Senior AI Engineer (GenAI & Agentic Systems)

NEORIS is a Digital accelerator that helps companies enter the future, having 20 years of experience as Digital Partners of some of the largest companies in the world. We have more than 4,000 professionals in 11 countries, with our multicultural startup culture where we cultivate innovation, continuous learning to create high-value solutions for our clients.

We are seeking a highly experienced and hands-on Senior AI Engineer (GenAI & Agentic Systems) to lead the design, development, and scaling of next-generation Agentic AI systems and GenAI applications. In this role, you will own the technical direction of complex AI solutions, bridging cutting-edge LLM capabilities with robust, production-grade software.
You will architect multi-agent systems, define best practices for RAG pipelines, and lead the development of scalable backend and cloud-native infrastructure on Google Cloud Platform (GCP). This role requires both deep technical expertise and the ability to guide teams in building reliable, secure, and high-performing AI systems.

Key Responsibilities

Agentic AI & GenAI Architecture

• Lead the design and implementation of advanced agentic architectures, including multi-agent orchestration, tool usage, planning, memory management, and self-reflection patterns using platforms such as Google ADK.

• Define and standardize RAG architectures, including retrieval strategies, context engineering, hybrid search, re-ranking, and optimization of latency, accuracy, and cost.

• Establish prompt engineering standards and governance, ensuring consistency, reliability, and scalability across use cases.

• Design and implement evaluation frameworks to measure model performance (hallucination rates, precision/recall, response quality).

• Define observability strategies for multi-agent systems, including tracing, debugging, and performance monitoring.

Backend & Systems Engineering Leadership

• Architect and oversee development of scalable, asynchronous backend systems and APIs using FastAPI or similar frameworks.

• Define best practices for system integration, enabling AI agents to interact securely with enterprise systems, APIs, and external tools.

• Ensure high standards in software design, modularity, performance, and reliability across services.

Cloud Architecture & MLOps

• Lead the design and deployment of cloud-native AI solutions on GCP, ensuring scalability, resilience, and cost optimization.

• Define containerization and orchestration strategies using Docker and Kubernetes (GKE).

• Establish and improve CI/CD pipelines, testing frameworks, and release processes for AI systems.

• Oversee database architecture, including vector search (pgvector) and relational data management.

Technical Leadership & Collaboration

• Provide technical leadership and mentorship to engineers, promoting best practices in AI/ML and software engineering.

• Collaborate with product, data, and engineering teams to translate business needs into scalable AI solutions.

• Drive architecture decisions, code reviews, and technical standards across projects.

• Ensure alignment with security, privacy, and governance standards, especially for GenAI applications.

Required Qualifications

• 5+ years of software engineering experience, with 2–3+ years building and deploying production-grade AI/LLM systems.

• Expert-level proficiency in Python, including asynchronous programming (AsyncIO).

• Strong experience designing and implementing RAG pipelines, vector search, and GenAI systems.

• Proven experience architecting multi-agent systems or complex AI workflows.

• Deep experience with FastAPI (or similar frameworks) for building scalable backend services.

• Strong knowledge of PostgreSQL and vector databases (pgvector or equivalent).

• Hands-on experience with GCP, including deploying and managing applications in cloud-native environments.

• Strong experience with Docker, Kubernetes (GKE), and CI/CD pipelines.

• Solid understanding of distributed systems, API design, and software architecture principles.

• Experience implementing evaluation, monitoring, and observability for AI systems.

• Strong communication skills and ability to work in cross-functional teams.

• English proficiency – B2+/C1 preferred.

Preferred Qualifications (Nice-to-Haves)

• Hands-on experience with Google ADK (Agent Development Kit) or similar agent orchestration frameworks.

• Experience with real-time systems, including streaming responses (WebSockets, SSE).

• Familiarity with additional GenAI frameworks (e.g., LangChain, LlamaIndex) for broader architectural perspectives.

• Experience implementing security, guardrails, and PII protection in AI systems.

• Background in scaling AI systems in enterprise environments.

• Experience leading or contributing to architecture design reviews and technical roadmaps.

We offer:

• Professional growth

• Dynamic work environment

• Competitive salary

• Attractive benefits plan

• Benefits of law and superiors

• Development opportunities

Come and meet us on: http://www.neoris.com, on Facebook, LinkedIn, Twitter, or Instagram @NEORIS.

Marina Molina

#LI-MM3