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eClerx LLC

Senior .NET Developer (Application Modernization / AI Transformation)

Posted 2 Days Ago
Be an Early Applicant
In-Office
London, Greater London, England, GBR
Senior level
In-Office
London, Greater London, England, GBR
Senior level
The role involves modernizing legacy applications using AI, designing intelligent systems, and optimizing technology stacks, while collaborating with stakeholders and leveraging AI tools.
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Senior .NET Developer (Application Modernization / AI Transformation)

Location: London, UK

Type: Full-time

Department: Technology

Job Summary

eClerx is seeking an Senior Developer to support one of our premier clients, a leading global financial institution on a multi‑year transformation journey. In this role, you will join a global eClerx team responsible for modernize legacy applications, re-engineer existing platforms to a new technology stack, and leverage AI-assisted development tools to accelerate analysis, migration, refactoring, testing, and delivery. The ideal candidate is a hands-on Senior AI Engineer with strong AI skills, responsible for designing, building, and optimizing intelligent systems leveraging LLMs, agentic frameworks, graph databases, Python, and modern AI/ML tools. The role is ideal for someone who enjoys solving complex problems, experimenting with cutting-edge architectures, and shipping production-grade AI solutions.

Responsibilities

  • Collaborate with stakeholders to gather and analyze business requirements for AI-driven automation across the clients’ global operations functions 
  • Contribute to the development of a comprehensive operational strategy for leveraging Agentic AI to drive efficiency, automation, and innovation across the client’s organization.
  • Analyse existing legacy applications, architecture, codebases, integrations, and dependencies to identify modernization opportunities.
  • Design and execute re-engineering strategies for migrating legacy systems to modern, scalable, cloud-ready technology stacks.
  • Use AI-accelerated development tools to improve productivity in code understanding, refactoring, code generation, documentation, testing, and migration.
  • Convert monolithic or outdated applications into modular, API-driven, microservices-based, or cloud-native architectures where applicable.
  • Perform code remediation, refactoring, optimization, and modernization while preserving functional parity with legacy systems.
  • Work hands-on with cutting-edge LLM architectures and tooling
  • Solve challenging logical and engineering problems every day
  • Contribute to CI/CD pipelines, automated testing frameworks, and DevOps practices to enable efficient releases
  • Support the rollout of enterprise-level Agentic AI frameworks, standards, best practices, and delivery methodologies
  • Document and communicate AI solutions and recommendations to technical and non-technical stakeholders clearly and effectively.

Eligibility Requirements

  • Technical experience, with a strong understanding of AI concepts, architectures, and methodologies. 
  • Hands-on experience with LLMs, both commercial and open source, including LangChain, LlamaIndex, agentic AI frameworks, Retrieval-Augmented Generation (RAG), and vector databases. 
  • Experience with graph databases, with Neo4j and Cypher strongly preferred. 
  • Hands-on experience working with legacy technologies and transforming them into modern tech stacks.
  • Demonstrated proficiency in Python, Golang and Java, along with experience using ML and data science libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, SciPy, and Pandas.
  • Strong foundation in experimental design, hypothesis testing, and causal inference methods. 
  • Good understanding of software architecture patterns, system decomposition, and migration strategies.
  • Experience working in Agile development environments and familiarity with Agile tools and practices. 
  • Experience with cloud platforms such as Azure, AWS, or GCP.
  • Strong knowledge of REST APIs, event-driven architecture, databases, and integration patterns.
  • Passion for innovation and a desire to push the boundaries of applied AI. 
  • Financial services industry experience is preferred. 
  • Experience using AI coding assistants / developer productivity tools for code analysis, transformation, documentation, and test generation.
  • Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field. 

 How to Apply

  • Click "Apply Now" to submit your resume through our career site
  • Be sure to include any relevant experience that aligns with the role.
  • Qualified candidates will be contacted by a member of our recruitment team for next steps

About eClerx

eClerx is a leading provider of productized services, bringing together people, technology and domain expertise to amplify business results.​
The firm provides business process management, automation, and analytics services to a number of Fortune 2000 enterprises, including some of the world’s leading financial services, communications, retail, fashion, media & entertainment, manufacturing, travel & leisure, and technology companies. Incorporated in 2000, eClerx is traded on both the Bombay and National Stock Exchanges of India. The firm employs more than 19,000 people across Australia, Canada, France, Germany, Switzerland, Egypt. India, Italy, Netherlands, Peru, Philippines, Singapore, Thailand, the UK, and the USA.

For more information, visit www.eclerx.com  

You can also find us on:

https://www.linkedin.com/company/eclerx/ 

https://www.indeed.com/cmp/Eclerx/about

https://www.glassdoor.com/eClerx

eClerx is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law. We are also committed to protecting and safeguarding your personal data. Please find our policy here

Top Skills

Agentic Ai Frameworks
AWS
Azure
GCP
Go
Java
Langchain
Llamaindex
Neo4J
Pandas
Python
PyTorch
Scikit-Learn
Scipy
TensorFlow

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