Salary
≈ $18k – $46k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Senior
First seen by Alion on Oct 1, 2026.
Overview
Company
Impact
Profile match
NeoSapien is a health-tech firm developing wearable habit management devices that analyzes conversations, habits, and routines to provide personalized insights and guidance for habit formation.
Responsibilities:
- Scale high-throughput ingestion, asynchronous processing and low-latency APIs.
- Use profiling and realistic load tests to find bottlenecks, improve concurrency and resource use, and prove behaviour under sustained and burst traffic.
- Build dependable processing: bounded retries, idempotency, backpressure, safe recovery and clear ownership of failed or delayed work.
- Improve database queries, indexing, caching and service performance.
- Own capacity planning and cost per successful workload.
- Measure throughput alongside p95/p99 latency, error rates and infrastructure cost.
- Lead thorough design and code reviews for concurrency, data correctness, failure recovery, security, observability and test coverage.
- Validate changes with realistic load tests, safe migrations and rollback plans.
Requirements:
- You've been a Backend Lead, Tech Lead or equivalent, leading engineers while personally building high-performance production systems.
- Show measurable improvements in scale, latency, reliability and cost, plus the team outcomes from your reviews and coaching.
- Strong academic pedigree from a top engineering/computing institution, plus depth in queues, databases, caching, consistency and failure recovery.
- College examples are in the recruiter brief; shipped systems and leadership evidence remain essential.
- Production depth in at least one of Python, Go or Rust; you need not know all three.
- Hands-on cloud experience is required: GCP preferred, AWS also relevant.
- You've deployed and scaled services, owned observability and security, and improved cloud cost.
- Understand concurrency, profiling and memory/CPU tradeoffs.
- You communicate clearly, mentor through real technical work and use AI tools with review and verification.
- Experience supporting audio or AI workloads is useful, not essential.
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