Role overview
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
What you'll work on
- 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- Convert monolithic or outdated applications into modular, API-driven, microservices-based, or cloud-native architectures where applicable.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.
What we're looking for
- 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.