Staff Software Engineer - Backend

About the role

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'll Do:

- Provide technical leadership across multiple teams and backend systems, owning the architecture of high-throughput, low-latency services built primarily on Java and Spring Boot.

- Drive architecture decisions for distributed systems, including service boundaries, data modelling, storage choices, and scalability, so the platform stays future-proof as volume and complexity grow.

- Tackle the most complex architectural challenges in your area, and partner with Tech Leads and Engineering Managers to shape the technical vision and roadmap.

- Lead critical cross-team technical initiatives end to end, from design through rollout, aligning engineering work with product and business goals.

- Act as the technical lead for your product line, breaking down complex problems into well-defined work, providing clear technical guidance, and unblocking engineers.

- Mentor senior and junior engineers through design reviews, code reviews, and pair programming, raising the technical bar and fostering a culture of ownership and continuous learning.

- Design and build systems that make effective use of Redis across a range of patterns, such as caching, real-time counters, rate limiting, distributed locking, pub/sub, and streams, alongside other datastores.

- Build and evolve event-driven and asynchronous systems using messaging and streaming platforms such as Kafka.

- Lead the integration of AI into our products and engineering workflows, including LLM-powered features, agentic workflows, retrieval-augmented generation (RAG), and tool integrations via the Model Context Protocol (MCP).

- Champion AI-assisted software development across the team, setting standards for how engineers use coding agents and AI tools responsibly to improve speed and quality.

- Establish and enforce engineering best practices around API design, code quality, testing, security, and data privacy, with healthcare compliance expectations in mind.

- Design observability strategies (metrics, logging, tracing, alerting) using tools such as Grafana and Prometheus to proactively identify bottlenecks and ensure production stability.

- Lead deep-dive investigations into complex production issues and drive root-cause fixes and blameless postmortems.

- Drive knowledge sharing across engineering through technical documentation, design forums, and internal talks.