Jobs at Sia Partners

Build and deploy production-grade Generative AI solutions for enterprise clients. Translate business needs into technical deliverables, develop Python services and APIs, integrate LLMs and enterprise systems, and operate solutions on major cloud platforms. Lead technical discovery, testing, observability, security, troubleshooting, documentation, knowledge transfer, and client communication throughout the delivery lifecycle.

Designs, deploys, maintains, and supports global Meraki and UniFi network infrastructure across 45 offices. Administers Microsoft 365, Entra ID, Intune, and Azure; develops PowerShell and Python automation using APIs; provides advanced network and application support; performs data migrations, documents systems, supports acquisitions, and assists with international office openings.

Collect, curate, classify, and organize strategic knowledge assets from internal and external sources. Apply metadata, taxonomies, naming conventions, quality controls, and governance standards across repositories. Use AI-enabled tools such as NLP, semantic search, and automated tagging to improve processing and retrieval. Identify content gaps and inconsistencies, support repository maintenance, generate usage and quality reports, and assist consulting teams with knowledge access.

Develop scalable AI-powered SaaS web applications across frontend and backend systems. Build React and TypeScript interfaces, Python services and REST APIs, database integrations, automated tests, and cloud-native deployments. Use Docker, Kubernetes, Terraform, Helm, and cloud platforms to manage infrastructure and releases. Collaborate with product, design, DevOps, and engineering teams while optimizing performance, reliability, security, and code quality.

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.

Build and deploy enterprise Generative AI applications using LLMs, RAG pipelines, vector databases, multimodal models, and autonomous agents. Develop prompt flows, benchmark and fine-tune models, implement MLOps practices, deploy solutions across major cloud platforms, and integrate AI capabilities into APIs and microservices. Collaborate with consultants, data scientists, engineers, architects, and customers to deliver secure, scalable, compliant, and cost-effective GenAI solutions.

Provide global Level 1 and Level 2 technical support through ticketing, phone, Teams, and on-site channels. Diagnose hardware, software, network, account, and access issues; configure Windows and Mac workstations; manage devices, inventory, and lifecycle activities; document resolutions; meet ITSM and SLA requirements; support VIP users; and collaborate with international IT teams in a 24x7 rotational shift environment.

The DevOps Engineer supports consulting engagements, SaaS product development, and data-focused projects. Responsibilities include managing cloud architecture and services, optimizing costs and access, containerizing and orchestrating applications with Docker and Kubernetes, developing Python automation tools and microservices, implementing CI/CD pipelines, and contributing to scalable technology, architecture, and governance decisions.

Own end-to-end recruitment for technical, consulting, and corporate roles across India and global locations. Develop sourcing strategies, build talent pipelines, conduct screening interviews, coordinate assessments, maintain ATS records, and support hiring teams. Provide talent market intelligence on compensation, sourcing challenges, and competitors, while managing career-fair outreach and delivering a strong candidate experience from sourcing through offer.

Design, build, and maintain ETL pipelines, semantic models and SQL transformations. Develop and optimize Power BI dashboards (DAX, Power Query, RLS), lead end-to-end BI projects, troubleshoot performance, document data lineage, and mentor junior analysts to enforce BI best practices.

Lead automation testing and QA activities within an agile team: design and execute test automation, produce secure high-quality code, create architecture artifacts, analyze large datasets to improve systems, identify hidden issues, and contribute to engineering communities and inclusive team culture.

Design, build, and maintain Power BI dashboards and reusable tabular data models; administer Power BI Service; ingest and transform data using SQL/Python and ETL tools; support stakeholders with ad-hoc reporting, documentation, demos, and Power Platform requests.

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

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.