AI Engineering Manager

Description Anju Software AI Engineering Manager 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. Core Responsibilities Technical Leadership & Architecture 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 AI Framework & Methodology Expertise 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 Team Leadership 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 Delivery & Outcome Ownership 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 AI-Driven Engineering Excellence Leverage AI-assisted development tools to improve velocity Optimize AI cost-performance tradeoffs Embed automation into testing and CI/CD pipelines Qualifications 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 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.

The AI Engineering Manager leads a cross-functional team to design and deliver scalable, AI-powered system architectures. They are responsible for driving an AI-first culture and ensuring the delivery of secure, stable, and measurable AI capabilities.

Candidates need over 7 years of software engineering experience with at least 2 years in technical leadership and hands-on experience deploying AI systems. Proficiency in LLM integration, RAG architectures, and cloud platforms is required.

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• AI Architecture
• LLM Integration
• RAG Architectures
• Vector Databases
• LangChain
• Semantic Kernel
• LlamaIndex
• Prompt Engineering
• AI Governance
• Cloud Platforms
• Distributed Systems
• Technical Leadership
• Model Monitoring
• CI/CD Pipelines
• Software Engineering
• QA Management

• Technology
• Software
• Management & Leadership
• Engineering
• Healthcare

Expérience minimale

5+ ans

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Niveau d’expérience

Mid-Senior level