Senior AI Engineer

About the opportunity

About Us Coderio designs and delivers scalable digital solutions for global companies. We combine strong technical expertise with a product mindset to lead complex software initiatives end-to-end. We work with international clients, value autonomy and clear communication, and build long-term partnerships through technical excellence. More information: http://coderio.com This is a high-impact technical role. We are looking for a Senior AI Engineer to join our AI Engineering Core initiatives. You will operate at the intersection of backend engineering, cloud platforms, and applied AI, building shared AI foundations that help software developers and product teams adopt Generative AI safely, observably, and efficiently. Your primary mission is to design, build, and operate reusable AI capabilities, LLM gateways, model routing, evaluation frameworks, and guardrails across the organization. This is a hands-on execution and engineering-driven role. You are responsible for designing, benchmarking, and deploying production-grade AI capabilities and agentic workflows directly into internal platforms and software ecosystems. What To Expect In This Role (Responsibilities) Shared AI Foundations: Design, implement, and operate production-grade, reusable AI capabilities and services adopted by multiple engineering and product teams. LLM Infrastructure & Gateways: Build and evolve LLM gateways, proxies, model routing mechanisms, prompt/context strategies, and agentic workflows (e.g., LangGraph, PydanticAI, MCP). Evaluations & Observability: Design evaluation frameworks (golden sets, LLM-as-a-judge), guardrails, and observability pipelines to measure task success, latency, security, and token costs. Engineering Standards & Best Practices: Define standards for production AI adoption across the organization, including automated testing, versioning, context segregation, and incident response. End-to-End Delivery: Own delivery end-to-end—from problem framing and architectural design through implementation, deployment, monitoring, and continuous iteration. Automation & DevEx: Identify high-impact opportunities to eliminate repetitive manual work by implementing internal tools, scripts, and intelligent workflows that boost developer velocity. Requirements Software & AI Engineering Foundation: Senior-level experience (typically 5+ years) delivering and operating production-grade systems in Software Engineering, AI Engineering, or ML Engineering. Development Skills: Advanced hands-on proficiency in Python, RESTful/async APIs, microservices, and cloud services (AWS or GCP). GenAI & Agentic Systems: Proven experience building reliable applications using LLMs, RAG pipelines, agent orchestration (e.g., LangGraph, CrewAI), and Model Context Protocol (MCP). LLM Infrastructure & Evals: Hands-on experience with LLM proxies/gateways, model routing, evaluation harnesses, and AI observability tools (e.g., LangSmith, Datadog, Logfire). Architecture & Trade-offs: Ability to make sound architectural decisions balancing quality, latency, reliability, security, privacy, scalability, and cost. Language & Communication: Advanced English proficiency (mandatory) with clear communication skills to collaborate effectively with cross-functional technical stakeholders. Nice to Have Experience with container orchestration (Docker, Kubernetes) and Infrastructure-as-Code (Terraform) in cloud environments. Experience building, scaling, or contributing to Internal Developer Platforms (IDP) or developer tooling. Background in prompt engineering optimization, fine-tuning open-source models, or custom vector database indexing. Benefits High-impact, strategic role driving shared AI foundations and internal developer adoption. Collaborative international environment with senior technical leadership. High autonomy to research, prototype, and implement cutting-edge GenAI workflows. Long-term 100% remote engagement with competitive compensation and growth opportunities. Why Join Coderio? At Coderio, we value talent and technical excellence. We are passionate about modern engineering, high autonomy, and building solutions that make a real difference. We offer an inclusive and challenging environment where innovation is encouraged and technical leadership is valued. If you are eager to research and deploy next-generation AI solutions that elevate engineering teams, apply now. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Responsibilities

• ) Shared AI Foundations: Design, implement, and operate production-grade, reusable AI capabilities and services adopted by multiple engineering and product teams.
• LLM Infrastructure & Gateways: Build and evolve LLM gateways, proxies, model routing mechanisms, prompt/context strategies, and agentic workflows (e.
• , LangGraph, PydanticAI, MCP).
• Evaluations & Observability: Design evaluation frameworks (golden sets, LLM-as-a-judge), guardrails, and observability pipelines to measure task success, latency, security, and token costs.
• Engineering Standards & Best Practices: Define standards for production AI adoption across the organization, including automated testing, versioning, context segregation, and incident response.
• End-to-End Delivery: Own delivery end-to-end—from problem framing and architectural design through implementation, deployment, monitoring, and continuous iteration.
• Automation & DevEx: Identify high-impact opportunities to eliminate repetitive manual work by implementing internal tools, scripts, and intelligent workflows that boost developer velocity.

Qualifications

• Software & AI Engineering Foundation: Senior-level experience (typically 5+ years) delivering and operating production-grade systems in Software Engineering, AI Engineering, or ML Engineering.
• Development Skills: Advanced hands-on proficiency in Python, RESTful/async APIs, microservices, and cloud services (AWS or GCP).
• GenAI & Agentic Systems: Proven experience building reliable applications using LLMs, RAG pipelines, agent orchestration (e.
• , LangGraph, CrewAI), and Model Context Protocol (MCP).
• LLM Infrastructure & Evals: Hands-on experience with LLM proxies/gateways, model routing, evaluation harnesses, and AI observability tools (e.
• , LangSmith, Datadog, Logfire).
• Architecture & Trade-offs: Ability to make sound architectural decisions balancing quality, latency, reliability, security, privacy, scalability, and cost.
• Language & Communication: Advanced English proficiency (mandatory) with clear communication skills to collaborate effectively with cross-functional technical stakeholders.