Senior GenAI Software Engineer

Description

**Job Description** ------------------- Choosing Capgemini means choosing a company where you’ll have the freedom to shape your professional career as you wish, backed and inspired by a collaborative global community of colleagues. Here, you can reinvent what’s possible. Join us and help the world’s leading organizations discover the value of technology and build a more sustainable and inclusive world. We have a Data & AI team eager to welcome you. Would you like to join us? **Brief Description** --------------------- **What will you do on the project? What will be your role?** * Drive the design and development of AI applications and services integrating Large Language Models (LLMs) and generative AI capabilities in cloud environments (Azure/AWS/GCP), applying modern engineering practices (CI/CD, testing, observability, security) to deliver robust production-ready solutions (RAG, agents, process automation) aligned with reliable GenAI delivery frameworks. * Design and develop backend services (REST/GraphQL) and microservices that integrate LLMs (Azure OpenAI, OpenAI, Vertex AI, Amazon Bedrock) and tools/functions to execute actions against internal/external APIs. * Build RAG pipelines (ingestion, chunking, embeddings, vector storage, retrieval) and agents using orchestrators (LangChain, LlamaIndex, Semantic Kernel, or others) and tool/function calling mechanisms. * Implement CI/CD (GitHub Actions, GitLab CI, Azure DevOps, Jenkins), containerization (Docker, Kubernetes), and observability (logging, metrics, tracing). * Ensure quality: TDD/BDD, unit/contract/integration testing; define quality gates (linting, SAST/DAST, dependency scanning). * Apply LLMOps/MLOps: prompt and artifact versioning, quality evaluation (accuracy, groundedness, toxicity), monitoring (latency, cost, drift), and guardrails (policies, content, PII). * Collaborate with architecture, data, security, and business teams to operationalize non-functional requirements (scalability, resilience, cost) and AI governance/ethics (data access, compliance). * Document decisions (ADRs), create reusable playbooks, and support code reviews and mentoring for junior profiles. * Contribute to internal accelerators and reusable components aligned with Data & AI capability frameworks. **Detailed Description** --------------------- **To thrive in this position, you need expertise in:** * Strong software engineering foundation (3–7+ years, depending on seniority): API design, integration patterns, concurrency/asynchronous processing, sound coding practices (Clean Code, SOLID). * Experience with Python and backend frameworks (FastAPI, Flask, Express, etc.). * Advanced Git (branching model, pull requests, code review) and CI/CD using at least one of: GitHub Actions / GitLab CI / Azure DevOps / Jenkins. * Cloud platform experience (at least one of: Azure, AWS, or GCP), including containerized workload deployment (Docker; Kubernetes preferred). * Integration with GenAI/LLM services (Azure OpenAI, OpenAI, Vertex AI, Bedrock): API consumption, authentication, cost and quota management, prompting, and basic evaluation. * Practical knowledge of RAG (embeddings, vector stores such as FAISS, pgvector, Pinecone) and orchestrators (LangChain/LlamaIndex/Semantic Kernel). * Testing (unit/integration/contract), observability (e.g., OpenTelemetry), and basic API security (OAuth2/OIDC, secrets management, rate limiting). * Professional English (working with documentation and international teams). * LLMOps/MLOps: MLflow, Weights & Biases, Prompt Flow/Azure AI Studio evaluations, experiment tracking, and evaluation dashboards. * Product mindset and obsession with production quality. * Collaboration with multidisciplinary teams (architecture, data, security, business). * Continuous learning in a highly dynamic environment (new models, frameworks, evaluations). * Clear communication and documentation of decisions. Additionally, it would be great if you have experience in: * Infrastructure as Code (Terraform), advanced Kubernetes (ingress, autoscaling, service mesh), event-driven architectures (Pub/Sub, Kafka). * Observability and reliability: SLO/SLA, alerting, controlled failures, chaos testing. * Security and compliance in GenAI: writing guardrails, PII filtering, content controls. * Experience with Agentic AI (planning, tools, memory, agent teams). **Brief Description** --------------------- We value all applications and offer in-person, online, and certification-based training. Even if you don’t meet 100% of the requirements, we’d love to meet you! **What will you enjoy about working here?** * Diverse and challenging projects: You’ll work on multisectoral challenges, avoiding routine and gaining exposure to varied technologies. * Flexibility and hybrid work model: A culture focused on work-life balance. * Continuous learning: o Training in cloud technologies, data governance, visualization… o Real-world involvement in generative AI, Business AI, and emerging data technologies. * Diverse clients and constant innovation: High-impact projects with leading organizations. * Collaborative and inclusive environments: Dynamic, multicultural teams focused on growth. * Professional growth and technical “challenge”: Autonomy, mentoring, certifications, and opportunities to expand your role within the Data & AI domain. **Why Capgemini? Our Commitments and Priorities** Capgemini is a global partner for business and technological transformation, helping organizations accelerate their dual transition toward a digital and sustainable world—delivering tangible impact both for businesses and society. We are a responsible and diverse group of 340,000 professionals across 50+ countries. With a strong track record spanning over 55 years, our clients trust us to harness the value of technology and address all their business needs. We offer end-to-end services and solutions—from strategy and design to engineering—powered by our leadership in AI, generative AI, cloud, and data, combined with deep industry expertise and a robust ecosystem of partners. MAKE IT REAL. Join the team! www.capgemini.com/es-es