Hafijur brings 8+ years of progressive experience as a Python developer and ML specialist, evolving from backend engineering at Verizon and United Airlines to leading full-stack initiatives at enterprise firms like Cisco, Infosys, and Citigroup. His arc spans data engineering, NLP/computer vision, REST API design, and team leadership—combining production-grade Python with modern DevOps and cloud deployment.
Route to AI Engineer, Data Engineer, Data Science Engineer teams building high-throughput services in the candidate's core stack.
End-to-end Python ML pipelines (regression, classification, NLP, computer vision). RESTful API design and microservice architecture at scale. PostgreSQL/MySQL/NoSQL schema design and optimization under high throughput. Team leadership and mentorship in Agile environments.
Platform Engineer, Full-Stack Backend Engineer, Machine Learning Engineer, Data Engineer.
Remote-first. Hybrid considered for high-alignment local roles. Based in New York, US.
Targeting $80K+. Currently: Software Engineer at Pypes LLC.
Recruiter screen → hiring-manager review → technical conversation around Citigroup Currency Exchange Dashboard, Customer Retention Modeling (Infosys), Financial Data Analysis Tool (Citigroup).
Hafijur's work in Platform Engineer, Full-Stack Backend Engineer, Machine Learning Engineer translates directly into adjacent domains with similar architecture, scale, and reliability needs.
The next pages convert the resume into a reusable proof index: production systems, platform architecture, org-wide pattern ownership, and technical leadership.
This reusable proof index maps common senior/staff engineering requirements to candidate proof. Role-specific addenda extend — not replace — this base matrix.
Requirement: Deliver on citigroup currency exchange dashboard at production scale.
Proof: Led Python team designing RESTful APIs and data pipelines for global banking transaction system handling international currency transfers
Requirement: Deliver on customer retention modeling (infosys) at production scale.
Proof: Engineered predictive churn model using XGBoost, SVC, Random Forest; feature engineering and model selection on multi-sector client data
Requirement: Deliver on financial data analysis tool (citigroup) at production scale.
Proof: Created Pandas/NumPy statistical analysis and reporting engine for financial dataset insights and visualization
Requirement: Deliver on sentiment analysis nlp system at production scale.
Proof: Built text classification pipeline using SVM, Random Forest, TF-IDF, NLTK to categorize opinions with high accuracy across product domains
Requirement: Ship work that requires end-to-end python ml pipelines (regression, classification, nlp, computer vision).
Proof: Demonstrated at prior roles.
Requirement: Ship work that requires restful api design and microservice architecture at scale.
Proof: Demonstrated at prior roles.
github.com/hafijur-python — public repositories, contribution activity, and open source project surfaces.
https://gethiringfunnel.com/u/hafijur-rhaman
Hosted candidate portfolio with positioning, proof points, and conversion kit surface for recruiter routing.
www.linkedin.com/in/hafijur-rhaman
Professional profile and recruiter connection path.
rhaman.netlify.app
Additional portfolio and technical writing surface.
This kit is designed to survive internal forwarding. The fastest next step is a recruiter screen, hiring-manager review, referral handoff, or direct call.
Primary fit: AI Engineer, Data Engineer, Data Science Engineer.
Ask about availability to discuss a senior/staff engineering opportunity.
Handoff email with routing context for internal referral.
Direct phone action for recruiter screen or same-day routing.
Persistent candidate surface for routing, resume, and proof surfaces.
Professional profile and recruiter connection path.
Public engineering surface, repositories, and OSS project path.
Hafijur Rhaman is a New York, US-based AI Engineer. Track record across 0 roles with expertise in . Best fit: AI Engineer, Data Engineer, Data Science Engineer.