Principal Engineer, Technical Architect
RemoteUnited States or India
Job Summary
Translate business use-cases into AI approaches, defining success metrics, evaluation plans, and end-to-end architecture for data, model, and serving layers. Identify optimal solutions from multiple options, narrow down the best fit for client requirements, and carry out POCs to validate suggested designs. Write and review design documents explaining overall architecture, frameworks, and high-level application designs for developers. Map technical decisions to requirements, translate specifications to developers, and resolve code review issues through systematic root cause analysis. Define guidelines and benchmarks for non-functional requirements, ensuring extensibility, scalability, security, and best practices are followed across large-scale system design and API-first implementations.
Required Qualifications
- 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
- 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)
- 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
- Experience in cloud & deployment, scalable inference (batch/real-time), GPUs basics, cost/latency tradeoffs, security/privacy (PII), access control, and compliant data handling
- Experience in large scale system design, API-first design, frontend & backend programming, and mentoring teams on best practices
- Experience in database like sql, mysql, oracle
- Understanding of MLOps and at least one deployment using some of the following technologies: MLflow, Kubeflow, Docker, Kubernetes, model deployment pipelines
- 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
- Bachelor's or master's degree in computer science, Information Technology, or a related field
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