Head of AI

Responsibilities:
Lead and manage a team of 6-10 Gen AI/NLP engineers working on healthcare automation solutions.
Drive technical excellence while fostering a collaborative, high-performance engineering culture.
Conduct performance reviews, career development planning, and mentorship for team members.
Recruit, interview, and onboard top-tier Gen AI talent to scale the team.
Create individual growth paths for engineers at different experience levels.
Foster knowledge sharing and continuous learning in the rapidly evolving Gen AI landscape.
Define a technical roadmap for evolving from prompt-based systems to RAG and AI agents.
Drive architectural decisions for scalable, cost-effective Gen AI solutions in healthcare.
Oversee model evaluation, selection, and deployment strategies across multiple medical specialities.
Ensure technical debt management and maintainable code standards across the team.
Lead technical design reviews and architecture discussions.
Stay current with Gen AI research and translate innovations into product capabilities.
Collaborate with Product, Clinical, and Business teams to translate requirements into technical solutions.
Manage project timelines, resource allocation, and delivery commitments for Gen AI initiatives.
Drive cross-functional collaboration to ensure seamless integration of AI capabilities.
Oversee A/B testing, experimentation, and data-driven decision making for AI features.
Ensure compliance with healthcare regulations (HIPAA) and coding standards (ICD-10-CPT).
Implement monitoring, observability, and SLA management for production Gen AI systems.
Drive cost optimisation initiatives for LLM usage, infrastructure, and data processing.
Establish best practices for Gen AI MLOps, including model versioning and deployment pipelines.
Ensure system reliability, scalability, and performance optimisation.
Lead incident response and post-mortem processes for AI system issues.
Partner with leadership to define Gen AI strategy and competitive positioning.
Evaluate build vs buy decisions for Gen AI capabilities and tooling.
Drive innovation initiatives and proof-of-concept development for new AI applications.
Represent engineering in executive discussions about AI roadmap and investment priorities.
Requirements:
3+ years of engineering management experience, preferably with AI/ML teams.
Proven track record of managing and scaling engineering teams (5-10 people).
Experience hiring, developing, and retaining top engineering talent.
Strong communication skills with the ability to influence across all organisational levels.
Experience managing remote/hybrid teams and fostering inclusive team culture.
3+ years of hands-on experience with Deep Learning, Large Language Models and Gen AI applications.
Deep understanding of RAG architectures, vector databases, and AI agent frameworks.
Experience with production Gen AI systems: deployment, monitoring, and cost optimisation.
Knowledge of model evaluation, fine-tuning, and prompt engineering best practices.
Understanding of MLOps practices for LLM deployments and model lifecycle management.
Experience with healthcare technology, clinical workflows, or medical data (preferred).
Understanding of healthcare compliance requirements (HIPAA, FDA regulations).
Knowledge of medical coding standards (ICD-10 CPT, SNOMED-CT) is a plus.
Experience with regulated industries and quality assurance processes.
Strong software engineering background with expertise in Python, cloud platforms (AWS/Azure/GCP).
Experience with distributed systems, microservices architecture, and API design.
Understanding of data engineering, ETL pipelines, and real-time processing systems.
Knowledge of modern development practices: CI/CD, testing, code review, agile methodologies.
Experience translating business requirements into technical solutions.
Understanding of cost optimisation and budget management for AI/ML projects.
Ability to communicate technical concepts to non-technical stakeholders.
Experience with product development lifecycle in a fast-paced startup environment.
Proven ability to define and execute technical roadmaps.
Experience with technology evaluation, vendor management, and build vs buy decisions.
Understanding of the AI/ML market landscape and competitive positioning.
Track record of driving innovation while maintaining operational excellence.

Experience
9-13 yrs