Define AI-assisted underwriting workflows, lead the frontend design system evolution, mentor engineers, and rapidly iterate features to enhance user trust and efficiency in high-stakes financial environments.

• Design and implement advanced AI/GenAI features across applications and SDLC workflows • Build and deploy AI solutions using Azure AI Foundry and LLM platforms • Develop multi-agent workflows using frameworks like LangChain, LangGraph, Semantic Kernel, or LlamaIndex • Implement RAG architectures, prompt engineering, and vector-based retrieval systems • Drive AI-assisted development using GitHub Copilot and establish best practices • Build scalable full-stack applications using Python, TypeScript/JavaScript, and/or C# • Develop APIs, backend services, and work with relational and NoSQL databases • Implement observability, monitoring, and performance optimization for AI systems • Lead troubleshooting, design decisions, and system integrations • Mentor junior engineers and contribute to AI governance and best practices

Role Description As an organization, we are in an exponential growth phase with a consistent focus on continuous improvement, process-oriented culture, and a true partnership mindset with our customers. We are looking for the right qualified and committed individuals to play an exceptional role as well as to support our accelerated growth. - Design and implement AI/GenAI features across applications and SDLC workflows - Build AI solutions using platforms like Azure AI Foundry and LLM APIs - Develop agent-based workflows using frameworks such as LangChain, LangGraph, or Semantic Kernel - Implement RAG-based solutions and prompt engineering strategies - Leverage GitHub Copilot for AI-assisted development and productivity - Build full-stack applications using Python, JavaScript/TypeScript, and/or C# (.NET) - Develop APIs, backend services, and integrate with databases (SQL/NoSQL) - Ensure application quality through testing, monitoring, and observability - Collaborate with cross-functional teams (product, UX, data science) - Troubleshoot and optimize AI models, pipelines, and integrations Qualifications - 3+ years of full-stack software development experience - 1–2 years of experience in AI/LLM-based application development - Hands-on experience with AI platforms (Azure OpenAI, OpenAI, or similar) - Knowledge of RAG, embeddings, and vector databases - Experience with AI orchestration frameworks (LangChain, Semantic Kernel, etc.) - Strong programming skills in Python (preferred) and/or JavaScript/C# - Experience with REST APIs and database systems (SQL & NoSQL) - Familiarity with GitHub Copilot or AI-assisted development tools - Strong problem-solving and communication skills - Experience working in Agile environments Benefits - Flexible working hours to create a work-life balance - Opportunity to work on advanced tools and technologies - Global exposure to not only collaborate with the team, but also to connect with the client portfolio and build professional relationships - Highly encouraged for any innovative ideas & thoughts and we support in executing the same - Periodical and on-spot rewards and recognitions on your performance - Provides a better platform for enhancing skills via many different L&D programs - Enabling and empowering atmosphere to work along

Role Description This role will give you the opportunity to design and shape the technical foundation of our Analytics & AI practice, working on high-impact client engagements across industries. As our Analytics & AI Architect, you will sit at the intersection of data engineering, analytics, data science, and AI — defining the standards, frameworks, and architectures that our teams build upon. What will you do? - ARCHITECTURE & DESIGN - Design end-to-end data architectures: data lakes, lakehouses, warehouses, and streaming pipelines. - Define standards for data modeling, storage, ingestion, and transformation across client engagements. - Architect MLOps and AI deployment infrastructure (model registries, CI/CD for ML, monitoring). - Lead technical decisions on cloud platforms (Azure, AWS, GCP) and open-source tooling. - TEAM ENABLEMENT - Define best practices and reusable frameworks for data engineers, analysts, and data scientists. - Act as a technical mentor and reviewer for cross-functional project teams. - Bridge the gap between data analysts, data engineers, and AI/ML engineers on complex projects. - Contribute to internal knowledge base, toolkits, and delivery accelerators. - CLIENT ENGAGEMENT - Lead architecture workshops and discovery sessions with client stakeholders. - Translate business requirements into scalable, robust technical blueprints. - Present architecture decisions to both technical teams and executive audiences. - Support pre-sales and proposal efforts with technical scoping and solution design. - OTHER - Provide internal training and knowledge-sharing sessions with the team. - Support the Head of Practice on business development and internal capability initiatives. Qualifications - Master’s degree in Computer Science, Data Engineering, Software Engineering, Applied Mathematics, or a related field. - Full proficiency in English + 1 additional language (French, Arabic, Spanish, German...). - 6+ years of technical experience in data architecture or a closely related field. - Proven track record in a consulting or multi-client services environment. Requirements - DATA ARCHITECTURE & PLATFORMS - Proven hands-on experience designing large-scale data platforms: data lake, lakehouse, or warehouse architectures (Databricks, Snowflake, BigQuery, Azure Synapse, Redshift). - Strong command of SQL and at least one of Python, Scala, or Spark for data processing and transformation. - Experience with Big Data ecosystems: Hadoop, Spark, PySpark, Hive, or equivalent. - Familiarity with streaming and real-time architectures (Kafka, Flink, Spark Streaming). - AI & ML INFRASTRUCTURE - Proven hands-on experience with ML lifecycle tooling: MLflow, Kubeflow, SageMaker, Azure ML, or equivalent. - Experience architecting MLOps pipelines: model versioning, CI/CD for ML, monitoring and drift detection. - Exposure to GenAI and LLM integration patterns (RAG architectures, vector databases, prompt pipelines). - DATA ENGINEERING & DEPLOYMENT - Proven hands-on experience with orchestration and transformation tools: Airflow, dbt, or equivalent. - Proven hands-on experience with container technologies: Docker, Kubernetes. - Proven hands-on experience with versioning software: Git, GitHub, GitLab. - Proven hands-on experience deploying solutions in cloud ecosystems: AWS, Azure, or Google Cloud. - GOVERNANCE & STANDARDS - Knowledge of data governance frameworks: data catalogs, lineage tracking, access control, and data quality management. - Exposure to BI and data visualization platforms (Power BI, Tableau, Looker) and semantic layer design. - INTERPERSONAL SKILLS - Ability to step back, analyze complex problems, define architectural options, and drive decisions. - Strong ability to work and collaborate with a variety of stakeholders across technical and business functions. - Excellent communication skills with the ability to translate complex technical architectures into clear business implications. - High autonomy, attention to detail, and ability to manage multiple client engagements simultaneously. Benefits - A competitive salary. - A great working environment. - A steep learning curve with interesting and diverse topics to work on. - A healthy work-life balance. - Health insurance benefits. Company Description Infomineo is an equal opportunity employer, we prohibit any sort of discrimination (based on color, race, sex, sexual orientation, religion, national origin or any other attributes) in all aspects of employment (recruiting, hiring, wages and salary, promotions, benefits, training and job termination). If you believe you match our requirements and values, we would be happy to hear from you. Visit our website to know more about us, our services and company culture.