Senior Staff Software Engineer
at Deepintent
Pune, India, hybrid, senior, full time, 8+ years
posted 02 Sept 2025
- JVM
- Airflow
- PostgreSQL
- Cassandra
- Kafka
- Spring Boot
- LLM
- Cursor
- Flink
- Docker
- MySQL
- AWS
- Java
- ClickHouse
- GraphQL
- Redis
- Spring Data
- GitHub Copilot
- REST
- GCP
- Claude Code
- RAG
- Spark
- MCP
- Kubernetes
About the role
Posted: 2025-09-02
DeepIntent is the leading healthcare marketing platform, purpose-built to help marketers plan, activate, and optimize data-driven campaigns with speed and precision. Trusted by the world’s top healthcare brands and their agencies, DeepIntent uniquely unites media, identity, and real-world clinical data to power privacy-safe, omnichannel marketing across every screen. Backed by patented technology and proven outcomes, DeepIntent’s platform delivers measurable audience quality and script lift at scale. Learn more at www.deepintent.com.
What you would do
You'll be the technical lead for a backend product line in our data and analytics platform. The platform lets healthcare marketers and analysts work with privacy-protected real-world data, run queries at scale, build audiences and use AI-assisted workflows. You will own the architecture of high-throughput, secure backend services built on Java and Spring Boot, and help shape the technical roadmap.
- Provide technical leadership for your product line. Own the architecture of backend services, including service boundaries, data modelling, storage choices and scalability.
- Design multi-tenant, privacy-first data flows across services and environments, with healthcare compliance in mind.
- Lead cross-team initiatives end to end, from design through rollout, working closely with Product, Infrastructure and partner teams.
- Build and evolve data-intensive and asynchronous systems using distributed query and processing engines, workflow orchestration and messaging platforms such as Kafka. Use datastores like Redis (caching, counters, rate limiting, locking, pub/sub) where they fit, alongside relational and analytical stores.
- Lead the integration of AI into our products and engineering workflows. This includes LLM-powered features, agentic workflows, retrieval over metadata or documents, and tool integrations via the Model Context Protocol (MCP). Design for grounded output, human approval, cost control and measurable quality.
- Establish engineering best practices for API design, code quality, testing, security and data privacy.
- Design observability (metrics, logging, tracing, alerting) with tools such as Grafana and Prometheus. Lead deep-dive investigations into production issues and run blameless postmortems.
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