AI Engineer

Vedi l’offerta su Go Lavoro: golavoro.it/annuncio-lavoro/7cibz0

ph3Who We Are /h3 pBased in The Romania Excellence Centre, Bucharest - our client is seeking for experienced professionals who value teamwork, pioneering technology, and innovation. People who want to take their careers to the next level of success. You will be part of a global and diverse team, contribute to all stages of software development lifecycle and lead the implementation, deployment and test of multi-agent systems. /p h3Also, This Role Will Give You The Chance To /h3 ul liUse frameworks like Google Agent Development Kit (Google ADK) and LangGraph to build robust, controllable, and observable agentic architectures /li liAssist in the design of LLM-powered agents and multi-agent workflows (planning, tool use, orchestration, memory, and human-in-the-loop) /li /ul pSo if you are an experienced AI Engineer please join our team to create the next big thing in digital banking. /p h3What You’ll Be Doing /h3 ul liDesign and build complex agentic systems with multiple interacting agents /li liImplement robust orchestration logic (state machines / graphs, retries, fallbacks, escalation to humans) /li liImplement RAG pipelines, tool calling, and sophisticated system prompts for optimal reliability, latency, and cost control /li liApply core ML concepts to evaluate and improve agent performance, including dataset curation and bias/safety checks /li liLead the development of agents using Google ADK and/or LangGraph, leveraging advanced features for orchestration, memory, evaluation, and observability /li liIntegrate with supporting libraries and infrastructure (e.g., LangChain/LlamaIndex, vector databases, message queues, monitoring tools) with minimal supervision /li liDefine success metrics, build evaluation suites for agents (automatic + human evaluation),



and drive continuous improvement /li liCurate and maintain comprehensive prompt/test datasets; run regression tests for new model versions and prompt changes /li liDeploy and operate AI services in production, establishing CI/CD pipelines, observability, logging, and tracing /li liDebug complex failures end-to-end, identifying and document root causes across models, prompts, APIs, tools, and data /li liWork closely with product managers and stakeholders to shape requirements, translate them into agent capabilities, and manage expectations /li liDocument comprehensive designs, decisions, and runbooks for complex systems /li /ul h3What We’re Looking For /h3 ul liBachelor’s degree in Computer Science, Engineering, or related field /li liAt least 3 years of experience as Software Engineer / ML Engineer / AI Engineer, with at least 1-2 years working directly with LLMs in real applications /li liStrong proficiency in Python (core language features, packaging, testing, async, type hints) /li liVery strong software engineering practices: version control (Git), unit/integration testing, code reviews, CI/CD /li liExperience building and consuming REST/gRPC APIs and integrating external tools/services /li liUnderstanding of core ML concepts: supervised/unsupervised learning, train/validation/test splits, overfitting, regularization, and common metrics (precision, recall, F1, ROC-AUC, etc.) /li liGood understanding of deep learning basics (neural networks, embeddings) and at least one ML/DL framework (e.g., PyTorch, TensorFlow, JAX, scikit-learn) /li liDeep practical knowledge of large language models /li liTokenization,



context windows, temperature, top‑p, system vs user prompts /li liPrompt engineering patterns (ReAct, chain‑of‑thought, tool‑calling/tool‑use) /li liFine‑tuning / adapters / instruction‑tuning, or experience with RAG as an alternative /li liExperience building LLM‑powered applications end‑to‑end: from idea → prototype → production /li liFamiliarity with safety and reliability considerations: hallucinations, guardrails, content filtering, privacy /li liConceptual understanding of modern agentic frameworks and patterns (stateful graphs, multi‑agent coordination, human‑in‑the‑loop, memory, and evaluation). /li liHands‑on experience with at least one of: Google Agent Development Kit (ADK) – building multi‑agent workflows, using its orchestration, tools, and evaluation features or LangGraph – designing graph‑based, stateful agent workflows with cycles, branches, and durable execution /li liCandidates must be able to read, reason about, and extend ADK/LangGraph‑based codebases /li liDirect production experience with both ADK and LangGraph is a strong plus /li liExperience working with vector databases (e.g., Pinecone, Weaviate, pgvector, Chroma) for retrieval‑augmented generation /li liComfortable with SQL and basic data modeling /li liExperience deploying on at least one major cloud platform (GCP, AWS, Azure) and using managed services (e.g., serverless runtimes, container orchestration, secrets management) /li /ul h3Nice‑to‑Have Experience With /h3 ul liVertex AI / Gemini or other hosted LLM ecosystems /li liRelated frameworks and tools: LangChain, LlamaIndex, semantic search, evaluation frameworks (e.g., RAGAS, custom eval harnesses) /li liMonitoring and observability stacks (OpenTelemetry, Prometheus/Grafana/NewRelic, Datadog, etc.) /li /ul /p #J-18808-Ljbffr

Vedi l’offerta su Go Lavoro: golavoro.it/annuncio-lavoro/7cibz0