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Job Closed

Senior Software Engineer

  • Source: LinkedIn
  • Humigent.ai
  • On-site
  • Bengaluru
  • Full-Time
  • Senior

Job Description

Senior Backend Software Engineer – Python & Platform Services About The Role Humigent is an AI-native analytics company helping pharma and life sciences organizations unlock the value of their commercial and medical data. As a Senior Backend Software Engineer, you will design, build, and own the backend services behind our analytics products — APIs, data access layers, caching, and asynchronous processing. You will work across Python, FastAPI and Django, PostgreSQL, Redis, and Celery, collaborating with Engineering, Data, Product, and Delivery to keep our services correct, fast, and dependable under real production load. Exposure to GenAI tooling is a strong plus, as a growing part of our roadmap involves LLM-backed features.

What You’ll Own

  • API & Service Development: Design, build, and maintain backend services and APIs using Python with FastAPI and/or Django. Own API contracts — versioning, pagination, error semantics, and backward compatibility. Structure applications so they remain maintainable as the team and surface area grow. Write services with clear boundaries and testable interfaces.
  • Data & Persistence: Model and optimize data in PostgreSQL — schema design, indexing strategy, query tuning with EXPLAIN, and safe migrations against live systems. Reason about transactions, isolation levels, and locking. Manage connection pooling and query performance as traffic grows.
  • Caching & Asynchronous Processing: Design caching and invalidation strategies with Redis, choosing the right data structures, TTLs, and eviction behavior. Build reliable background and scheduled workloads with Celery — task design, retries, idempotency, rate limiting, and backpressure. Ensure async work fails safely and recovers predictably.
  • Reliability & Performance: Own the performance and reliability of your services — profiling, load behavior, timeouts, and graceful degradation. Troubleshoot production incidents and drive fixes to root cause. Build in observability — metrics, logs, and traces that make failures diagnosable.
  • Engineering Craft & Enablement: Participate in design discussions and technical reviews; document and defend tradeoffs. Review code and collaborate through disciplined Git workflows — branching, PRs, and clean history. Mentor mid-level engineers and raise the quality bar across the team.

What You Bring

  • 6–9 years of hands-on backend engineering experience in a product or SaaS environment
  • Strong production experience with Python — data model, concurrency (GIL, threading, asyncio, multiprocessing), typing, and testing
  • Depth in FastAPI and/or Django — dependency injection, Pydantic validation, ORM internals, middleware, and authentication
  • Strong PostgreSQL skills — indexing, query planning, transactions and isolation, locking, and connection pooling
  • Practical Redis experience — caching patterns and invalidation, data structures, TTL and eviction behavior, and use as a broker
  • Production experience with Celery — task design, broker and backend choices, retry and idempotency patterns, and worker scaling
  • Confident with Git — branching strategies, rebase vs. merge, conflict resolution, and collaborative review practices
  • Solid API design sense and the ability to reason about failure modes, not just happy paths
  • Strong systems thinking and ability to collaborate cross-functionally with engineering and product teams

Nice to Have

  • GenAI, LLM experience — LangChain, LangGraph, agentic or multi-step LLM workflows
  • RAG pipelines, vector databases (pgvector, Pinecone, Qdrant, Weaviate), embedding and chunking strategies
  • Prompt design, evaluation, and cost/latency management for LLM-backed features
  • Docker and containerized deployments; CI/CD pipelines (GitHub Actions or similar)
  • Cloud platform experience (AWS or Azure)
  • Observability tooling (Prometheus, Grafana, Sentry, OpenTelemetry)
  • Event-driven architecture (Kafka, RabbitMQ)
  • Experience with high-traffic or data-heavy systems, or multi-tenant enterprise SaaS
  • Experience in pharma tech, life sciences, or health data products

What We Offer

  • Competitive compensation package aligned with industry benchmarks
  • Direct access to leadership and meaningful ownership over backend architecture
  • Opportunity to build the services behind cutting-edge AI analytics in pharma and life sciences
  • Fast-paced, high-growth environment with a culture of learning and experimentation

Skills

  • Python
  • FastAPI
  • Django
  • PostgreSQL
  • processing-js
  • Redis
  • Celery
  • Asyncio
  • re-base
  • LangChain
  • LangGraph
  • qdrant
  • Docker
  • Github
  • github-actions
  • amazon-web-services
  • microsoft-azure
  • Prometheus
  • Grafana
  • sentry
  • opentelemetry
  • Kafka
  • RabbitMQ
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