Senior Software Engineer

End Date

Monday 29 June 2026

We Support Flexible Working – Click here for more information on flexible working options

Flexible Working Options

Hybrid Working

Job Description Summary

Lloyds Banking Group is the UK’s largest Digital, Retail and Commercial Bank with a focus on Helping Britain Prosper.

We’re on the mission to build the bank of the future, and we need your help do it. Continuing our extensive transformation programme, we're redefining what a bank is from the inside out. Our technology, our culture, and our mind-set is changing to craft a true engineering-led organisation.

Job Description

Role: Senior/Lead Software Engineer
Experience: 4-15 years
Location: Hyderabad
Job Type: Full Time

Role Description & Responsibilities:

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 scope

AI, NLP & Document AI (Primary Differentiator)

• NLP fundamentals:

• Text extraction, classification, entity recognition

• Document AI:

  • OCR, document parsing, structure

  • d/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