AI Engineer

Description

Job Summary: We are seeking an AI Specialist to design, implement, and orchestrate AI agents, ensuring their reliability and compliance with banking industry standards. Key Highlights: 1. Design and implement AI agents for complex tasks 2. Lead technical architecture decisions for new AI use cases 3. Mentor other engineers on AI design and best practices Join Stefanini! At Stefanini, we are over 30,000 geniuses connected across 41 countries, co\-creating a better future. Become our **AI Specialist!** ### ******Role Purpose** Design and implement AI agents, skills, and orchestration workflows on client platforms. Define AI technical guidelines, evaluate models and frameworks, integrate telemetry, and ensure scalability, reusability, and risk control of AI assets. **Responsibilities and Authorities** ### **Core Functions** * Design and implement **AI agents** capable of executing complex tasks through reasoning, planning, and tool use. * Develop reusable **skills** (encapsulated capabilities) consumable by various agents and bank teams. * Build and maintain **orchestration workflows** that coordinate multiple agents, models, and systems. * Define **AI technical guidelines and standards** (design patterns, best practices, architecture guidelines) for enterprise-wide adoption across the bank. * Evaluate and compare **AI models and frameworks** (LLMs, agent frameworks, orchestration tools) based on performance, cost, security, and regulatory compliance criteria. * Integrate **telemetry and observability** into AI assets (logging, decision traceability, usage and quality metrics). * Design solutions with **scalability and reusability** in mind, avoiding duplication of effort across teams. * Collaborate with **risk, compliance, and security** teams to ensure AI assets comply with internal policies and banking regulatory requirements. ### **Responsibilities** * Ensure deployed AI agents and workflows are **reliable, auditable, and traceable**, given the bank’s regulated context. * Establish and enforce **risk controls** associated with AI usage (bias, hallucinations, data leakage, misuse). * Lead technical architecture decisions for new AI use cases in collaboration with Product, Risk, and Business teams. * Maintain up-to-date documentation of technical guidelines, skill catalogs, and orchestration architectures. * Conduct technical reviews (design/code reviews) of agent implementations developed by the team. * Monitor AI asset performance in production via telemetry, proposing continuous improvements. * Evaluate vendors, models (in-house or third-party), and emerging frameworks, delivering well-founded recommendations. * Mentor other team engineers on agent design, skills development, and AI best practices. **Requirements and Qualifications** ### **Technical Requirements** **Academic Background** * Bachelor’s degree in Computer Engineering, Computer Science, Mathematics, Statistics, or related fields. * Preferred: postgraduate degree (Master’s or specialization) in AI, Machine Learning, or Data Science. **Experience** * 4–6\+ years of software development experience, with at least 3 years focused on Machine Learning / AI. * Demonstrable experience deploying models into production (not just notebooks/experimentation). **Technical Knowledge** * Programming languages: Python (advanced); Java, Go, or Scala knowledge is desirable. * ML/DL frameworks: PyTorch, TensorFlow, scikit\-learn. * Generative AI and LLMs: fine\-tuning, prompt engineering, RAG (Retrieval\-Augmented Generation), embeddings, frameworks such as LangChain / LlamaIndex. * MLOps: Docker, Kubernetes, MLflow, Airflow, CI/CD for models. * Cloud: AWS, GCP, or Azure (AI/ML services: SageMaker, Vertex AI, Azure ML). * Databases: SQL and NoSQL; vector database knowledge (Pinecone, Weaviate, FAISS, etc.). * Strong foundation in applied mathematics: linear algebra, statistics, probability, and optimization. * Software engineering best practices: version control (Git), testing, distributed systems architecture. * Preferred: advanced technical English (reading research papers, documentation). ### **Soft Skills** * **Analytical thinking and problem solving**: ability to decompose complex problems and propose data-driven solutions. * **Effective communication**: ability to explain complex technical concepts to non-technical audiences. * **Teamwork and collaboration**: ability to work with multidisciplinary teams. * **Technical leadership and mentorship**: willingness to guide and develop other team members. * **Curiosity and continuous learning**: genuine interest in staying current with field advancements. * **Critical and ethical thinking**: ability to identify risks, biases, and limitations of AI models. * **Autonomy and proactivity**: ability to manage one’s own work with minimal supervision. * **Adaptability**: ability to adjust to a constantly evolving technology landscape. * **Results orientation**: focus on generating measurable business impact through technical solutions. **Additional Information** Stefanini Benefits Looking for a place where your ideas shine? With over 38 years of experience and a global presence, Stefanini transforms tomorrow— together. Here, every action matters and every idea can make a difference. Join a team that values innovation, respect, and commitment. If you’re a disruptive thinker, committed to continuous learning, and innovation is in your DNA, then we’re what you’re looking for. Come and let’s build a better future—together!