Website:
vectoriq.ai
Job details:
Required Qualifications
- 8–10 years of professional software engineering experience (At least 1+ year in GenAI Frameworks)
- Expertise in below skills for production systems
Role Overview
We are looking for a Principal AI Engineer to lead and scale a distributed GenAI engineering team based in India. This is a hands-on technical leadership role combining 50% coding and 50% architectural guidance, code reviews, and mentorship.
You will serve as the single technical point of contact for US leadership and be accountable for the technical quality, delivery, and maturity of the offshore team. The ideal candidate has deep Python expertise, strong applied GenAI experience, and proven experience building and operating production-grade systems on Microsoft Azure or similar cloud hyperscalers.
Key Responsibilities
Technical Leadership & Architecture
- Own the end-to-end technical architecture for GenAI applications, from design through production
- Define and enforce clean architecture principles, separation of concerns, and scalable system design
- Provide architectural guidance across:
- Backend (Python), Frontend (React preferred), GenAI orchestration, Azure cloud infrastructure
- Review and approve technical designs with a focus on performance, scalability, reliability, and maintainability
- Anticipate and mitigate production challenges, including latency, throughput, cost, and operational risks
Hands-On Development (≈50%)
- Contribute directly to the codebase with a strong focus on:
- Production Quality Python backend services
- GenAI pipelines and orchestration layers
- Performance- and scale-critical components
- Perform deep code reviews and refactoring where needed
- Troubleshoot complex production issues and guide resolution
GenAI & Applied AI Engineering
- Design and guide implementation of applied GenAI solutions, including:
- Retrieval-Augmented Generation (RAG)
- Agent-based workflows
- Prompt orchestration and evaluation strategies
- Provide technical leadership across frameworks such as:
- LangChain
- LlamaIndex
- Azure OpenAI SDK or similar
- Vector search technologies (e.g., Azure AI Search)
- Experience implementing various LLM-powered APIs in production including prompt design
- Evaluate and adopt new AI techniques intentionally, avoiding unnecessary complexity
Backend Code Maturity & Engineering Standards
- Define and enforce Python coding standards and best practices
- Strong experience building production APIs using FastAPI, including async request handling, Pydantic-based data modeling, API design best practices, testing, and deployment in cloud environment
Azure Cloud & Platform Ownership
- Hands-on ownership of Azure-based architectures (Azure OpenAI, App Services, Functions, Storage, Azure AI Search), including building, deploying, and operating secure, reliable, scalable, and cost-efficient production systems, and approving all infrastructure and deployment changes.
DevOps & Engineering Discipline
- Define and enforce DevOps best practices, including:
- GitHub and/or Azure DevOps workflows
- Branching strategies and pull request standards
- CI/CD pipeline design and release discipline
- Promote DevOps maturity across the team
- Ensure consistent use of version control, automation, and deployment hygiene
Team Leadership & Accountability
- Provide technical leadership to a team of 5–7 engineers
- Establish internal engineering guidelines and playbooks
- Raise the team’s overall Python maturity through mentorship and reviews
- Act as the technical escalation point for the offshore team
- Be accountable for offshore delivery quality, timelines, and technical outcomes
- Identify skill gaps and proactively drive improvement plans
Cross-Geo Communication
- Serve as the single technical interface between the India-based team and US leadership
- Communicate clearly on:
- Technical progress
- Risks and trade-offs
- Architecture decisions
- Engage with US leadership 2–3 times per week
- Push back on unrealistic timelines while proposing viable alternatives
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