Jobs at Sia Partners

Lead and grow an engineering team to design, build, and operate cloud-native AI and Generative AI SaaS products. Translate product requirements into scalable microservices, enforce architectural standards, optimize CI/CD and cloud deployments, contribute hands-on code/infra, and collaborate with product, data science, and ops to deliver reliable, production-grade AI systems.

Lead design and implementation of scalable TypeScript/Node.js backend systems, own architecture and TDDs, build APIs and event-driven integrations, optimize databases and performance, define cloud-native deployments, mentor engineers, manage incidents, and participate in hiring and cross-team delivery for the Heka.ai platform.

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.

Lead and grow a cross-functional engineering team to design, build, and operate cloud-native AI and Generative AI platforms. Own platform roadmap, MLOps pipelines, LLM integrations (RAG, vector DBs, orchestrators), security/compliance, and cross-functional alignment to productionize ML models at scale.

Senior individual-contributor DevOps engineer responsible for architecting and standardizing multi-cloud platform foundations, CI/CD pipelines, observability, security, and cost governance for AI Factory products. Drives reliability engineering (SLOs/SLIs, incident response, RCAs), mentors platform engineers, owns escalation for complex infrastructure issues, and builds tooling to enable safe, repeatable deployments and improved developer experience.

Build and own scalable production-grade AI and generative AI backend platforms. Deploy and optimize ML models, design cloud infrastructure with Terraform/Helm on GCP/AWS, containerize with Docker/Kubernetes, ensure data integrity across Postgres/MongoDB, implement monitoring (Prometheus/Grafana/ELK/Loki), ship microservices and platform tooling, and act as technical lead on client engagements.

Design and optimize Python-based microservices, integrate AI/ML models with backend systems, deploy containerized applications using Docker/Kubernetes, manage PostgreSQL and MongoDB, use Terraform/Helm for IaC, work with cloud platforms (GCP/AWS/Azure), maintain CI/CD pipelines, and collaborate across DevOps and data teams to build scalable AI-powered SaaS solutions.

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.

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.

Serve as trusted advisor to ensure successful implementation, adoption, and ongoing satisfaction of Stratumn customers. Manage relationships, lead success reviews, translate customer needs into functional specs, coordinate with Solution Engineers and Product/Engineering, drive implementations and testing, support production transitions, monitor usage, and promote best practices for increased adoption.

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.

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 and grow a platform/DevOps/SRE team to design, build, and operate cloud-native MLOps and developer platforms (AWS/Azure/GCP). Own platform product roadmap, IaC (Terraform), container orchestration (Docker/Kubernetes), CI/CD, observability, cost optimization, reliability, and enablement for data scientists, ML engineers, and application teams.

Lead end-to-end recruitment for technical and consulting roles across India and globally. Build talent pipelines, manage SmartRecruiters ATS, conduct screenings, coordinate interviews, provide market intelligence, and ensure an excellent candidate and hiring experience.

Lead and deliver multiple client-facing analytics engagements, manage an 8-person analyst team, oversee Power BI/SQL-based dashboards and semantic models, ensure ETL/data quality and governance, mentor staff, present insights to senior stakeholders, and support business development.

Supervise a global hybrid L1/L2 IT support team while actively resolving complex incidents, supporting VIP users, managing MDM and device fleets, improving KB/processes, and coordinating worldwide IT deployments.

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.

Develop and optimize React-based user interfaces for AI-powered SaaS, ensuring performance, cross-browser compatibility, and accessibility. Collaborate with backend teams and designers, write unit tests and perform code reviews, and manage CI/CD. Use IaC (Terraform, Helm) and deploy/manage applications on GCP/AWS/Azure.

Lead architecture, development, and production deployment of GenAI solutions (LLMs, RAG, agentic systems). Build backend microservices, data pipelines, and cloud-native deployments (AWS/Azure/GCP). Ensure production readiness (monitoring, optimization, security), mentor engineers, own critical repositories, and act as technical lead in client engagements.