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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Applied AI Engineer - Information Intelligence and Automation (mid) - **Company:** Tesla, Inc. - **Location:** St. Louis, MO, United States (Remote available) - **Experience:** Experienced - **Salary:** $125,000.0 - $175,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Automated Storage and Retrieval Systems, Databases, Information Retrieval, Python (Programming Language), Open Source Technology, Regression Testing, Cloud Services, Software Deployment, Systems Architecture, Data Ingestion, Large Language Models, Software Application Programming, Web Content, Containerization, Information Technology, Low Latency, Data Analytics, Api Design, Splunk, Data Pipelines, Docker, Programming Languages - **Published:** September 16, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=c7ca8cae8fec0e9d ## About the Role * Bachelor's degree in computer science, data science, engineering, statistics, or a related technical field, or equivalent professional experience. * 5+ years of professional software, data, ML, or AI engineering experience, with demonstrated experience building and deploying technical solutions. * Professional experience developing applications using Python or another modern programming language. * Experience working with at least one commercial or open-source LLM and its API. * Experience building AI-powered applications using techniques such as retrieval, structured outputs, tool use, prompting, or grounding. * Experience working with APIs, data pipelines, or cloud-based services. * Experience containerizing and deploying applications using Docker and AWS ECR/ECS. * Demonstrated ability to troubleshoot complex technical problems and work independently when requirements or solutions are not fully defined. * Strong written and verbal communication skills, including the ability to explain technical concepts to nontechnical stakeholders. * Strong attention to detail and an ability to critically evaluate AI-generated outputs rather than assuming they are correct. Desired Experience: * Experience building production RAG or LLM-based applications. * Experience designing or implementing AI evaluation frameworks, benchmarks, or regression testing. * Experience with Amazon Bedrock. * Experience with Splunk. * Experience with PDF/OCR pipelines, document parsing, layout-aware extraction, or table extraction. * Experience with vector databases, embeddings, search, or information retrieval. * Experience optimizing AI systems for cost, latency, scalability, and reliability. * Experience working with government, defense, or intelligence agencies. * Experience with data analytics, predictive modeling, or user behavior analysis. * Experience taking an AI prototype from experimentation through production deployment. ## Description Position Description: Tesla Government is seeking an Applied AI Engineer to help turn AI capabilities into reliable tools that improve how our staff and clients work with user behavior data, open source information, and official government reporting, supporting key projects for a number of US and partner nation entities. As a mid-level expert, the Applied AI Engineer is responsible for understanding business challenges and identifying and applying AI to solve problems., Build Applied AI Solutions * Design and develop AI-powered applications and services using commercial and open-source foundation models. * Work with models available through Amazon Bedrock, evaluating and selecting models based on capability, reliability, cost, latency, and operational requirements. * Project token costs, submit token budget estimates and expected output values for prior approval, and present expected ROI for each project. * Build production workflows incorporating LLMs, retrieval, structured outputs, APIs, and other AI capabilities. * Use grounding, citations, retrieval, structured generation, and appropriate refusal or uncertainty behaviors to improve reliability and reduce hallucination. * Work with Data Team and Customer Success colleagues to understand business and user needs into practical AI solutions. * Clearly communicate model capabilities, limitations, risks, and expected performance to technical and nontechnical staff and clients. Build Data Pipelines * Build data ingestion and transformation pipelines for structured and unstructured sources, including databases, web content, PDFs, documents, and data integrated with Tesla's GovShare platform. * Automate data collection, cleaning, transformation, extraction, and analysis. * Develop solutions for document processing, including OCR, layout-aware parsing, table extraction, and other techniques where appropriate. * Design systems that maintain data quality, traceability, and provenance throughout the AI pipeline. Own AI Evaluation & Reliability * Own the evaluation harness for the AI features you build. * Develop representative evaluation datasets and test cases for AI applications. * Define measurable criteria for accuracy, relevance, grounding, hallucination, refusal behavior, and other task-specific requirements. * Establish regression testing so that changes to prompts, models, retrieval systems, or code can be evaluated before implementation. * Analyze failures and use evaluation results to improve prompts, models, retrieval strategies, data, and system architecture. * Monitor production performance using AWS and Splunk, and identify opportunities to improve quality, cost, and latency. Identify & Automate Opportunities * Analyze existing workflows and identify opportunities where AI or automation can reduce repetitive work, improve decision-making, or increase efficiency. * Work with departments across Tesla Government to understand their workflows and develop appropriate automation solutions. * Prototype, evaluate, and implement approved automation opportunities. * Measure the impact of new solutions, including time savings, improved accuracy, increased adoption, or other relevant business outcomes. * Explore emerging AI technologies and determine where they can provide practical value rather than adopting technology for its own sake. Collaborate Across Tesla * Translate technical concepts and AI limitations for nontechnical audiences. * Help staff and clients understand both the capabilities and limitations of AI-enabled tools. * Contribute technical expertise to client engagements when appropriate. * Participate in business development activities where technical expertise can help communicate the value and feasibility of AI solutions. What Success Looks Like: * Delivering production-ready AI and automation solutions that solve meaningful government problems. * Time savings for the Data Team and other Tesla departments gained through new AI-based tools * Building AI systems whose performance can be measured in time savings, cost avoidance, user adoption, or other KPIs you establish with your supervisor. * Implementing citation, grounding, and refusal patterns so the model says "I do not know" instead of hallucinating * Improve the speed, cost, accuracy, or usability of existing workflows. * Helping teams across Tesla Government identify practical opportunities to use AI. * Clearly communicating what AI can and cannot do. * Demonstrating a measurable improvement in a workflow or product in Tesla within the first 90 days. ## Related Videos - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Our journey with Spring Boot in a microservice architecture](https://www.wearedevelopers.com/videos/511-our-journey-with-spring-boot-in-a-microservice-architecture) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [How AI Models Get Smarter](https://www.wearedevelopers.com/videos/1374-how-ai-models-get-smarter) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts)