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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - **Company:** Tegna Inc. - **Location:** United States - **Experience:** Expert - **Contract:** Temporary contract - **Skills:** Microsoft Access, XML Schema, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Business Analytics Applications, Application Performance Management, Batch Processing, Cloud Computing, Cloud Engineering, Information Engineering, Data Systems, JSON, Python (Programming Language), Software Deployment, Systems Integration, Management of Software Versions, Enterprise Data Management, Data Logging, Large Language Models, Snowflake, Grafana, Prompt Engineering, Model Validation, Generative AI, Backend, AI Platforms, Kubernetes, Machine Learning Operations, Virtual Agents, Cloudwatch, Software Version Control, Data Pipelines, Serverless Computing, Microservices - **Published:** June 24, 2026 - **Apply:** https://www.dice.com/job-detail/0c9a1dba-c4b0-4a2a-b1aa-b6af32a61dfd ## About the Role The ideal candidate combines strong cloud engineering expertise with hands-on experience in prompt engineering, foundation models, agentic AI systems, and data pipelines within Snowflake and AWS ecosystems, * 5+ years of experience in AI/ML, Software or Data engineering. * Proficiency in Python with solid understanding of ML fundamentals * Strong hands-on experience with AWS, APIs and microservices architecture * Experience integrating AI solutions with data systems like Snowflake. * Practical experience with prompt engineering * Experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel, or similar * Experience with agentic frameworks (AutoGen, CrewAI, or equivalent). Preferred Qualifications * Experience building RAG pipelines in enterprise environments. * Knowledge of MLOps best practices. * Experience with vector databases and embeddings. * Familiarity with model evaluation frameworks (e.g., LLM eval metrics). * Experience implementing AI governance and responsible AI practices. * Background in sales, media, marketing analytics, or enterprise data platforms (a plus). #LI-MS1 ## Description AI & Generative AI Development * Design, develop, and deploy LLM-powered applications and agentic AI systems in production environments. * Implement advanced prompt engineering strategies including: * Prompt chaining and multi-turn orchestration * Few-shot learning and in-context learning * Chain-of-Thought (CoT) and Tree-of-Thought (ToT) prompting * Function calling and tool use optimization * Structured output generation (JSON, XML schemas) * Build and optimize Retrieval-Augmented Generation (RAG) systems integrating Snowflake data with LLMs. * Evaluate and fine-tune foundation models via AWS Bedrock or other managed AI services. * Develop guardrails for AI systems including hallucination mitigation, grounding, and safety controls. * Implement LLMOps best practices for model lifecycle management: * Model versioning, deployment, and rollback strategies * Prompt versioning and experimentation frameworks * Monitor and observe LLM application performance using observability tools. * Evaluation frameworks for LLM outputs Cloud & Platform Engineering (AWS) Architect scalable AI solutions using AWS services such as: * Bedrock - Sagemaker - Access and fine-tune foundation models * Lambda - Serverless LLM application deployment * EC2 - GPU-accelerated inference and batch processing * Step Functions - Orchestrate complex LLM workflows and agentic pipelines * CloudWatch - Monitoring, logging, and alerting for AI systems AI Application Development * Build APIs and backend services to operationalize AI solutions. * Integrate LLM/AI systems into internal applications, sales tools, or analytics platforms. * Implement streaming and real-time inference for low-latency AI applications. * Collaborate with stakeholders to translate use cases into production AI systems., Recruiters or Hiring Managers will never request payments, ask for financial account information or sensitive information such as social security numbers. ## Related Videos - [Tips and Tricks for Working with JSON](https://www.wearedevelopers.com/videos/1229-tips-and-tricks-for-working-with-json) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [5 steps for running a Kubernetes environment at scale](https://www.wearedevelopers.com/videos/88-5-steps-for-running-a-kubernetes-environment-at-scale) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [Introducing JSON Structure](https://www.wearedevelopers.com/videos/100219-introducing-json-structure) - [Developer Experience, Platform Engineering and AI powered Apps](https://www.wearedevelopers.com/videos/990-developer-experience-platform-engineering-and-ai-powered-apps) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? 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