Jobs at Sia Partners

Hands-on full-stack engineer responsible for designing and developing backend services in .NET Core/C#, building Angular 12+ frontends, owning end-to-end features, engaging with clients to translate requirements, deploying containerized apps to cloud platforms, and maintaining CI/CD, code quality, and system design standards.

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.

Curate, classify, and organize internal and external knowledge assets using AI-enabled tools. Maintain metadata, taxonomy, and repository hygiene; ensure data quality and governance. Support consultants with content retrieval, reporting, and continuous improvement of KM processes.

Support consulting teams by collecting, curating, and classifying strategic data; generate market and account intelligence; leverage AI-enabled tools for insights; coordinate cross-functional knowledge sharing; prepare strategic materials and briefings; monitor community performance and promote reusable solutions and best practices.

Design, build, and optimize React-based front-end interfaces for AI-powered SaaS. Improve client-side performance, ensure cross-browser compatibility, write tests, perform code reviews, collaborate with backend and design teams, and manage cloud deployments and infrastructure as code with Terraform/Helm.

Support the Data Science business line by developing SaaS products and enabling data projects: design cloud architecture, manage containers and Kubernetes clusters, write Python automation and microservices, implement CI/CD pipelines, and advise on scalability, governance, and cost optimization.

Lead architecture, standardization, and scaling of cloud-native platform foundations across multi-cloud environments. Define DevOps standards, CI/CD pipelines, observability, security, cost controls, and reliability engineering practices. Act as a technical escalation point, mentor senior engineers, and deliver hands-on infrastructure improvements enabling safe, repeatable deployments and improved developer experience.

Build and optimize React-based user interfaces for an AI-powered SaaS product. Collaborate with backend teams and designers, ensure cross-browser compatibility, implement state management, write tests, perform code reviews, and manage cloud deployments using IaC (Terraform/Helm) across GCP/AWS/Azure while supporting CI/CD pipelines.

Design and build Generative AI solutions: benchmark and integrate LLMs, implement RAG with vector DBs, develop multimodal models and agents, drive MLOps and deployment on cloud, establish security/compliance guardrails, and support PoCs to enterprise rollouts.

Maintain and optimize production ML/algorithm services: debug, profile and tune for CPU/memory/I/O, add regression tests, implement parallelism, build and maintain REST APIs (Django/DRF or FastAPI), benchmark scalability and costs, ensure high code quality (tests, CI/CD, docs), and collaborate with product/data/QA to meet SLAs.

Support month-end close, raise and post sales invoices, maintain and reconcile general ledger and intercompany activity, manage customer projects and timesheets, monitor collections, reconcile payroll and revenue, and provide ad hoc accounting support for the Mumbai office and group entities.

Provide L1/L2 global IT support via ticketing, phone, Teams or on-site. Troubleshoot hardware, software, network issues; manage accounts, device deployment (Windows/Mac), MDM (Intune/Kandji), document resolutions, escalate complex incidents, and support SLA-driven, 24x7 operations.

Lead and grow a platform/DevOps/SRE team to design, build, and operate cloud-native MLOps and developer platforms. Own platform product roadmaps, IaC, Kubernetes, CI/CD, observability, cost optimization, and developer enablement to support ML, data, and application teams.

Lead and grow an engineering team to design and deliver cloud-native AI/Generative AI SaaS products. Translate product requirements into scalable microservices, drive architecture and cloud best practices (AWS, Docker, Kubernetes, IaC), optimize CI/CD, and support client engagements. Recruit, mentor, and ensure reliable production-grade AI systems while collaborating with product, data science, and global stakeholders.

Lead and supervise a global hybrid L1/L2 IT helpdesk while performing hands-on resolution of complex incidents, supporting VIP users, managing MDM and device fleets, improving knowledgebase and processes, and coordinating cross-region deployments and IT migrations.

Lead architecture, development, and scaling of distributed TypeScript/Node.js backend systems. Design APIs and event-driven integrations, own data and deployment architecture, enforce production readiness and security, mentor engineers, manage incidents and repositories, and drive cross-team delivery and hiring for the Mumbai-based SaaS platform.

Lead architecture, development, and deployment of GenAI backend systems (LLMs, RAG, agentic workflows). Build scalable microservices, data pipelines, and cloud-native deployments (AWS/Azure/GCP) using Docker, Kubernetes, and Terraform. Ensure production readiness, monitoring, cost control, and security; collaborate with data scientists, mentor engineers, and engage in client-facing consulting and technical leadership.

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.