Jobs at Sia Partners

The Senior Applied Data Scientist will lead the design and implementation of analytical solutions, translating business requirements into scalable data products while mentoring junior scientists and ensuring model deployment success.

Owner of customer adoption and satisfaction for Stratumn Trace. Build relationships, lead success reviews, coordinate solution engineers and integrations, manage implementations, drive post-production adoption, and relay customer needs to product and engineering.

Design and deliver scalable AI and Generative AI backend platforms integrating LLMs and ML models with cloud-native services. Build and ship Python-based microservices, manage containerization and orchestration, deploy and optimize models, maintain cloud infrastructure (Terraform/Helm), ensure database performance, and establish monitoring and observability while providing technical leadership on client engagements.

Lead and grow a cloud-native engineering team to design, build, and operate AI/Generative AI SaaS platforms. Translate product requirements into scalable architectures, drive cloud and CI/CD best practices, contribute hands-on code and IaC, and collaborate with product, data science, and operations to deliver reliable, production-grade AI systems while recruiting and mentoring engineers.

Design, develop, and optimize Python-based back-end services and microservices; integrate and deploy AI/ML models; manage containerized applications with Docker/Kubernetes; maintain PostgreSQL and MongoDB databases; use Terraform/Helm for IaC; work with cloud platforms (GCP/AWS/Azure) and CI/CD; collaborate with DevOps, data scientists, and engineers.

Lead design and maintenance of ETL pipelines and semantic models; build and optimize complex SQL transformations and Power BI dashboards (DAX, Power Query, RLS); manage end-to-end BI projects; optimize performance; document data lineage and schemas; mentor junior analysts and enforce BI best practices.

Design, maintain, and enhance internal Power BI dashboards and data models; administer Power BI Service (access, workspaces, gateways); perform data ingestion and transformation using SQL/Python; develop reusable tabular models and DAX; support stakeholders with ad-hoc reporting, training, and Power Platform tasks; document solutions and run demos.

Lead front-end development using React/Next.js, optimize client-side performance, ensure cross-browser compatibility, collaborate with backend and designers, maintain code quality with tests and reviews, and manage cloud deployments and IaC (Terraform/Helm) across GCP/AWS/Azure for AI-powered SaaS.

Lead architecture, development, and production deployment of GenAI/ML systems (LLMs, RAG, agents). Build backend microservices, data pipelines, and cloud-native deployments (Docker/Kubernetes/Terraform). Ensure performance, monitoring, security, and mentor engineering teams while driving cross-team delivery and client-facing technical leadership.

Support Data Science business line and SaaS product development through cloud architecture, containerization and Kubernetes management, Python automation, CI/CD pipelines, cost optimization, and collaboration with Data Scientists, Engineers and consultants.

Design and build production-grade Generative AI solutions: benchmark and deploy LLMs, implement RAG with vector DBs, create multimodal systems and agents, drive MLOps/CI-CD, ensure security/compliance, integrate models into microservices, and support PoCs to enterprise rollouts.

Lead and grow a platform/DevOps/SRE team to design, build, and operate cloud-native MLOps and developer platforms (Terraform, Docker, Kubernetes, CI/CD). Ensure reliability, scalability, observability, security, cost optimization, and strong developer experience while partnering with product, data, and security teams.

Lead platform architecture, standardize multi-cloud infrastructure and CI/CD, drive reliability engineering (SLOs/SLIs, incident response), mentor senior engineers, and own escalations for complex deployment, security, cost, and scaling challenges across AI Factory products.

Support consulting teams by collecting, curating, and classifying strategic data, leveraging AI-enabled research tools to generate market and account intelligence, produce briefings and recommendations, promote reusable solutions, and coordinate cross-functional knowledge sharing to strengthen business development and client positioning.

Lead and grow a cross-functional AI platforms team to productionize LLM-powered solutions. Own platform roadmap, architecture, MLOps pipelines, vector DB integrations, security/compliance, and cross-functional stakeholder alignment to deliver scalable, reliable AI services.

Responsible for leading end-to-end recruitment for technical and consulting roles, driving talent mapping, and providing an exceptional candidate experience.

The Engineering Manager will lead the design and delivery of cloud-native engineering projects, manage software engineering teams, enhance technical strategies, and ensure operational excellence in the AI Factory's product development.

The Senior Full Stack Engineer will develop and optimize APIs and services using .NET Core/C# and Angular, while managing both backend and frontend components. Responsibilities include engaging clients, deploying applications in cloud environments, maintaining code quality, and contributing to system design.

Collect, curate, classify, and maintain knowledge assets from proposals, deliverables, methodologies, and external sources. Apply metadata, taxonomies, and governance standards, use AI/NLP tools to automate tagging and improve searchability, support consulting teams with content retrieval, and generate reporting on repository usage and data quality.

Own the product lifecycle for enterprise AI-enabled solutions: define strategy and roadmap, lead discovery, define requirements and KPIs, prioritize backlog, coordinate engineering/data/design/delivery, ensure secure and responsible AI deployments, and measure adoption and business impact.