BigStep Technologies Pvt Ltd

Role Description We are looking for an experienced Technical Architect to lead the design and implementation of scalable, high-performance applications. This role requires deep expertise in backend technologies including Node.js, Python, and Java , along with strong experience in AWS cloud architecture . You will be responsible for defining system architecture, guiding development teams, and ensuring best practices in scalability, security, and performance. Qualifications - 10+ years of experience in software development with strong architectural exposure - Expertise in Node.js, Python, and Java - Hands-on experience with AWS services (EC2, S3, Lambda, RDS, API Gateway, etc.) - Strong understanding of microservices architecture and distributed systems - Experience with REST APIs and event-driven architectures - Knowledge of containerization tools (Docker, Kubernetes) - Strong problem-solving and leadership skills Requirements - Design and architect scalable, distributed systems using Node.js, Python, and Java - Define and implement cloud-native solutions on AWS - Lead architectural discussions and technical decision-making - Collaborate with cross-functional teams (product, engineering, DevOps) - Establish best practices for coding, security, and performance optimization - Review code and provide technical guidance to development teams - Ensure system reliability, availability, and scalability - Drive DevOps and CI/CD best practices Benefits - Experience with Infrastructure as Code (Terraform, CloudFormation) - Familiarity with monitoring tools (CloudWatch, Prometheus, Grafana) - Experience working in Agile/Scrum environments

Role Description We are hiring a hands-on NLP Engineer to build robust pipelines that convert policy, regulatory, fintech, and healthcare documents into structured, graph-ready data. You will own the full extraction lifecycle from raw text to clean, schema-validated outputs using classical NLP, deep learning, and LLM APIs. Qualifications - 3–5 years hands-on NLP engineering & real production pipelines, not just model experiments - Strong Python skills: OOP, async programming, packaging, and testing - NLP frameworks: spaCy, HuggingFace Transformers, NLTK - Deep learning: fine-tuning transformer models for sequence labeling and classification - LLM API integration: prompt engineering, structured outputs, and function/tool calling - Data pipeline experience: ETL, batch processing, and text pre-processing at scale - JSON schema design and validation using pydantic or json schema Requirements - Pipeline Development: Design and build end-to-end text extraction pipelines for policy, regulatory, fintech, and healthcare documents - Entity & Clause Extraction: Extract key entities (countries, companies, minerals) and structure policy clauses and obligations - Deep Learning & Transformers: Fine-tune BERT / RoBERTa for NER, text classification, and relation extraction tasks - LLM Integration: Leverage LLM APIs with structured output extraction, prompt engineering, and tool/function calling - Data Engineering: Build scalable Python pipelines for high-volume document processing with robust pre-processing for PDF, DOCX, and HTML - Schema & Graph Readiness: Define and enforce JSON schemas; ensure outputs are clean and compatible with knowledge graph ingestion - Accuracy Improvement: Evaluate model performance, track metrics, and implement feedback loops to improve extraction quality over time Benefits - Experience with legal, regulatory, or policy documents (contracts, compliance filings, government publications) - Familiarity with knowledge graphs or graph databases (Neo4j, RDF) - Document parsing tools: pdfplumber, Docling, Apache Tika - Domain knowledge in fintech or healthcare NLP - Exposure to information extraction benchmarks (CoNLL, DocRED, SciERC)