Backend Software Engineer
I build distributed, cloud-scale systems that don't fall over.
3.10+ years building high-throughput event pipelines, semantic search engines, and network management platforms.
import pgvector, openai
# Semantic match against profile
query_vector = get_embedding(user_dna)
results = db.execute(
"SELECT job_id, title, "
"cosine_similarity(embedding, :q) "
"FROM jobs WHERE active = true",
q=query_vector
)
print(f"Matched {len(results)} jobs (Avg score: 94.2%)")I'm a backend software engineer with 3.10+ years of experience building distributed, cloud-scale systems. I specialize in Python, Django, and FastAPI — designing APIs, high-throughput event pipelines, and caching layers that handle real workloads at scale.
I've built and scaled a cloud-scale network management platform serving 20,000+ active devices, a real-time PCB manufacturing execution system, and I am currently architecting and building Jobspiq — an AI-native job aggregation platform.
I thrive on end-to-end system ownership, solving performance bottlenecks, and building highly resilient backend architectures that scale seamlessly.
An AI-native job aggregation platform with semantic matching, multi-portal crawling, and full-stack solo deployment. Features a semantic matching engine using bge-base-en-v1.5 embeddings with pgvector cosine similarity, multi-portal Playwright crawlers with SHA-256 deduplication, and a Redis TTL-backed OTP auth system.
Open-source productivity OS with a discipline scoring engine and LLM-powered coaching layer. Features async Celery workers for streak tracking, habit scoring, and background report generation, alongside a context-injected LLM coaching layer with token budgeting.
Open to senior backend roles and interesting problems. I respond to every message — best way to reach me is email.