality improvements, rework reduction, revenue generation and business or customer outcomes from AI enabled workflows.
• Drive Adoption and Behavior Change: Train teams, coach leaders, create champions, document best practices, and make AI-enabled workflows easy, safe and useful enough to become the default way of working.
• Establish Quality, Governance and Trust: Partner with security, legal, privacy, IT, PMO, go-to-market and engineering to ensure workflows are secure, compliant, auditable, explainable, and appropriate for enterprise use.
• Design Human-In-The-Loop Systems: Define where AI should act independently, where humans must review or approve, and how teams should manage risk, quality and accountability in AI-enabled workflows.
• Increase Leverage: Identify and automate repetitive, manual, duplicative, or low-value work so teams can spend more time on customer insight, product judgment, and execution.
• Evaluate Emerging AI Patterns: Stay current on AI agent frameworks, tooling, security models, governance practices, workflow automation approaches, and enterprise patterns, then translate the most practical opportunities into Ford use cases.

Director, AI Transformation Architect

• Design and implement enterprise semantic models and certified KPI layers to ensure trusted, reusable business metrics.
• Build AI-safe data abstraction layers that prevent metric recomputation and ensure consistency across analytics and AI use cases.
• Develop and enforce data contracts, metadata standards, and semantic governance frameworks across domains.
• Engineer scalable batch and real-time streaming data pipelines in a modern cloud environment (GCP preferred).
• Collaborate with AI/ML teams to design reliable grounding strategies for AI applications and agents.
• Implement metadata management capabilities including cataloging, lineage, observability, and automated data quality checks.
• Apply DataOps principles including CI/CD, automated testing, and deployment automation for data products.
• Support domain-oriented and microservices-based data architecture patterns.
• Mentor engineers and promote best practices in semantic modeling, governance, and AI-ready platform design.

Senior AI Context Engineer

• Identify engineering pain points and propose/design/implement solutions that are reliable, scalable, and maintainable
• Influence the team’s technical roadmap
• Evaluate new tools and technologies through PoCs
• Ship improvements to our AV development toolchains and services which have a measurable and direct impact on engineering productivity and our core company metrics
• Drive software engineering best practices within your team, and create tooling which encourages these
• Help steer the engineering culture on the team
• Guide the team to find the right balance between delivering impact and addressing technical debt
• Mentor and grow engineers on the team
• Set the example for high levels of accountability
• Execute and deliver impact both individually and through the team
• Set strong boundaries when selecting external requests and pushing back on requests that do not align with our team vision

Staff AI/ML Engineer, Developer Productivity

• Build and maintain shared infrastructure: secure web app hosting infrastructure, MCP/API standards, secret/key management, model selection, guardrails, and a centralized pattern library that all builders across the organization can pull from.
• Own the review, tracking, and advisory process for all corporate AI and automation builds — MCP servers and tool configurations, Claude Skills, API integrations, and agentic workflows — before deployment.
• Partner directly with AI specialists across departments to identify, scope, and build AI and automation solutions that meet high standards for cost, security, and scalability security before they ship.
• Define and maintain the secure intake path for AI and automation requests across the organization, replacing ad-hoc builds and shadow IT with a governed, cost-effective, and scalable process.
• Contribute to the organization’s AI cost efficiency by monitoring, alerting, and setting thresholds on AI spend across usage-based tools and platforms.

AI & Automations Lead

• Integrate conversational AI assistant features into software applications, owning the experience end to end
• Design, implement, and evaluate tool/function calling so AI assistants can reliably invoke backend capabilities and return correct, useful results
• Write, test, and refine prompts; evaluate and improve the accuracy and effectiveness of LLM and tool-calling behavior
• Build, train, and evaluate machine learning models for classification, prediction, and simulation tasks
• Collaborate with software engineers to integrate AI capabilities into applications and services
• Use Git for version control and contribute to shared team repositories
• Document your work and communicate results clearly to technical and non-technical stakeholders
• Support deployment, testing, and iteration of AI capabilities alongside the broader engineering team

• Use Claude Code to implement new features and functions within the platform
• Translate product requirements and design specs into clean, production-ready code
• Review and refine AI-generated code to ensure correctness, performance, and maintainability
• Leverage AI to write and update automated tests for all new functionality
• Participate in async code reviews and provide constructive feedback
• Ensure new features, APIs, and architectural decisions are documented as they are built
• Proactively identify technical debt or gaps and surface them to the team

AI Software Developer

• Design and Build Agentic Workflows: Design and build AI-powered applications, agents, and intelligent workflows that improve discovery, recommendation, and analysis of marketing enterprise analytics assets, customer data, and media metrics.
• Architect Autonomous Loops: Transition from linear "chain" workflows to self-correcting agentic loops using frameworks like LangChain, LangGraph, or LlamaIndex to automate complex marketing analytics workflows.
• Implement Tool-Use & MCP: Design and implement robust "tool-calling" capabilities, ensuring LLMs can reliably interact with external marketing APIs, Customer Data Platforms (CDPs), and internal media databases. Build and maintain Model Context Protocol (MCP) servers to bridge the gap between LLMs and our proprietary marketing data silos securely and in real-time.
• Develop High-Concurrency Backends: Develop asynchronous Python (FastAPI/Flask) or Java (Spring Boot) backend services optimized for long-running AI tasks, marketing attribution modeling, and real-time token streaming.
• Build Streaming Frontends: Build responsive, stateful UIs in React or Angular that handle complex AI interactions (streaming text, generative UI components, and multi-modal feedback).
• Optimize Advanced RAG Pipelines: Implement advanced RAG pipelines (re-ranking, query transformation, and embedding optimization) to maximize retrieval precision over vast libraries of marketing assets, creative guidelines, and historical campaign results.
• Establish AI Evals & Observability: Establish AI Evals to quantify hallucination rates, latency, and cost, leading the shift from "vibes-based" testing to rigorous, automated AI benchmarking.
• Collaborate & Guide: Collaborate with product managers, marketing experts, and domain stakeholders to translate business needs into technical solutions. Drive architecture decisions, engineering best practices, and operational excellence.

AI Software Engineer

• Responsible for architecting solutions achieving customer business outcomes
• Develop and articulate compelling, accurate, and relevant proposals
• Provide technical expertise to sales teams and customers
• Develop customer proposals and critically review them
• Quantify the impact of business problems and position business value
• Communicate how the solution value propositions address customer business needs
• Drive the Account Business Planning process leveraging knowledge of industry trends and customer’s technical environment

AI Architect – Pre-Sales

• Lead the design, development, and deployment of production AI systems end-to-end
• Contribute hands-on to the codebase and set a high bar for engineering quality
• Establish scalable patterns for evaluation, deployment, and system reliability
• Conduct technical design reviews and guide architectural decisions
• Mentor and develop engineers, providing regular coaching and technical guidance
• Support hiring efforts, including candidate evaluation and onboarding
• Partner with cross-functional stakeholders to align priorities and deliver impactful solutions
• Help translate experimentation into stable, production-ready systems

AI Engineer jobs in Missouri

See all jobs on JobTailor

AI Workflow Engineer, Developer

Software Engineer – AI, CoCounsel Forward Deployed Engineering

AI/ML Engineer

Senior Software Engineer – Applied AI

Product Engineer – AI

AI Engineer

Enterprise AI Architect

Director, AI Transformation Architect

Senior AI Context Engineer

Staff AI/ML Engineer, Developer Productivity

AI & Automations Lead

AI Engineer

AI Software Developer

AI Software Engineer

AI Architect – Pre-Sales

Full Stack AI Engineer

Full Stack AI Engineer