Looking for a job

Prateeka Bhat

@prateekabhat

Software Engineer with 5 years of experience building backend, distributed, and GenAI systems. Strong in Java, Python, FastAPI, AWS, and Kubernetes, w

India

Message

What I'm looking for

I’m looking to build and own production GenAI, backend, and distributed systems end-to-end, from design through delivery, in a fast-paced environment.

I’m a Software Engineer with 5 years of experience building backend systems, distributed infrastructure, and GenAI-powered applications. My work has involved Java and Python, APIs with FastAPI, AWS, Kubernetes, Redis, PostgreSQL, and production AI systems using LLMs, RAG, and agentic workflows.

I enjoy working on problems that combine software engineering and AI, designing reliable services, building data pipelines, integrating LLMs into real workflows, and taking systems from architecture through production. I’m particularly interested in AI infrastructure, developer tools, distributed systems, and building practical AI products rather than just prototypes.

I’m looking for roles where I can take ownership, solve ambiguous engineering problems, and work closely with a strong engineering team.

Experience

Work history, roles, and key accomplishments

Current

Software Engineer, Associate

Current

Goldman Sachs

Jan 2024 - Present (2 years 7 months)

Built ingestion pipelines for GenAI cloud migration platform, architected LLM-as-judge evaluation framework, and improved service catalog data quality by 57%. Led technical discussions and mentored juniors.

Java Python fastAPI AWS Kubernetes TaskIQ Redis LangGraph GPT Dropwizard MongoDB EventBridge Lambda Docker Terraform SQL Snowflake PostgreSQL Junit GraphQL JWT Kong

Software Engineer, Analyst

Goldman Sachs

Aug 2021 - Dec 2023 (2 years 4 months)

Built and maintained microservices for an operational resilience dashboard using React.js and Java Dropwizard, ensuring recovery coverage for 7,000+ business continuity plans. Engineered a Python-based ETL pipeline processing 500K+ records per day into a centralized data lake for Tableau dashboards, resulting in a 50% improvement to production-access governance.