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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer - **Company:** Perfection Servo Hydraulics, Inc. - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $150,000.0 - $180,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Cloud Computing, Code Review, Continuous Integration, Distributed Systems, Information Extraction, Python (Programming Language), Machine Learning, Systems Development Life Cycle, Workflow Management Systems, Large Language Models, Prompt Engineering, Kubernetes, Information Technology, Machine Learning Operations, Terraform - **Published:** May 31, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=21a0bf48b6619f48 ## About the Role Do you have experience in System development?, Do you have a Master's degree?, * Authorized to work in the United States and not require work authorization sponsorship by our company for this position now or in the future. * Bachelor's or Master's degree in Computer Science, Data Science, or related technical field. * 3-5 years of experience designing, building, and deploying scalable production applications. * Strong proficiency in Python. * Hands on experience of distributed computing and cloud platforms (g., AWS, Kubernetes, Terraform, CI/CD frameworks). * Excellent communication and collaboration skills. * Nice to haves: + Experience with prompt engineering, RAG systems, and LLM evaluation. + Experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, AutoGen). + Experience with workflow orchestration tools (e.g., Airflow, Prefect, Temporal) for managing complex ML/GenAI pipelines. + Familiarity with vector databases and retrieval-augmented generation (RAG) patterns. + Experience evaluating and mitigating LLM risks (hallucinations, bias, safety) Tech Stack * Python * AWS (SageMaker, Bedrock, ECS, Lambda, S3, etc.) * Terraform, CI/CD frameworks ## Description We are looking for a Senior Software Engineer to drive the design and development of scalable AI systems that deliver meaningful impact across the organization. In this role, you will serve as a technical expert, guiding the team in productionizing and maintaining our GenAI workflows for information extraction and document generation., * Design and implementation of reliable, maintainable, and scalable GenAI systems in production. * Serve as a subject matter expert for machine learning systems owned by the team. * Mentor junior and mid level engineers through code reviews, technical guidance, and design collaboration. * Design, evaluate, and implement GenAI systems and workflows for information extraction and document generation. * Ability to take a proof of concept and turn it into production capable system. * Collaborate with product managers, data scientists, and engineers to translate business needs into high quality, production ready ML solutions. * Present findings, insights, and system results to technical and non technical stakeholders. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Infrastructure as Code: The Developer's Secret Weapon](https://www.wearedevelopers.com/videos/1221-infrastructure-as-code-the-developer-s-secret-weapon) - [WeAreDevelopers LIVE - CSS is DOOMed](https://www.wearedevelopers.com/videos/1838-wearedevelopers-live-css-is-doomed) - [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow) - [Implementing Feature Environments with AWS and Terraform](https://www.wearedevelopers.com/videos/531-implementing-feature-environments-with-aws-and-terraform) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [The Prompt Engineer ✍️](https://www.wearedevelopers.com/magazine/216-the-prompt-engineer) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)