Sobre esta vaga de Principle Engineer AI na Weekday AI
This role is for one of Weekday’s clients
Location: Bengaluru, Pune
JobType: full-time
Principal Engineer – AI & Full-Stack
Experience: 10+ years (with 5+ years in Python production systems)
Notice Period: 1 month or less
Role Summary Lead the architecture, development, and delivery of production-grade AI-powered applications. Provide technical leadership across the SDLC, mentor engineering teams, and drive enterprise-scale AI adoption.
Requirements
Key Responsibilities
- Define and evolve end-to-end architectures for AI-enabled applications.
- Build scalable backend services, APIs, and AI orchestration layers in Python.
- Develop user-facing applications with React/Angular, TypeScript, HTML, CSS.
- Integrate LLMs, RAG pipelines, vector databases, agents, and enterprise data sources.
- Establish engineering standards for security, reliability, observability, and performance.
- Lead technical design reviews and make build-vs-buy decisions.
- Partner with product, data science, cybersecurity, and cloud stakeholders.
- Mentor senior engineers and contribute to hiring and capability building.
- Promote responsible AI practices (privacy, explainability, governance).
Required Qualifications
- 10+ years of software engineering; 5+ years in Python production systems.
- Strong expertise in FastAPI, Django, Flask, REST APIs, event-driven architectures.
- Full-stack experience with React/Angular.
- Hands-on with LLM apps, prompt engineering, RAG, embeddings, vector DBs, AI agents.
- Cloud-native expertise: AWS, Azure, GCP, Docker, Kubernetes, CI/CD.
- Strong database skills (SQL + NoSQL).
- Proven ability to lead architecture decisions and influence teams.
Preferred
- Enterprise-scale AI deployment experience.
- Knowledge of MLOps, LLMOps, AI safety controls.
- Familiarity with Azure OpenAI, Bedrock, Vertex AI.
- Consulting/regulated industry experience.
- Relevant certifications in cloud/architecture/AI.
Must-have skills
Python, ReactJS, AngularJS
Good-to-have skills
Generative AI, LLm, rag