AI Engineering Manager- United States
About The Position
The AI Engineering Manager leads a cross-functional team (Development & QA) and owns technical architecture, delivery outcomes, AI-enabled system design and driving an AI first culture among your team. This role is both strategic and hands-on. It requires strong expertise in modern AI frameworks, applied AI architectures, and scalable system design. The manager is accountable for delivering stable, secure, AI-powered capabilities — not just managing execution. About Anju Software Anju Software delivers end-to-end solutions for the life sciences industry, supporting clinical trials, medical affairs, and scientific data management with precision, compliance, and operational rigor. Our products help pharmaceutical, biotech, and medical device companies bring therapies to market faster and more efficiently. Anju is part of Valsoft Corporation, a global acquirer and operator of vertical market software businesses. Valsoft invests with a long-term mindset, empowering each company to operate autonomously while benefiting from shared capital and operational expertise. We are entering a new phase of growth, focused on embedding AI deeply into our systems and workflows. We are excited to add talent who will help lead our transformation into a truly agentic, automation-driven organization that redefines how work gets done in life sciences.
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
Nice To Haves
- Experience in regulated industries
- AI governance and compliance knowledge
- Model lifecycle management and monitoring tools
Responsibilities
- Own product architecture, including AI/LLM-integrated components
- Design scalable, secure, and maintainable systems
- Lead decisions involving: o LLM integration (OpenAI, Azure OpenAI, etc.) o RAG architectures and vector databases o 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: o Retrieval-Augmented Generation (RAG) o Prompt engineering and evaluation o AI output validation and guardrails o Human-in-the-loop workflows o 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
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Manager
Education Level
No Education Listed
Number of Employees
101-250 employees
