Founding Head of Engineering at Talent.com leading AI - native product development and scaling the engineering team. Owning technical direction and establishing engineering culture.
About the role
- AI Engineering Manager building scalable AI-enabled systems at Anju Software. Leading technical architecture and mentoring teams to enhance AI capabilities in life sciences.
Responsibilities
- Own product architecture, including AI/LLM-integrated components
- Design scalable, secure, and maintainable systems
- Lead decisions involving:
- - LLM integration (OpenAI, Azure OpenAI, etc.)
- - RAG architectures and vector databases
- - AI orchestration frameworks (LangChain, Semantic Kernel, LlamaIndex)
- Ensure system reliability, observability, and cost efficiency
- Establish AI governance and safe usage practices
- Apply modern AI methodologies, including:
- - Retrieval-Augmented Generation (RAG)
- - Prompt engineering and evaluation
- - AI output validation and guardrails
- - Human-in-the-loop workflows
- - Model monitoring and performance evaluation
- Drive experimentation, A/B testing, and telemetry-based decision making
- Lead and mentor developers and QA engineers
- Raise AI literacy across the team
- Establish AI-native coding and review standards
- Balance speed, quality, and architectural integrity
- Own predictable, high-quality releases
- Ensure AI features are measurable, validated, and production-ready
- Act as technical escalation point
- Drive cross-team alignment with Product, Data, and DevOps
- Leverage AI-assisted development tools to improve velocity
- Optimize AI cost-performance tradeoffs
- Embed automation into testing and CI/CD pipelines
Requirements
- 7+ years software engineering experience, 2+ years in technical leadership
- Hands-on experience building and deploying AI-enabled systems
- Strong knowledge of:
- - LLM integration and prompt design
- - RAG architectures and vector search
- - AI orchestration frameworks
- - Cloud platforms (Azure, AWS, or GCP)
- Experience designing scalable distributed systems
- Preferred
- - Experience in regulated industries
- - AI governance and compliance knowledge
- - Model lifecycle management and monitoring tools
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