Software Engineer
As Software Engineer Contribute to applied R&D by designing, developing, and maintaining software solutions for next-generation systems. Translated business and system requirements into scalable software designs, implemented new features, and performed unit testing to ensure software quality and reliability. Supported Software Configuration Management (SCM), continuous integration, and automation of build and deployment processes to improve development efficiency. Collaborated with cross-functional teams to deliver customer-focused solutions, resolve technical challenges, and continuously enhance products and operational processes using Agile development practices.
- Designed and defined APIs for integrating service automation platforms with Nokia products.
- Collaborated with internal and external teams to deliver efficient service automation solutions.
- Developed and optimized automation workflows to improve operational efficiency.
- Resolved complex performance, integration, and automation issues.
- Applied business and technical expertise to align DevOps solutions with organizational goals.
- Improved automation, deployment processes, and operational efficiency through continuous improvements.
- Mentored DevOps engineers and promoted knowledge sharing and best practices.
- Coordinated team activities, assigned tasks, and supported project delivery and team development.
You have:
- Bachelor’s degree with 10-12 Years of experience in AI/ML engineering and solution development.
- Strong experience in AI/ML engineering, solution architecture, and end-to-end AI solution delivery.
- Deep understanding of RAG, prompt engineering, vector databases, embeddings, and model evaluation techniques.
- Hands-on experience with LLMs, generative AI technologies, and agentic AI frameworks for building intelligent applications and orchestration workflows.
- Strong knowledge of software engineering best practices, including APIs, automation platforms, version control, testing, CI/CD, deployment, and responsible AI principles related to governance, security, and privacy.
It would be nice if you also had:
Experience with LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, OpenAI Agents SDK, or equivalent agent orchestration frameworks.
orchestration frameworks for intelligent automation.
Automated infrastructure provisioning and management using Terraform and Infrastructure as Code (IaC) practices.
Designed and deployed cloud-based solutions on Azure, AWS, and Google Cloud platforms.
Applied MLOps best practices for enterprise AI deployments and leveraged automation certifications to deliver scalable, reliable solutions.