- Location
- Hyderabad Knowledge Park Tower 2, India
- Workplace
- Hybrid
- Type
- Full-time
- Department
- Engineering
- Seniority
- Lead
- Experience
- 10+ years
- Closing date
- Today
- Source
- Workday
Description
End Date
Sunday 23 August 2026We Support Flexible Working – Click here for more information on flexible working options
Flexible Working Options
Hybrid WorkingJob Description Summary
1. Minimum 10 years of Strong expertise in NLP, Document AI, and AI-driven data processing systems, Solid software engineering skills with focus on clean, scalable, and production-grade solutions, Hands-on experience with data pipelines and cloud-native platforms (GCP), Ability to design and deliver end-to-end AI-enabled solutions within team scopeJob Description
- Experience: 9- 15 years
Location: Hyderabad
Job Type: Full Time
AI, NLP & Document AI (Primary Differentiator)
- NLP fundamentals:
- Text extraction, classification, entity recognition
- Document AI:
- OCR, document parsing, structured/unstructured data extraction
- LLMs / GenAI:
- Prompt engineering
- Retrieval-Augmented Generation (RAG)
- Knowledge of document workflows:
- Input → processing → enrichment → output
Data Engineering & Processing (Tech & Data Arch)
- Data pipelines (ETL/ELT)
- Batch and streaming data processing
- Handling large document datasets
- SQL, BigQuery / data platforms
- Data transformation and enrichment
Software Engineering Excellence (Core Expectation)
- Strong programming skills (Python/Java)
- Writing clean, efficient, maintainable code
- Use of design patterns (API design, modularisation)
- Code reviews and engineering best practices
- Unit + integration testing
Cloud & Platform Engineering
- Cloud platforms (GCP preferred):
- BigQuery, Vertex AI, storage, compute
- Containerisation (Docker)
- Kubernetes basics
- API-based services
DevOps & CI/CD
- CI/CD pipelines (Jenkins, GitHub Actions, etc.)
- Source control (Git)
- Automated builds and deployments
- Environment management
Reliability, Performance & Observability (Important)
- Logging and monitoring basics
- Performance tuning (latency of AI APIs, pipelines)
- Understanding system failures and debugging
- Awareness of scalability constraints
System & Solution Design (Team-Level)
- Design small-to-medium systems
- API-first design thinking
- Integration of AI + data + services
- Understanding trade-offs (performance vs cost vs complexity)
Collaboration & Delivery
- Work with:
- Product owners
- Data scientists
- Platform teams
- Agile practices (stories, sprints, backlog)
- Communicate technical solutions clearly
Skills
PythonJavaGCPDockerKubernetesJenkinsCI/CDSQLNLPBigQueryData EngineeringETLGitGitHubAgileDevOps
