Nagarro logo
Nagarro

Nagarro (Frankfurt: NA9) is a leader in digital product engineering and drives technology-led business breakthroughs.

Principal Engineer, Technical Architect

Backend EngineerSoftware EngineerFull TimeRemoteLeadTeam 10,001+Since 1996H1B SponsorCompany SiteLinkedIn

Location

India

Posted

120 days ago

Salary

0

Seniority

Lead

Job Description

Principal Engineer, Technical Architect

Nagarro

• Understanding the client’s business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements. • Mapping decisions with requirements and be able to translate the same to developers. • Identifying different solutions and being able to narrow down the best option that meets the client’s requirements. • Defining guidelines and benchmarks for NFR considerations during project implementation • Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers • Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed. • Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it • Understanding and relating technology integration scenarios and applying these learnings in projects • Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken. • Carrying out POCs to make sure that suggested design/technologies meet the requirements.

Job Requirements

  • Total experience: 13+ Years
  • Strong working experience in machine learning, with a proven track record of delivering impactful solutions in NLP, machine vision, and AI.
  • Should have strong experience in AI/ML solution design, translate business use-cases into AI approach (LLM vs classical ML), define success metrics, evaluation plans, and end-to-end architecture (data, model, serving).
  • Must have experience in AI/ML architecture design and implementation in data / big data using cloud infrastructure.
  • Proficiency in programming languages such as Python, Dotnet, JAVA, and experience with data manipulation libraries (e.g., Pandas, NumPy).
  • Strong understanding of statistical concepts and techniques, and experience applying them to real-world problems.
  • Must have experience in cloud & deployment, scalable inference (batch/real-time), GPUs basics, cost/latency tradeoffs, security/privacy (PII), access control, and compliant data handling.
  • Should have experience in large scale system design, API-first design, frontend & backend programming, and mentoring teams on best practices.
  • Should have experience in database like sql, mysql, oracle.
  • Should have understanding of MLOps and at least one deployment using some of the following technologies: MLflow, Kubeflow, Docker, Kubernetes, model deployment pipelines.
  • Should have designed, developed, and deployed a few AI agents as part of multi-agent systems for autonomous/semi-autonomous decision-making and agent orchestration.
  • Strong understanding of LLMs and foundation models with an expertise in designing and building prompts for prompt development and templates.
  • Practical experience with Generative AI frameworks such as GANs, VAEs, prompt engineering, and retrieval-augmented generation (RAG), and the ability to apply them to real-world problems.
  • Excellent problem-solving skills, with a creative and analytical mindset.
  • Strong communication and teamwork skills, with the ability to work effectively in a team environment and interact with stakeholders at all levels.
  • Experience with AI ethics and responsible AI practices.

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