Senior Engineering Manager - Generative AI

Description :

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 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.