Location
Hybrid (Chennai, India)
Seniority
Middle · 6+ years exp
Employment
Full-Time
First seen by Alion on Oct 25, 2026.
Overview
Company
Impact
Profile match
Overview
TekWissen is a global workforce management provider throughout India and many other countries in the world. The below client is a global company with shared ideals and a deep sense of family. From our earliest days as a pioneer of modern transportation, we have sought to make the world a better place – one that benefits lives, communities and the planet
Job Title: Back-end Software Development Engineering Engineer III
Location: Chennai
Work Type: Hybrid (4 Days work From Office)
Position Description
TekWissen is a global workforce management provider throughout India and many other countries in the world. The below client is a global company with shared ideals and a deep sense of family. From our earliest days as a pioneer of modern transportation, we have sought to make the world a better place – one that benefits lives, communities and the planet
Job Title: Back-end Software Development Engineering Engineer III
Location: Chennai
Work Type: Hybrid (4 Days work From Office)
Position Description
- Employees in this job function develop and maintain the back-end/ server-side parts of an application, typically consisting of APIs, databases and other services containing business logic.
- They work with various languages and tools to create and maintain services on-prem or in the cloud.
- Engage with customers to understand their use-cases and requirements
- Solve complex problems by designing, developing, and delivering using various tools, languages, frameworks, and technologies
- Align with architecture guidelines for unified and coherent approach to development
- Design, develop, and deliver new code using various tools, languages, frameworks, and technologies
- Develop and maintain back-end applications like APIs and microservices using server-side languages like Java, Python, C#, etc.
- Collaborate with front-end developers to integrate user interface elements and with cross functional teams like product owners, designers, architects etc.
- Manage application deployment to the cloud or on-prem, health and performance monitoring, security hardening and disaster recovery for deployed applications
- Manage data storage and retrievals in applications by utilizing database technologies such as Oracle, MySQL, MongoDB, etc.
- Promote improvements in programming practices, such as test-driven development, continuous integration, and continuous delivery
- Optimize back-end infrastructure and deployment practices to improve application resiliency and reliability
- Support security practices to safeguard user data including encryption and anonymization
- Spring Boot, AI, PostgreSQL, Java
- SonarQube, GCP, Pub/Sub
- Engineer 3 Exp: Proficient In 2 coding lang. or adv. Prac. in 1 lang.
- 6+ years in IT;
- 4+ years in development
- Prompt Engineering: Experience crafting effective prompts and workflows for code understanding, documentation, and generation.
- LLM Integration: Exposure to building applications that integrate LLMs (e.g., RAG pipelines, embeddings, vector databases, LangChain, or similar frameworks).
- Python: Familiarity with Python for scripting, notebooks, and AI/ML tooling.
- Cloud: Experience with cloud platforms (GCP, AWS, or Azure) and their AI/ML services.
- Legacy Modernization: Prior experience reverse-engineering or modernizing legacy systems.
- Documentation Tooling: Experience generating architecture diagrams, API docs, or knowledge bases (including AI-assisted approaches).
- Bachelor's Degree
- Understand Complex Systems Fast: Use AI-assisted techniques (Copilot, LLMs, code-analysis notebooks) to explore, map, and comprehend large existing applications, services, and their interdependencies.
- Build & Maintain Backend Services: Design, develop, and optimize robust microservices and APIs using Java and Spring Boot.
- Reverse-Engineer & Document Legacy Logic: Analyze undocumented or legacy code, extract business logic, and produce clear technical documentation, diagrams, and knowledge artifacts—leveraging LLMs to accelerate the process.
- Apply AI to Engineering Workflows: Use LLMs and notebooks for code comprehension, test generation, refactoring assistance, dependency analysis, and impact assessment.
- Establish good practices for prompt design, validation, and safe use of AI-generated output.
- Improve Developer Productivity: Champion AI-assisted development practices across the team, sharing patterns, tooling, and guardrails that help engineers work faster without compromising quality.
- Ensure Quality & Correctness: Write comprehensive tests and rigorously validate AI-assisted output—treating AI as an accelerator, never a substitute for engineering judgment.
- Collaborate: Work closely with architects, product managers, and fellow engineers to translate legacy understanding into modernization and enhancement plans.
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