> Markdown version of [/jobs/ext/447062-ai-engineer](https://www.wearedevelopers.com/jobs/ext/447062-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - **Company:** Ishir, Inc. - **Location:** Dallas, TX, United States (Remote available) - **Experience:** Expert - **Salary:** $80,000.0 - $100,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Audit Trail, Software as a Service, Code Generation, Continuous Integration, Cursor (Graphical User Interface Elements), Software Debugging, DevOps, Programming Tools, Python (Programming Language), Open Web Application Security, Cloud Services, Data Processing, GitHub Copilot, Large Language Models, Gitlab, Usage Tracking, Gitlab-ci, Kubernetes, Enterprise Integration, Api Gateway, Terraform, GPT - **Published:** June 3, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=eee68436e6a6959e ## About the Role Do you have experience in Tooling?, * 8+ years in platform engineering, DevOps, developer experience, or a closely related technical discipline. * Demonstrated hands-on experience with LLM APIs and AI developer tooling in production or organizational contexts * Experience evaluating, procuring, or governing AI/SaaS tools at an organizational level, including vendor assessment, license management, and cost governance. * Strong Python skills for automation, tooling, and lightweight AI workflow and integration development. * Practical, daily use of AI-assisted development tools (GitHub Copilot, Cursor, Claude Code, ChatGPT, or similar) in your own engineering workflows. * Experience designing developer workflows, internal platforms, or engineering self-service capabilities with a focus on adoption and usability. * Solid AWS experience with familiarity with Bedrock, API Gateway, or equivalent managed AI and cloud services. * Strong observability mindset with the ability to instrument AI tooling and workflows with meaningful metrics and usage signals. * Infrastructure-as-code familiarity (Terraform, Helm) and experience working within GitOps and CI/CD environments, with GitLab CI preferred. * Excellent communication and stakeholder management skills, with the ability to translate technical findings into clear recommendations for engineering leadership and business audiences. Ways to Stand Out from the Crowd * Experience building or contributing to an internal AI enablement function, center of excellence, or developer experience program. * Hands-on experience with LLM Agents, RAG pipelines, vector databases (pgvector, OpenSearch, Pinecone, or similar), and prompt orchestration frameworks such as LangChain or LlamaIndex. * Familiarity with AI FinOps tooling, cost attribution models, and LLM API usage reporting at an organizational scale. * Experience with AI governance frameworks including acceptable use policies, audit logging, PII redaction pipelines, and responsible AI practices in regulated enterprise environments. * Background in financial services or insurance with an understanding of compliance constraints on AI tool usage and data handling. * Experience with AI-specific security threat models including OWASP Top 10 for LLMs, prompt injection risks, and model supply chain security. * Familiarity with developer productivity metrics frameworks such as DORA or SPACE, and a track record of using data to demonstrate engineering impact. * Strong ownership demeanor with a structured, automation-first approach and demonstrated impact driving AI-first engineering practices across teams. ## Description * Drive an AI-first culture through internal playbooks and "golden-path" templates while measuring impact via DORA and SPACE metrics. * Manage AI costs through token budgeting and usage tracking alongside guardrails like PII redaction and audit logging. * Build and document reusable patterns for code generation, PRs, testing, and debugging to optimize the end-to-end developer lifecycle. * Conduct POCs and provide recommendations for AI tools based on ROI, technical merit, and stakeholder feedback. * Manage lightweight AWS infrastructure including API Gateways and LLM pipelines while integrating tools with CI/CD and GitLab. ## Related Videos - [WeAreDevelopers LIVE - Modern DevOps for IoT Devices and More](https://www.wearedevelopers.com/videos/1805-wearedevelopers-live-modern-devops-for-iot-devices-and-more) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Engineering Mindset in the Age of AI - Gunnar Grosch, AWS](https://www.wearedevelopers.com/videos/1735-engineering-mindset-in-the-age-of-ai-gunnar-grosch-aws) - [AI Killed DevOps... What Now? - Lee Faus](https://www.wearedevelopers.com/videos/1759-ai-killed-devops-what-now-lee-faus) - [Streaming AI Responses in Real-Time with SSE in Next.js & NestJS](https://www.wearedevelopers.com/videos/1630-streaming-ai-responses-in-real-time-with-sse-in-next-js-nestjs) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Got AI ideas but no money? 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