Engineering Manager

Brillio is seeking an experienced Engineering Manager – AI/GenAI to lead the engineering and delivery of complex Artificial Intelligence and Generative AI solutions for our Healthcare clients.

This is a technical engineering leadership role requiring a strong foundation in software engineering, AI/ML, cloud technologies, and modern engineering practices. The Engineering Manager will be responsible for leading cross-functional engineering teams, providing technical direction, managing end-to-end execution, and ensuring AI solutions are scalable, secure, reliable, and production-ready.

The ideal candidate will have experience managing AI/ML and Generative AI projects in a consulting or client-facing environment
, preferably within Healthcare, and should be comfortable engaging with both senior client stakeholders and deeply technical engineering teams.

• Lead the architecture, engineering, development, and production deployment of enterprise AI and Generative AI solutions.
• Provide technical leadership across AI/ML, GenAI, data engineering, cloud, APIs, and application development.
• Guide engineering teams on architecture, design patterns, technology selection, scalability, performance, security, and reliability.
• Review technical designs and ensure engineering solutions meet enterprise architecture and quality standards.
• Drive technical decision-making and resolve complex engineering challenges.
• Ensure AI prototypes and POCs can successfully transition into scalable, production-grade solutions.

Lead engineering initiatives involving technologies and use cases such as:

• Generative AI applications
• Retrieval-Augmented Generation (RAG)
• AI Agents / Agentic AI
• Conversational AI
• Natural Language Processing (NLP)
• Machine Learning and Predictive Analytics
• Prompt Engineering
• Embeddings and Vector Databases
• Model evaluation and optimization
• AI orchestration frameworks
• MLOps / LLMOps
• Responsible AI and AI governance

Experience working with platforms and technologies such as Azure OpenAI, OpenAI APIs, AWS Bedrock, Google Vertex AI, Databricks, MLflow, Lang Chain, Llama Index, Hugging Face, or equivalent technologies is highly desirable.

Lead AI initiatives supporting Healthcare use cases such as:

• Clinical and healthcare data analytics
• Member and patient engagement
• Provider analytics
• Claims analytics
• Care management
• Pharmacy and medication management
• Contact center transformation
• Knowledge management
• Clinical or operational workflow automation
• AI-powered search and knowledge assistants
• Predictive analytics

Ensure solutions appropriately address Healthcare-specific requirements around data privacy, security, HIPAA compliance, explainability, governance, and responsible use of AI
.

Knowledge of healthcare data and interoperability standards such as FHIR, HL7, EDI, claims, member, provider, pharmacy, and clinical data is highly desirable.

• Lead and mentor cross-functional teams of AI Engineers, ML Engineers, Data Scientists, Data Engineers, Software Engineers, Architects, and Dev Ops/MLOps Engineers.
• Provide technical coaching and career development to engineering team members.
• Establish clear engineering standards and expectations.
• Conduct architecture and design reviews.
• Drive code quality, peer reviews, automated testing, and engineering best practices.
• Build a culture of engineering excellence, accountability, experimentation, and continuous improvement.
• Manage globally distributed onshore and offshore engineering teams.

• Python
• PyTorch / Tensor Flow
• Scikit-learn
• MLflow

• LLMs
• Agentic AI
• Embeddings
• Model evaluation and guardrails

• AWS

• Databricks
• Snowflake
• Spark
• SQL
• Data Lakes / Lakehouse

• Python
• Java
• REST APIs
• Microservices
• Event-driven architectures
• React or modern front-end frameworks

• Docker
• CI/CD
• Terraform
• Model deployment and monitoring
• Observability

• Serve as a senior technical point of contact for Healthcare clients.
• Translate business…