Jobs at Sia Partners

Leads social media strategy for client engagements, refining content approaches, developing creative briefs, guiding creator strategy, reviewing social creative, managing client approvals, and overseeing community management playbook development.

Build and maintain cloud-based data engineering and machine learning infrastructure for client projects and internal AI solutions. Responsibilities include cloud architecture, storage and compute optimization, Docker and Kubernetes orchestration, Python development, CI/CD, ETL pipelines, Infrastructure as Code, security implementation, and deployment support for data science projects.

Lead client data engineering engagements from strategy through execution. Design scalable cloud data architectures, pipelines, databases, integration patterns, and DataOps practices using platforms such as GCP, AWS, Azure, Databricks, and Snowflake. Manage stakeholders, advise senior clients, develop consulting offerings, support business development, represent the firm externally, and mentor junior consultants.

Leads machine learning engineering initiatives, develops production-grade AI and ML solutions, designs cloud architectures, and helps scale data science models into production. The role includes technical leadership, mentoring, client project participation, internal AI product development, training, event participation, and thought leadership. Candidates need strong Python and software engineering skills, cloud and DevOps experience, big data expertise, and willingness to travel internationally.

Lead data science and digital transformation consulting projects involving machine learning, AI, statistics, operational research, optimization, simulation, and big data. Support client modeling and analysis, contribute to internal offering development and business development, and progress toward team leadership. The role requires strong analytical, communication, and consulting skills, advanced technical education, French, Dutch, and English fluency, and willingness to accept temporary international assignments.

Lead client data engineering engagements from strategy through execution. Design scalable data architectures, pipelines, cloud and distributed systems, databases, data models, and batch or real-time integrations. Implement CI/CD and DataOps practices while managing stakeholders and mentoring consultants. Contribute to internal training, thought leadership, proposals, business development, and long-term client relationships as a technical subject matter expert.

Execute client transformation projects involving machine learning, AI, statistics, predictive modeling, optimization, simulation, and big-data processing. Perform business and IT analysis with partial coding, contribute to digital transformation initiatives, and support internal innovation, offer development, and business development. The role requires strong analytical, communication, teamwork, and multilingual skills, with potential temporary international assignments.

Consults on data science and digital transformation projects, developing predictive models, optimization solutions, simulation models, and algorithms for large or unstructured datasets. Contributes to internal data science offerings, innovation analysis, business development, and client initiatives. Requires strong analytical, communication, teamwork, and multilingual skills, with potential temporary international assignments.

Build and maintain cloud-based data engineering and machine learning infrastructure for client projects and internal AI solutions. Responsibilities include designing cloud architectures, managing Docker and Kubernetes environments, developing Python tools and ETL pipelines, automating CI/CD, implementing Infrastructure as Code, optimizing cloud costs, and securing applications. The role also supports data science deployments and requires strong collaboration, communication, and English, Dutch, and French language skills.

Lead machine learning engineering initiatives across internal AI products and client projects. Build production-grade ML and AI solutions, make cloud architecture decisions, scale data science models into production, and guide engineers through optimization, testing, and deployment. The role also includes mentoring, training, client workshops, conference presentations, thought leadership, and collaboration with international data science and engineering teams.

Lead data science and digital transformation consulting projects involving machine learning, AI, statistics, econometrics, forecasting, optimization, simulation, and big data processing. Contribute to client transformation initiatives, internal service development, and business development. Build expertise in data and AI topics, collaborate across teams, and assume leadership responsibilities. The role requires strong analytical, communication, consulting, and multilingual skills, with potential temporary international assignments.

Leads software and cloud engineering teams building scalable AI and generative AI SaaS products. Owns technical roadmaps, cloud architecture, distributed systems, microservices, CI/CD, infrastructure, reliability, and cost optimization. Partners with product, research, data science, and operations teams to deliver production-grade AI capabilities. Provides architectural leadership, contributes targeted code, develops engineering talent, and communicates technical trade-offs to clients and stakeholders.

Architect and standardize multi-cloud DevOps and platform foundations for AI products. Own CI/CD, Kubernetes, infrastructure automation, observability, reliability engineering, security, and cloud cost governance across teams. Serve as the escalation point for complex infrastructure incidents, guide architecture and deployment practices, improve developer experience, and mentor senior engineers without direct people management.

Develop and optimize Python backend services, microservices, and data-centric applications for AI-powered SaaS products. Integrate and optimize AI/ML models, manage PostgreSQL and MongoDB databases, and deploy applications using Docker, Kubernetes, Terraform, and Helm. Work across GCP, AWS, and Azure with CI/CD pipelines, testing, and artifact management. Collaborate with DevOps, data scientists, and data engineers while contributing to frontend and overall software architecture and mentoring engineering teams.

Build and own scalable AI and Generative AI platforms using Python, microservices, cloud infrastructure, and machine learning models. Design backend architecture, deploy and optimize ML systems, manage Kubernetes and Terraform-based infrastructure, maintain databases and observability platforms, and lead production reliability practices. The role also involves technical leadership, mentoring, architecture decisions, incident response, and translating client requirements into robust technical solutions.

Manage client marketing programs from planning through execution, launch, and measurement. Translate objectives into deliverables, timelines, owners, and dependencies; coordinate cross-functional teams; identify risks; facilitate client meetings; create executive-ready materials; and use data to improve performance. The role also identifies practical applications for AI and automation across marketing workflows, supports process improvement, and builds trusted client relationships in a consulting environment.

Manage client marketing programs from planning through launch and measurement. Translate objectives into deliverables, timelines, owners, and dependencies; coordinate cross-functional teams; facilitate client sessions; create executive-ready materials; identify risks and improve workflows. Use data and stakeholder feedback to guide recommendations, while identifying practical applications for AI and automation across marketing strategy, content, insights, and execution.

Designs end-to-end cloud, data, machine learning, deep learning, generative AI, and agent-based architectures for client engagements. Leads architecture reviews, technical governance, production readiness, security, compliance, scalability, reliability, and cost optimization. Partners with senior stakeholders, supports pre-sales scoping and proposals, mentors consultants and engineers, and develops AI reference architectures and internal accelerators.

Manages web marketing execution for client launches, translating marketing and product needs into briefs, requirements, landing pages, and digital workstreams. Coordinates design, content, development, and client stakeholders while prioritizing timelines and dependencies. Conducts customer journey, competitive, SEO, and site performance analysis, using analytics and dashboards to inform recommendations and optimization. Ensures web experiences support acquisition, engagement, conversion, and broader campaign goals.

Supports and manages innovation consulting projects across strategy, technology scouting, solution validation, research, requirements documentation, stakeholder collaboration, and project delivery. The role contributes to innovation strategy, design thinking, capability building, and business project management for Middle Eastern clients. Candidates need 3–5 years of technology, research, or innovation experience, strong project delivery skills, Arabic and English proficiency, and physical residence in Abu Dhabi.